Information extraction is generally concerned with the location of different items in any document, may be textual or web document. This paper is concerned with the methodologies and applications of information extraction. The field of information extraction plays a very important role in the natural language processing community. The architecture of information extraction system which acts as the base for all languages and fields is also discussed along with its different components. Information is hidden in the large volume of web pages and thus it is necessary to extract useful information from the web content, called Information Extraction. In information extraction, given a sequence of instances, we identify and pull out a sub-sequence of the input that represents information we are interested in.
Manual data extraction from semi supervised web pages is a difficult task. This paper focuses on study of various data extraction techniques and also some web data extraction techniques. In the past years, there was a rapid expansion of activities in the information extraction area. Many methods have been proposed for automating the process of extraction. We will survey various web data extraction tools. Several real-world applications of information extraction will be introduced. What role information extraction plays in different fields is discussed in these applications. Current challenges being faced by the available information extraction techniques are briefly discussed along with the future work going on using the current researches is discussed.
Algorithm for calculating relevance of documents in information retrieval sys...IRJET Journal
The document proposes an algorithm to calculate the relevance of documents returned in response to user queries in information retrieval systems. It is based on classical similarity formulas like cosine, Jaccard, and dice that calculate similarity between document and query vectors. The algorithm aims to integrate user search preferences as a variable in determining document relevance, as classic models do not account for this. It uses text and web mining techniques to process user query and document metadata.
Survey of Machine Learning Techniques in Textual Document ClassificationIOSR Journals
Classification of Text Document points towards associating one or more predefined categories based
on the likelihood expressed by the training set of labeled documents. Many machine learning algorithms plays
an important role in training the system with predefined categories. The importance of Machine learning
approach has felt because of which the study has been taken up for text document classification based on the
statistical event models available. The aim of this paper is to present the important techniques and
methodologies that are employed for text documents classification, at the same time making awareness of some
of the interesting challenges that remain to be solved, focused mainly on text representation and machine
learning techniques.
An effective pre processing algorithm for information retrieval systemsijdms
The Internet is probably the most successful distributed computing system ever. However, our capabilities
for data querying and manipulation on the internet are primordial at best. The user expectations are
enhancing over the period of time along with increased amount of operational data past few decades. The
data-user expects more deep, exact, and detailed results. Result retrieval for the user query is always
relative o the pattern of data storage and index. In Information retrieval systems, tokenization is an
integrals part whose prime objective is to identifying the token and their count. In this paper, we have
proposed an effective tokenization approach which is based on training vector and result shows that
efficiency/ effectiveness of proposed algorithm. Tokenization on documents helps to satisfy user’s
information need more precisely and reduced search sharply, is believed to be a part of information
retrieval. Pre-processing of input document is an integral part of Tokenization, which involves preprocessing
of documents and generates its respective tokens which is the basis of these tokens probabilistic
IR generate its scoring and gives reduced search space. The comparative analysis is based on the two
parameters; Number of Token generated, Pre-processing time.
Survey on Existing Text Mining Frameworks and A Proposed Idealistic Framework...ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
The document proposes a text mining template-based algorithm to improve business intelligence by categorizing text. It begins with an introduction to data mining and text mining. It then discusses related work on text mining algorithms. The document proposes a methodology using a configuration file to identify fields in documents based on regular expressions. The algorithm reads documents line by line, matches lines to conditions in the configuration file, and stores the identified fields in an array. The array is then used to populate a structured table for analysis to improve decision making. The methodology is experimentally tested on 100 resumes to select candidates, demonstrating its ability to extract structured data from unstructured documents.
Structured and Unstructured Information Extraction Using Text Mining and Natu...rahulmonikasharma
Information on web is increasing at infinitum. Thus, web has become an unstructured global area where information even if available, cannot be directly used for desired applications. One is often faced with an information overload and demands for some automated help. Information extraction (IE) is the task of automatically extracting structured information from unstructured and/or semi-structured machine-readable documents by means of Text Mining and Natural Language Processing (NLP) techniques. Extracted structured information can be used for variety of enterprise or personal level task of varying complexity. The Information Extraction (IE) in also a set of knowledge in order to answer to user consultations using natural language. The system is based on a Fuzzy Logic engine, which takes advantage of its flexibility for managing sets of accumulated knowledge. These sets may be built in hierarchic levels by a tree structure. Information extraction is structured data or knowledge from unstructured text by identifying references to named entities as well as stated relationships between such entities. Data mining research assumes that the information to be “mined” is already in the form of a relational database. IE can serve an important technology for text mining. The knowledge discovered is expressed directly in the documents to be mined, then IE alone can serve as an effective approach to text mining. However, if the documents contain concrete data in unstructured form rather than abstract knowledge, it may be useful to first use IE to transform the unstructured data in the document corpus into a structured database, and then use traditional data mining tools to identify abstract patterns in this extracted data. We propose a novel method for text mining with natural language processing techniques to extract the information from data base with efficient way, where the extraction time and accuracy is measured and plotted with simulation. Where the attributes of entities and relationship entities from structured and semi structured information .Results are compared with conventional methods.
IJRET-V1I1P5 - A User Friendly Mobile Search Engine for fast Accessing the Da...ISAR Publications
Mobile search engine is a meta search engine that imprisonments the user’s favorite in
the form of concepts by mining their click through data. But the search query is limited to small
words unlike those used when interacting with search engines through computers. It has become
popular because of presence of huge number of applications. Smartphone’s carry large amount of
personal information, such as user’s personal details, contacts, messages, emails, credit card
information, etc. User type specific search and finally Ontology based Search. Moreover opinion
mining is conducted to provide feedback and valuable suggestions given by the mobile users. Due
to the different characteristics of the content concepts and location concepts, use different
techniques for their concept extraction and ontology formulation. Moreover the individual users
can use this search engine, which runs on android platform. They can give feedbacks and
suggestions about the search result. Based on the feedback other users can get valuable
information about the services available in their location or nearby location.
Algorithm for calculating relevance of documents in information retrieval sys...IRJET Journal
The document proposes an algorithm to calculate the relevance of documents returned in response to user queries in information retrieval systems. It is based on classical similarity formulas like cosine, Jaccard, and dice that calculate similarity between document and query vectors. The algorithm aims to integrate user search preferences as a variable in determining document relevance, as classic models do not account for this. It uses text and web mining techniques to process user query and document metadata.
Survey of Machine Learning Techniques in Textual Document ClassificationIOSR Journals
Classification of Text Document points towards associating one or more predefined categories based
on the likelihood expressed by the training set of labeled documents. Many machine learning algorithms plays
an important role in training the system with predefined categories. The importance of Machine learning
approach has felt because of which the study has been taken up for text document classification based on the
statistical event models available. The aim of this paper is to present the important techniques and
methodologies that are employed for text documents classification, at the same time making awareness of some
of the interesting challenges that remain to be solved, focused mainly on text representation and machine
learning techniques.
An effective pre processing algorithm for information retrieval systemsijdms
The Internet is probably the most successful distributed computing system ever. However, our capabilities
for data querying and manipulation on the internet are primordial at best. The user expectations are
enhancing over the period of time along with increased amount of operational data past few decades. The
data-user expects more deep, exact, and detailed results. Result retrieval for the user query is always
relative o the pattern of data storage and index. In Information retrieval systems, tokenization is an
integrals part whose prime objective is to identifying the token and their count. In this paper, we have
proposed an effective tokenization approach which is based on training vector and result shows that
efficiency/ effectiveness of proposed algorithm. Tokenization on documents helps to satisfy user’s
information need more precisely and reduced search sharply, is believed to be a part of information
retrieval. Pre-processing of input document is an integral part of Tokenization, which involves preprocessing
of documents and generates its respective tokens which is the basis of these tokens probabilistic
IR generate its scoring and gives reduced search space. The comparative analysis is based on the two
parameters; Number of Token generated, Pre-processing time.
Survey on Existing Text Mining Frameworks and A Proposed Idealistic Framework...ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
The document proposes a text mining template-based algorithm to improve business intelligence by categorizing text. It begins with an introduction to data mining and text mining. It then discusses related work on text mining algorithms. The document proposes a methodology using a configuration file to identify fields in documents based on regular expressions. The algorithm reads documents line by line, matches lines to conditions in the configuration file, and stores the identified fields in an array. The array is then used to populate a structured table for analysis to improve decision making. The methodology is experimentally tested on 100 resumes to select candidates, demonstrating its ability to extract structured data from unstructured documents.
Structured and Unstructured Information Extraction Using Text Mining and Natu...rahulmonikasharma
Information on web is increasing at infinitum. Thus, web has become an unstructured global area where information even if available, cannot be directly used for desired applications. One is often faced with an information overload and demands for some automated help. Information extraction (IE) is the task of automatically extracting structured information from unstructured and/or semi-structured machine-readable documents by means of Text Mining and Natural Language Processing (NLP) techniques. Extracted structured information can be used for variety of enterprise or personal level task of varying complexity. The Information Extraction (IE) in also a set of knowledge in order to answer to user consultations using natural language. The system is based on a Fuzzy Logic engine, which takes advantage of its flexibility for managing sets of accumulated knowledge. These sets may be built in hierarchic levels by a tree structure. Information extraction is structured data or knowledge from unstructured text by identifying references to named entities as well as stated relationships between such entities. Data mining research assumes that the information to be “mined” is already in the form of a relational database. IE can serve an important technology for text mining. The knowledge discovered is expressed directly in the documents to be mined, then IE alone can serve as an effective approach to text mining. However, if the documents contain concrete data in unstructured form rather than abstract knowledge, it may be useful to first use IE to transform the unstructured data in the document corpus into a structured database, and then use traditional data mining tools to identify abstract patterns in this extracted data. We propose a novel method for text mining with natural language processing techniques to extract the information from data base with efficient way, where the extraction time and accuracy is measured and plotted with simulation. Where the attributes of entities and relationship entities from structured and semi structured information .Results are compared with conventional methods.
IJRET-V1I1P5 - A User Friendly Mobile Search Engine for fast Accessing the Da...ISAR Publications
Mobile search engine is a meta search engine that imprisonments the user’s favorite in
the form of concepts by mining their click through data. But the search query is limited to small
words unlike those used when interacting with search engines through computers. It has become
popular because of presence of huge number of applications. Smartphone’s carry large amount of
personal information, such as user’s personal details, contacts, messages, emails, credit card
information, etc. User type specific search and finally Ontology based Search. Moreover opinion
mining is conducted to provide feedback and valuable suggestions given by the mobile users. Due
to the different characteristics of the content concepts and location concepts, use different
techniques for their concept extraction and ontology formulation. Moreover the individual users
can use this search engine, which runs on android platform. They can give feedbacks and
suggestions about the search result. Based on the feedback other users can get valuable
information about the services available in their location or nearby location.
The document provides an overview of the key components and objectives of an information retrieval system. It discusses how an IR system aims to minimize the time a user spends locating needed information by facilitating search generation, presenting search results in a relevant order, and processing incoming documents through normalization, indexing, and selective dissemination to users. The major measures of an IR system's effectiveness are precision and recall.
Towards From Manual to Automatic Semantic Annotation: Based on Ontology Eleme...IJwest
This document describes a proposed system for automatic semantic annotation of web documents based on ontology elements and relationships. It begins with an introduction to semantic web and annotation. The proposed system architecture matches topics in text to entities in an ontology document. It utilizes WordNet as a lexical ontology and ontology resources to extract knowledge from text and generate annotations. The main components of the system include a text analyzer, ontology parser, and knowledge extractor. The system aims to automatically generate metadata to improve information retrieval for non-technical users.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
MalayIK: An Ontological Approach to Knowledge Transformation in Malay Unstruc...IJECEIAES
The number of unstructured documents written in Malay language is enormously available on the web and intranets. However, unstructured documents cannot be queried in simple ways, hence the knowledge contained in such documents can neither be used by automatic systems nor could be understood easily and clearly by humans. This paper proposes a new approach to transform extracted knowledge in Malay unstructured document using ontology by identifying, organizing, and structuring the documents into an interrogative structured form. A Malay knowledge base, the MalayIK corpus is developed and used to test the MalayIK-Ontology against Ontos, an existing data extraction engine. The experimental results from MalayIKOntology have shown a significant improvement of knowledge extraction over Ontos implementation. This shows that clear knowledge organization and structuring concept is able to increase understanding, which leads to potential increase in sharable and reusable of concepts among the community.
Sentimental classification analysis of polarity multi-view textual data using...IJECEIAES
The data and information available in most community environments is complex in nature. Sentimental data resources may possibly consist of textual data collected from multiple information sources with different representations and usually handled by different analytical models. These types of data resource characteristics can form multi-view polarity textual data. However, knowledge creation from this type of sentimental textual data requires considerable analytical efforts and capabilities. In particular, data mining practices can provide exceptional results in handling textual data formats. Besides, in the case of the textual data exists as multi-view or unstructured data formats, the hybrid and integrated analysis efforts of text data mining algorithms are vital to get helpful results. The objective of this research is to enhance the knowledge discovery from sentimental multi-view textual data which can be considered as unstructured data format to classify the polarity information documents in the form of two different categories or types of useful information. A proposed framework with integrated data mining algorithms has been discussed in this paper, which is achieved through the application of X-means algorithm for clustering and HotSpot algorithm of association rules. The analysis results have shown improved accuracies of classifying the sentimental multi-view textual data into two categories through the application of the proposed framework on online polarity user-reviews dataset upon a given topics.
Natural Language Processing is a programmed approach to analyze text that is based on both a set of theories and a set of technologies. This forum aims to bring together researchers who have designed and build software that will analyze, understand, and generate languages that humans use naturally to address computers.
Design and Implementation of Meetings Document Management and Retrieval SystemCSCJournals
The document describes the design and implementation of a meetings document management and retrieval system. Key features of the system include:
1. Capturing, storing, indexing, and retrieving meeting documents such as agendas, minutes, and registration forms from a database.
2. Implementing a search facility to allow users to quickly locate topics of interest within documents.
3. Incorporating hyperlinks to enable navigation between related documents and sections.
4. Developing the system as a web application using ASP.NET to allow remote access by authorized users.
The system was designed using object-oriented principles and includes security features to protect unauthorized access to documents. It aims to improve organization and access of meeting
Dynamic & Attribute Weighted KNN for Document Classification Using Bootstrap ...IJERA Editor
This document discusses document classification using a k-nearest neighbors algorithm with dynamic attribute weighting and bootstrap sampling. It begins with an introduction to text mining and document classification. It then describes k-nearest neighbors classification and how bootstrap sampling can be used to improve k-NN by assigning different weightings to attributes. The document evaluates this approach and compares its performance to traditional k-NN classification.
Research on ontology based information retrieval techniquesKausar Mukadam
The document summarizes and compares three novel ontology-based information retrieval techniques. It discusses a technique for retrieving information in the domain of Traditional Chinese Medicine that uses an ontology to represent concepts and measures concept similarity to sort search results. It also describes a framework for semantic indexing and querying that uses an ontology and entity-attribute-value model to improve scalability, usability, and retrieval performance for transport systems. Additionally, it outlines a semantic extension retrieval model that uses ontology annotation and semantic extension of queries to address limitations of keyword-based search. The techniques are evaluated based on precision and recall measures to analyze their effectiveness compared to traditional methods.
This document describes a method for enriching search results using ontology. It begins with an abstract discussing how keyword searches often return irrelevant documents due to the large amount of information available online. It then introduces the concept of using ontology to allow for more sophisticated semantic searches. The paper presents an architecture that augments keyword search results with additional documents that are semantically relevant based on ontology mappings. Documents in the search results are then ranked based on both keyword frequency and semantic relevance to improve search accuracy.
This document provides an overview of information retrieval systems, including their definition, objectives, and key functional processes. An information retrieval system aims to minimize the time and effort users spend locating needed information by supporting search generation, presenting relevant results, and allowing iterative refinement of searches. The major functional processes involve normalizing input items, selectively disseminating new items to users, searching archived documents and user-created indexes. Information retrieval systems differ from database management systems in their handling of unstructured text-based information rather than strictly structured data.
Comparative Study on Graph-based Information Retrieval: the Case of XML DocumentIJAEMSJORNAL
The processing of massive amounts of data has become indispensable especially with the potential proliferation of big data. The volume of information available nowadays makes it difficult for the user to find relevant information in a vast collection of documents. As a result, the exploitation of vast document collections necessitates the implementation of automated technologies that enable appropriate and effective retrieval. In this paper, we will examine the state of the art of IR in XML documents. We will also discuss some works that have used graphs to represent documents in the context of IR. In the same vein, the relationships between the components of a graph are the center of our attention.
Scaling Down Dimensions and Feature Extraction in Document Repository Classif...ijdmtaiir
-In this study a comprehensive evaluation of two
supervised feature selection methods for dimensionality
reduction is performed - Latent Semantic Indexing (LSI) and
Principal Component Analysis (PCA). This is gauged against
unsupervised techniques like fuzzy feature clustering using
hard fuzzy C-means (FCM) . The main objective of the study is
to estimate the relative efficiency of two supervised techniques
against unsupervised fuzzy techniques while reducing the
feature space. It is found that clustering using FCM leads to
better accuracy in classifying documents in the face of
evolutionary algorithms like LSI and PCA. Results show that
the clustering of features improves the accuracy of document
classification
This curriculum vitae summarizes the qualifications and experience of Dr. Jie Bao. He is currently a research associate at Rensselaer Polytechnic Institute, a research affiliate at MIT, and a visiting scientist at Raytheon BBN Technologies. He received his Ph.D. in computer science from Iowa State University in 2007. His research focuses on areas including semantic web, linked data, description logics, and ontology engineering. He has over 50 publications and has served on numerous conference committees.
Named Entity Recognition Using Web Document CorpusIJMIT JOURNAL
This paper introduces a named entity recognition approach in textual corpus. This Named Entity (NE) can be a named: location, person, organization, date, time, etc., characterized by instances. A NE is found in texts accompanied by contexts: words that are left or right of the NE. The work mainly aims at identifying contexts inducing the NE’s nature. As such, The occurrence of the word "President" in a text, means that this word or context may be followed by the name of a president as President "Obama". Likewise, a word preceded by the string "footballer" induces that this is the name of a footballer. NE recognition may be viewed as a classification method, where every word is assigned to a NE class, regarding the context.
The aim of this study is then to identify and classify the contexts that are most relevant to recognize a NE, those which are frequently found with the NE. A learning approach using training corpus: web documents, constructed from learning examples is then suggested. Frequency representations and modified tf-idf representations are used to calculate the context weights associated to context frequency, learning example frequency, and document frequency in the corpus.
Named entity recognition using web document corpusIJMIT JOURNAL
This paper introduces a named entity recognition approach in textual corpus. This Named Entity (NE)
can be a named: location, person, organization, date, time, etc., characterized by instances. A NE is
found in texts accompanied by contexts: words that are left or right of the NE. The work mainly aims at identifying contexts inducing the NE’s nature. As such, The occurrence of the word "President" in a text, means that this word or context may be followed by the name of a president as President "Obama". Likewise, a word preceded by the string "footballer" induces that this is the name of a
footballer. NE recognition may be viewed as a classification method, where every word is assigned to
a NE class, regarding the context. The aim of this study is then to identify and classify the contexts that are most relevant to recognize a NE, those which are frequently found with the NE. A learning approach using training corpus: web documents, constructed from learning examples is then suggested. Frequency representations and modified tf-idf representations are used to calculate the context weights associated to context frequency, learning example frequency, and document frequency in the corpus.
The Survey of Data Mining Applications And Feature Scope IJCSEIT Journal
In this paper we have focused a variety of techniques, approaches and different areas of the research which
are helpful and marked as the important field of data mining Technologies. As we are aware that many MNC’s
and large organizations are operated in different places of the different countries. Each place of operation
may generate large volumes of data. Corporate decision makers require access from all such sources and
take strategic decisions .The data warehouse is used in the significant business value by improving the
effectiveness of managerial decision-making. In an uncertain and highly competitive business
environment, the value of strategic information systems such as these are easily recognized however in
today’s business environment, efficiency or speed is not the only key for competitiveness. This type of huge
amount of data’s are available in the form of tera- to peta-bytes which has drastically changed in the areas
of science and engineering. To analyze, manage and make a decision of such type of huge amount of data
we need techniques called the data mining which will transforming in many fields. This paper imparts more
number of applications of the data mining and also o focuses scope of the data mining which will helpful in
the further research.
Improving Annotations in Digital Documents using Document Features and Fuzzy ...IRJET Journal
The document proposes a system to automatically annotate digital documents using document features extracted via natural language processing techniques and fuzzy logic. It aims to improve on existing annotation systems by maintaining semantic accuracy while annotating large amounts of documents. The system first extracts features from documents like titles, sentence length, proper nouns etc. It then uses fuzzy logic to apply the best possible annotations based on weighted feature values. The approach is meant to accurately annotate documents in all conditions while preserving semantic meaning.
A SURVEY OF LINK MINING AND ANOMALIES DETECTIONIJDKP
This document discusses link mining and its application in detecting anomalies. It begins by defining link mining as focusing on discovering explicit links between objects, as opposed to data mining which aims to find patterns within datasets. The document then surveys different types of anomalies that can be detected through link mining, including contextual, point, collective, online, and distributed anomalies. It also discusses challenges in link mining like logical vs statistical dependencies and the skewed class distribution problem in link prediction. Applications of link mining mentioned include social networks, epidemiology, and bibliographic analysis. Overall, the document provides an overview of the emerging field of link mining and its relevance for detecting unusual or anomalous links within linked datasets.
This document proposes using Word2Vec and decision trees to extract keywords from textual documents and classify the documents. It reviews related work on keyword extraction and text classification techniques. The proposed approach involves preprocessing text, representing words as vectors with Word2Vec, calculating frequently occurring keywords for each category, and using decision trees to classify documents based on keyword similarity. Experiments using different preprocessing and Word2Vec settings achieved an F-score of up to 82% for document classification.
Experimental Investigations of Exhaust Emissions of four Stroke SI Engine by ...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
This document provides an overview of the biblical antichrist power as revealed in prophecies in the books of Daniel and Revelation. It identifies the antichrist power as the Papacy based on historical and prophetic evidence. Key points made include:
- The antichrist power arises as a "little horn" out of the Roman Empire and persecutes the saints for 1260 years.
- The number 666 is identified with the title "Vicarius Filii Dei" (Vicar of the Son of God), which is the numerical equivalent of the Pope's official title in Latin.
- The deadly wound to one of the beast's heads in Revelation 13 refers to the Papacy losing political power
The document provides an overview of the key components and objectives of an information retrieval system. It discusses how an IR system aims to minimize the time a user spends locating needed information by facilitating search generation, presenting search results in a relevant order, and processing incoming documents through normalization, indexing, and selective dissemination to users. The major measures of an IR system's effectiveness are precision and recall.
Towards From Manual to Automatic Semantic Annotation: Based on Ontology Eleme...IJwest
This document describes a proposed system for automatic semantic annotation of web documents based on ontology elements and relationships. It begins with an introduction to semantic web and annotation. The proposed system architecture matches topics in text to entities in an ontology document. It utilizes WordNet as a lexical ontology and ontology resources to extract knowledge from text and generate annotations. The main components of the system include a text analyzer, ontology parser, and knowledge extractor. The system aims to automatically generate metadata to improve information retrieval for non-technical users.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
MalayIK: An Ontological Approach to Knowledge Transformation in Malay Unstruc...IJECEIAES
The number of unstructured documents written in Malay language is enormously available on the web and intranets. However, unstructured documents cannot be queried in simple ways, hence the knowledge contained in such documents can neither be used by automatic systems nor could be understood easily and clearly by humans. This paper proposes a new approach to transform extracted knowledge in Malay unstructured document using ontology by identifying, organizing, and structuring the documents into an interrogative structured form. A Malay knowledge base, the MalayIK corpus is developed and used to test the MalayIK-Ontology against Ontos, an existing data extraction engine. The experimental results from MalayIKOntology have shown a significant improvement of knowledge extraction over Ontos implementation. This shows that clear knowledge organization and structuring concept is able to increase understanding, which leads to potential increase in sharable and reusable of concepts among the community.
Sentimental classification analysis of polarity multi-view textual data using...IJECEIAES
The data and information available in most community environments is complex in nature. Sentimental data resources may possibly consist of textual data collected from multiple information sources with different representations and usually handled by different analytical models. These types of data resource characteristics can form multi-view polarity textual data. However, knowledge creation from this type of sentimental textual data requires considerable analytical efforts and capabilities. In particular, data mining practices can provide exceptional results in handling textual data formats. Besides, in the case of the textual data exists as multi-view or unstructured data formats, the hybrid and integrated analysis efforts of text data mining algorithms are vital to get helpful results. The objective of this research is to enhance the knowledge discovery from sentimental multi-view textual data which can be considered as unstructured data format to classify the polarity information documents in the form of two different categories or types of useful information. A proposed framework with integrated data mining algorithms has been discussed in this paper, which is achieved through the application of X-means algorithm for clustering and HotSpot algorithm of association rules. The analysis results have shown improved accuracies of classifying the sentimental multi-view textual data into two categories through the application of the proposed framework on online polarity user-reviews dataset upon a given topics.
Natural Language Processing is a programmed approach to analyze text that is based on both a set of theories and a set of technologies. This forum aims to bring together researchers who have designed and build software that will analyze, understand, and generate languages that humans use naturally to address computers.
Design and Implementation of Meetings Document Management and Retrieval SystemCSCJournals
The document describes the design and implementation of a meetings document management and retrieval system. Key features of the system include:
1. Capturing, storing, indexing, and retrieving meeting documents such as agendas, minutes, and registration forms from a database.
2. Implementing a search facility to allow users to quickly locate topics of interest within documents.
3. Incorporating hyperlinks to enable navigation between related documents and sections.
4. Developing the system as a web application using ASP.NET to allow remote access by authorized users.
The system was designed using object-oriented principles and includes security features to protect unauthorized access to documents. It aims to improve organization and access of meeting
Dynamic & Attribute Weighted KNN for Document Classification Using Bootstrap ...IJERA Editor
This document discusses document classification using a k-nearest neighbors algorithm with dynamic attribute weighting and bootstrap sampling. It begins with an introduction to text mining and document classification. It then describes k-nearest neighbors classification and how bootstrap sampling can be used to improve k-NN by assigning different weightings to attributes. The document evaluates this approach and compares its performance to traditional k-NN classification.
Research on ontology based information retrieval techniquesKausar Mukadam
The document summarizes and compares three novel ontology-based information retrieval techniques. It discusses a technique for retrieving information in the domain of Traditional Chinese Medicine that uses an ontology to represent concepts and measures concept similarity to sort search results. It also describes a framework for semantic indexing and querying that uses an ontology and entity-attribute-value model to improve scalability, usability, and retrieval performance for transport systems. Additionally, it outlines a semantic extension retrieval model that uses ontology annotation and semantic extension of queries to address limitations of keyword-based search. The techniques are evaluated based on precision and recall measures to analyze their effectiveness compared to traditional methods.
This document describes a method for enriching search results using ontology. It begins with an abstract discussing how keyword searches often return irrelevant documents due to the large amount of information available online. It then introduces the concept of using ontology to allow for more sophisticated semantic searches. The paper presents an architecture that augments keyword search results with additional documents that are semantically relevant based on ontology mappings. Documents in the search results are then ranked based on both keyword frequency and semantic relevance to improve search accuracy.
This document provides an overview of information retrieval systems, including their definition, objectives, and key functional processes. An information retrieval system aims to minimize the time and effort users spend locating needed information by supporting search generation, presenting relevant results, and allowing iterative refinement of searches. The major functional processes involve normalizing input items, selectively disseminating new items to users, searching archived documents and user-created indexes. Information retrieval systems differ from database management systems in their handling of unstructured text-based information rather than strictly structured data.
Comparative Study on Graph-based Information Retrieval: the Case of XML DocumentIJAEMSJORNAL
The processing of massive amounts of data has become indispensable especially with the potential proliferation of big data. The volume of information available nowadays makes it difficult for the user to find relevant information in a vast collection of documents. As a result, the exploitation of vast document collections necessitates the implementation of automated technologies that enable appropriate and effective retrieval. In this paper, we will examine the state of the art of IR in XML documents. We will also discuss some works that have used graphs to represent documents in the context of IR. In the same vein, the relationships between the components of a graph are the center of our attention.
Scaling Down Dimensions and Feature Extraction in Document Repository Classif...ijdmtaiir
-In this study a comprehensive evaluation of two
supervised feature selection methods for dimensionality
reduction is performed - Latent Semantic Indexing (LSI) and
Principal Component Analysis (PCA). This is gauged against
unsupervised techniques like fuzzy feature clustering using
hard fuzzy C-means (FCM) . The main objective of the study is
to estimate the relative efficiency of two supervised techniques
against unsupervised fuzzy techniques while reducing the
feature space. It is found that clustering using FCM leads to
better accuracy in classifying documents in the face of
evolutionary algorithms like LSI and PCA. Results show that
the clustering of features improves the accuracy of document
classification
This curriculum vitae summarizes the qualifications and experience of Dr. Jie Bao. He is currently a research associate at Rensselaer Polytechnic Institute, a research affiliate at MIT, and a visiting scientist at Raytheon BBN Technologies. He received his Ph.D. in computer science from Iowa State University in 2007. His research focuses on areas including semantic web, linked data, description logics, and ontology engineering. He has over 50 publications and has served on numerous conference committees.
Named Entity Recognition Using Web Document CorpusIJMIT JOURNAL
This paper introduces a named entity recognition approach in textual corpus. This Named Entity (NE) can be a named: location, person, organization, date, time, etc., characterized by instances. A NE is found in texts accompanied by contexts: words that are left or right of the NE. The work mainly aims at identifying contexts inducing the NE’s nature. As such, The occurrence of the word "President" in a text, means that this word or context may be followed by the name of a president as President "Obama". Likewise, a word preceded by the string "footballer" induces that this is the name of a footballer. NE recognition may be viewed as a classification method, where every word is assigned to a NE class, regarding the context.
The aim of this study is then to identify and classify the contexts that are most relevant to recognize a NE, those which are frequently found with the NE. A learning approach using training corpus: web documents, constructed from learning examples is then suggested. Frequency representations and modified tf-idf representations are used to calculate the context weights associated to context frequency, learning example frequency, and document frequency in the corpus.
Named entity recognition using web document corpusIJMIT JOURNAL
This paper introduces a named entity recognition approach in textual corpus. This Named Entity (NE)
can be a named: location, person, organization, date, time, etc., characterized by instances. A NE is
found in texts accompanied by contexts: words that are left or right of the NE. The work mainly aims at identifying contexts inducing the NE’s nature. As such, The occurrence of the word "President" in a text, means that this word or context may be followed by the name of a president as President "Obama". Likewise, a word preceded by the string "footballer" induces that this is the name of a
footballer. NE recognition may be viewed as a classification method, where every word is assigned to
a NE class, regarding the context. The aim of this study is then to identify and classify the contexts that are most relevant to recognize a NE, those which are frequently found with the NE. A learning approach using training corpus: web documents, constructed from learning examples is then suggested. Frequency representations and modified tf-idf representations are used to calculate the context weights associated to context frequency, learning example frequency, and document frequency in the corpus.
The Survey of Data Mining Applications And Feature Scope IJCSEIT Journal
In this paper we have focused a variety of techniques, approaches and different areas of the research which
are helpful and marked as the important field of data mining Technologies. As we are aware that many MNC’s
and large organizations are operated in different places of the different countries. Each place of operation
may generate large volumes of data. Corporate decision makers require access from all such sources and
take strategic decisions .The data warehouse is used in the significant business value by improving the
effectiveness of managerial decision-making. In an uncertain and highly competitive business
environment, the value of strategic information systems such as these are easily recognized however in
today’s business environment, efficiency or speed is not the only key for competitiveness. This type of huge
amount of data’s are available in the form of tera- to peta-bytes which has drastically changed in the areas
of science and engineering. To analyze, manage and make a decision of such type of huge amount of data
we need techniques called the data mining which will transforming in many fields. This paper imparts more
number of applications of the data mining and also o focuses scope of the data mining which will helpful in
the further research.
Improving Annotations in Digital Documents using Document Features and Fuzzy ...IRJET Journal
The document proposes a system to automatically annotate digital documents using document features extracted via natural language processing techniques and fuzzy logic. It aims to improve on existing annotation systems by maintaining semantic accuracy while annotating large amounts of documents. The system first extracts features from documents like titles, sentence length, proper nouns etc. It then uses fuzzy logic to apply the best possible annotations based on weighted feature values. The approach is meant to accurately annotate documents in all conditions while preserving semantic meaning.
A SURVEY OF LINK MINING AND ANOMALIES DETECTIONIJDKP
This document discusses link mining and its application in detecting anomalies. It begins by defining link mining as focusing on discovering explicit links between objects, as opposed to data mining which aims to find patterns within datasets. The document then surveys different types of anomalies that can be detected through link mining, including contextual, point, collective, online, and distributed anomalies. It also discusses challenges in link mining like logical vs statistical dependencies and the skewed class distribution problem in link prediction. Applications of link mining mentioned include social networks, epidemiology, and bibliographic analysis. Overall, the document provides an overview of the emerging field of link mining and its relevance for detecting unusual or anomalous links within linked datasets.
This document proposes using Word2Vec and decision trees to extract keywords from textual documents and classify the documents. It reviews related work on keyword extraction and text classification techniques. The proposed approach involves preprocessing text, representing words as vectors with Word2Vec, calculating frequently occurring keywords for each category, and using decision trees to classify documents based on keyword similarity. Experiments using different preprocessing and Word2Vec settings achieved an F-score of up to 82% for document classification.
Experimental Investigations of Exhaust Emissions of four Stroke SI Engine by ...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
This document provides an overview of the biblical antichrist power as revealed in prophecies in the books of Daniel and Revelation. It identifies the antichrist power as the Papacy based on historical and prophetic evidence. Key points made include:
- The antichrist power arises as a "little horn" out of the Roman Empire and persecutes the saints for 1260 years.
- The number 666 is identified with the title "Vicarius Filii Dei" (Vicar of the Son of God), which is the numerical equivalent of the Pope's official title in Latin.
- The deadly wound to one of the beast's heads in Revelation 13 refers to the Papacy losing political power
The document defines and studies the properties of g#p-continuous maps between topological spaces. It is shown that:
1. Every pre-continuous, α-continuous, gα-continuous and continuous map is g#p-continuous.
2. The class of g#p-continuous maps properly contains and is properly contained in other classes of generalized continuous maps.
3. g#p-continuity is independent of other properties like semi-continuity and β-continuity.
4. The composition of two g#p-continuous maps need not be g#p-continuous.
This document discusses a model that studies a consolidated system of events, causes, and an n-qubit quantum register for quantum computation. The model analyzes the properties and behavior of this system using equations. It is argued that including events and causes enhances the "quantumness" of the system and brings quantum computation more in line with classical analysis. Additional variables of space-time are said to provide a framework for studying quantum space-time. The introduction discusses the notion of events having pre-existing destinies and discusses relating events to human behavior and system behavior through "problematizing" events.
The document discusses vocabulary words that are important to know for the SAT. Mastering a wide range of vocabulary words is key to doing well on the SAT, as the test includes many questions that require understanding the meanings of words in different contexts. Learning prefixes, suffixes, and roots can help students more easily determine the definitions of unfamiliar words on the SAT.
The document summarizes the implementation and performance analysis of MIMO in Digital Video Broadcasting-T2 (DVB-T2). It discusses how MIMO-OFDM was implemented to support multiple antenna transmission and reception in DVB-T2. The DVB-T2 transmitter and receiver were simulated using MATLAB. MIMO processing replaced the existing MISO processing to allow multiple transmitting and receiving antennas. The implementation aimed to reduce peak-to-average power ratio and support robustness levels for both fixed and portable devices. Simulation results showed accurate constellations and a decreasing bit error rate graph with increasing SNR.
A digital footprint can impact job applications, school admission, and people's perceptions by leaving an online record of what users post, share, join, and upload. The document advises being careful about personal information disclosed on websites, forms, and photos due to a digital footprint consisting of all internet content related to an individual posted by themselves or others.
The document provides tips for small businesses to easily create internet marketing videos. It recommends creating a simple video using an affordable flip camera, uploading it to YouTube and embedding it on a blog. This takes less than 30 minutes. The video will be viewed over time as it ranks for relevant keywords. It encourages businesses to convert written content into accessible and interactive videos.
Modified Procedure for Construction and Selection of Sampling Plans for Vari...IJMER
Linear Trend is Technique to generate the values for observerd frequency distribution and it
will give the accuracy of the smoothing obtained depends on the number of available data sets. In this
article ,an attempt was made to estimate the modified liner trend value generator for construction and
selection of sampling plans for variable inspection scheme indexed through the MAAOQ over the Liner
Trend .We compare the constructed sampling plans indexed through MAAOQ over Linear Trend with
the basic sampling plans indexed with AOQL. And also obtain the performance of the operating
characteristic curves.
This document summarizes a research paper that developed a Simulink model of a photovoltaic (PV) cell to study the effects of shading. The model accounts for the reduction in output power due to partial shading of cells. It was found that power losses increase with higher irradiation levels and greater rates of shading. The model can also examine the reverse bias characteristics of shaded solar cells in a PV module. In conclusion, the proposed Simulink model accurately models the decrease in maximum output power of a PV module from shading effects across different lighting conditions.
In this paper, we give several new fixed point theorems to extend results [3]-[4] ,and we apply
the effective modification of He’s variation iteration method to solve some nonlinear and linear equations are
proceed to examine some a class of integral-differential equations and some partial differential equation, to
illustrate the effectiveness and convenience of this method(see[7]). Finally we have also discussed Berge type
equation with exact solution
Network Forensic Investigation of HTTPS ProtocolIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
A digital footprint is a record of everything posted online about an individual, including what they post themselves, photos others post of them, and information posted by friends and family. This footprint can impact things like job applications, school admission, and what people think of an individual, both positively and negatively. To manage their footprint, people should be careful about what they post online, the websites they join, forms they fill out, who they give information to, and photos they post.
How to get over your networking fears part 2denise2228
The document discusses small business networking ideas to help business owners overcome fears of networking. It suggests providing potential clients with valuable information or help in the form of email mini-courses, PDF reports, or audio recordings on topics relevant to the client's business needs. These deliverables can help position the business as experts and be shared virally. The document also recommends implementing a 7-day email mini-course as research shows people typically need around 7 touches to take action. The next post will cover practical application of these ideas.
Dash7 is a wireless networking standard ratified in 2004 that uses low power for applications like RFID tags. It operates at 433MHz, which allows penetration through obstacles but makes efficient compact antennas difficult to design. Dash7 uses an asynchronous transmission method called BLAST that minimizes active transmission time to reduce power usage compared to standards like Zigbee. While lower frequencies have disadvantages like larger antenna size, designs like loop and helical antennas can achieve reasonable efficiency at 433MHz for applications requiring long battery life and range.
This document discusses the computational fluid dynamics (CFD) analysis of flow through a butterfly valve. It aims to determine the head loss coefficient and flow coefficient for the valve at different opening angles (30°, 60°, 75°, 90°). The CFD software ANSYS ICEM was used to model the valve geometry and ANSYS CFX was used to simulate the flow. The results found that the velocity increased with opening angle while head loss coefficient decreased. Streamlines became more uniform at higher openings. Numerical results closely matched experimental data, validating the CFD analysis method. The study provides a less expensive and time-consuming alternative to experimental testing of large butterfly valves.
Reduction of Topology Control Using Cooperative Communications in ManetsIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
A production - Inventory model with JIT setup cost incorporating inflation an...IJMER
A production inventory model with Just-In-Time (JIT) set-up cost has been developed in which inflation and time value of money are considered under an imperfect production process. The demand rate is considered to be a function of advertisement cost and selling price. Unit production cost is considered incorporating several features like energy and labour cost, raw material cost and development cost of the manufacturing system. Development cost is assumed to be a function of reliability parameter.
Considering these phenomena, an analytic expression is obtained for the total profit of the model. The model provides an analytical solution to maximize the total profit function.A numerical example is presented to illustrate the model along with graphical analysis. Sensitivity analysis has been carried out to identify the most sensitive parameters of the model.
Men tend to die younger than women for several biological and behavioral reasons. Biologically, men's bodies are less efficient at repairing cellular damage and they lack the protective effects of estrogen. Behaviorally, men are more likely to engage in risky behaviors like smoking, drinking alcohol in excess, not exercising regularly, and dangerous occupations. Addressing behavioral factors through health education and social support could help close the gender gap in life expectancy.
Rule-based Information Extraction for Airplane Crashes ReportsCSCJournals
Over the last two decades, the internet has gained a widespread use in various aspects of everyday living. The amount of generated data in both structured and unstructured forms has increased rapidly, posing a number of challenges. Unstructured data are hard to manage, assess, and analyse in view of decision making. Extracting information from these large volumes of data is time-consuming and requires complex analysis. Information extraction (IE) technology is part of a text-mining framework for extracting useful knowledge for further analysis.
Various competitions, conferences and research projects have accelerated the development phases of IE. This project presents in detail the main aspects of the information extraction field. It focused on specific domain: airplane crash reports. Set of reports were used from 1001 Crash website to perform the extraction tasks such as: crash site, crash date and time, departure, destination, etc. As such, the common structures and textual expressions are considered in designing the extraction rules.
The evaluation framework used to examine the system's performance is executed for both working and test texts. It shows that the system's performance in extracting entities and relations is more accurate than for events. Generally, the good results reflect the high quality and good design of the extraction rules. It can be concluded that the rule-based approach has proved its efficiency of delivering reliable results. However, this approach does require an intensive work and a cycle process of rules testing and modification.
Rule-based Information Extraction for Airplane Crashes ReportsCSCJournals
Over the last two decades, the internet has gained a widespread use in various aspects of everyday living. The amount of generated data in both structured and unstructured forms has increased rapidly, posing a number of challenges. Unstructured data are hard to manage, assess, and analyse in view of decision making. Extracting information from these large volumes of data is time-consuming and requires complex analysis. Information extraction (IE) technology is part of a text-mining framework for extracting useful knowledge for further analysis.
Various competitions, conferences and research projects have accelerated the development phases of IE. This project presents in detail the main aspects of the information extraction field. It focused on specific domain: airplane crash reports. Set of reports were used from 1001 Crash website to perform the extraction tasks such as: crash site, crash date and time, departure, destination, etc. As such, the common structures and textual expressions are considered in designing the extraction rules.
The evaluation framework used to examine the system's performance is executed for both working and test texts. It shows that the system's performance in extracting entities and relations is more accurate than for events. Generally, the good results reflect the high quality and good design of the extraction rules. It can be concluded that the rule-based approach has proved its efficiency of delivering reliable results. However, this approach does require an intensive work and a cycle process of rules testing and modification.
This document provides an overview of text mining and web mining. It defines data mining and describes the common data mining tasks of classification, clustering, association rule mining and sequential pattern mining. It then discusses text mining, defining it as the process of analyzing unstructured text data to extract meaningful information and structure. The document outlines the seven practice areas of text mining as search/information retrieval, document clustering, document classification, web mining, information extraction, natural language processing, and concept extraction. It provides brief descriptions of the problems addressed within each practice area.
Temporal Information Processing is a subfield of Natural Language Processing, valuable in many tasks
like Question Answering and Summarization. Temporal Information Processing is broadened, ranging
from classical theories of time and language to current computational approaches for Temporal
Information Extraction. This later trend consists on the automatic extraction of events and temporal
expressions. Such issues have attracted great attention especially with the development of annotated
corpora and annotations schemes mainly TimeBank and TimeML. In this paper, we give a survey of
Temporal Information Extraction from Natural Language texts.
An Improved Annotation Based Summary Generation For Unstructured DataMelinda Watson
This document discusses annotation-based summarization of unstructured data. It begins with an introduction to annotation and information retrieval. Current annotation processes cannot maintain modifications due to frequent document updates. The document then reviews literature on automatic text classification, applying annotations to linked open data sets, and using domain ontologies for automatic document annotation. Keywords, sentences and contexts are extracted from documents for annotation. Different annotation models are discussed. The goal is to develop an improved annotation approach for summarizing unstructured data that can handle frequent document changes.
A study on the approaches of developing a named entity recognition tooleSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
The document discusses existing text mining frameworks and proposes a new framework called RDIET. It analyzes frameworks like DiscoTEX, RAPIER, EPD and BWI and identifies their benefits and deficiencies. RDIET aims to integrate information extraction and knowledge discovery from databases to overcome individual limitations. It extracts structured data from text using IE and then applies data mining to discover relationships, improving IE recall. Challenges include selecting appropriate IE/KDD methods and validating the framework's performance.
Knowledge Graph and Similarity Based Retrieval Method for Query Answering SystemIRJET Journal
This document proposes a knowledge graph and question answering system to extract and analyze information from large volumes of unstructured data like annual reports. It discusses using natural language processing techniques like named entity recognition with spaCy and dependency parsing to extract entity-relation pairs from text and construct a knowledge graph. For question answering, it analyzes user queries with similar NLP approaches and then matches query triplets to the knowledge graph to retrieve answers, combining information retrieval and trained classifiers. The proposed system aims to provide faster understanding and analysis of complex, unstructured data for professionals.
Automatically finding domain specific key terms from a given set of research paper is a challenging task and research papers to a particular area of research is a concern for many people including students, professors and researchers. A domain classification of papers facilitates that search process. That is, having a list of domains in a research field, we try to find out to which domain(s) a given paper is more related. Besides, processing the whole paper to read take a long time. In this paper, using domain knowledge requires much human effort, e.g., manually composing a set of labeling a large corpus. In particular, we use the abstract and keyword in research paper as the seeing terms to identify similar terms from a domain corpus which are then filtered by checking their appearance in the research papers. Experiments show the TF –IDF measure and the classification step make this method more precisely to domains. The results show that our approach can extract the terms effectively, while being domain independent.
The document discusses mining frequent patterns from object-relational data. It begins with an introduction to data mining and frequent pattern mining. It then reviews related work on data models, including relational, object-oriented, and object-relational data models. Several frequent pattern mining algorithms are described, including Apriori, FP-Growth, ECLAT and RElim. Two approaches for mining object-relational data are proposed: a fundamental approach that treats it similarly to transactional data, and a nested-relations approach to handle nested attributes. The document concludes by outlining parameters for applying frequent pattern mining algorithms to object-relational data.
CANDIDATE SET KEY DOCUMENT RETRIEVAL SYSTEMIRJET Journal
This document describes a proposed candidate set key document retrieval system. The system would process user queries in English and return relevant documents from a collection. It would use natural language processing techniques like tokenization, stop word removal, stemming, and lemmatization to index the documents and match them with user queries. The proposed system architecture includes components for indexing, processing user queries, and retrieving relevant documents from the collection. The indexing process involves organizing the documents, extracting tokens, removing stop words, and applying stemming/lemmatization to create an inverted index for efficient searching.
This document summarizes an article about adaptive information extraction. It discusses how information extraction research has grown with the increasing availability of online text sources. However, one drawback of information extraction is its domain dependence. To address this, machine learning techniques have been used to develop adaptive information extraction systems that can be applied to new domains with less manual adaptation. The document provides an overview of information extraction and different machine learning approaches used for adaptive information extraction.
This document discusses parsing HTML documents to extract data from websites. It proposes an automated system to parse HTML pages from the SEC website and extract specific data fields, like company financial information, to insert into databases of financial companies. The system will use Java parser libraries to identify patterns in SEC forms, including data in plain text and tables. It analyzes sample SEC forms to understand the structure and focus on extracting data from table sections.
Extraction and Retrieval of Web based Content in Web EngineeringIRJET Journal
The document discusses a proposed architecture for parallelizing natural language processing (NLP) operations and web content crawling using Apache Hadoop and MapReduce. The system extracts keywords and key phrases from online articles using NLP techniques like part-of-speech tagging in a Hadoop cluster. Evaluation of the system showed improved storage capacity, faster data processing, shorter search times and accurate information retrieval from large datasets stored in HBase.
Data Mining System and Applications: A Reviewijdpsjournal
In the Information Technology era information plays vital role in every sphere of the human life. It is very important to gather data from different data sources, store and maintain the data, generate information, generate knowledge and disseminate data, information and knowledge to every stakeholder. Due to vast use of computers and electronics devices and tremendous growth in computing power and storage capacity, there is explosive growth in data collection. The storing of the data in data warehouse enables entire enterprise to access a reliable current database. To analyze this vast amount of data and drawing fruitful conclusions and inferences it needs the special tools called data mining tools. This paper gives overview of the data mining systems and some of its applications.
IRJET- Concept Extraction from Ambiguous Text Document using K-MeansIRJET Journal
This document discusses using a K-means clustering algorithm to extract concepts from ambiguous text documents. It involves preprocessing the text by tokenizing, removing stop words, and stemming words. The words are then represented as vectors and dimensionality reduction using PCA is applied. Finally, K-means clustering is used to group similar words into clusters to identify the overall concepts in the document without reading the entire text. The aim is to help users understand the key topics in a document in a time-efficient manner without having to read the full text.
Rule-based Information Extraction from Disease Outbreak ReportsWaqas Tariq
Information extraction (IE) systems serve as the front end and core stage in different natural language programming tasks. As IE has proved its efficiency in domain-specific tasks, this project focused on one domain: disease outbreak reports. Several reports from the World Health Organization were carefully examined to formulate the extraction tasks: named-entities, such as disease name, date and location; the location of the reporting authority; and the outbreak incident. Extraction rules were then designed, based on a study of the textual expressions and elements found in the text that appeared before and after the target text.
The experiment resulted in very high performance scores for all the tasks in general. The training corpora and the testing corpora were tested separately. The system performed with higher accuracy with entities and events extraction than with relationship extraction.
It can be concluded that the rule-based approach has been proven capable of delivering reliable IE, with extremely high accuracy and coverage results. However, this approach requires an extensive, time-consuming, manual study of word classes and phrases.
1. The document proposes techniques to improve search performance by matching schemas between structured and unstructured data sources.
2. It involves constructing schema mappings using named entities and schema structures. It also uses strategies to narrow the search space to relevant documents.
3. The techniques were shown to improve search accuracy and reduce time/space complexity compared to existing methods.
The huge volume of text documents available on the internet has made it difficult to find valuable
information for specific users. In fact, the need for efficient applications to extract interested knowledge
from textual documents is vitally important. This paper addresses the problem of responding to user
queries by fetching the most relevant documents from a clustered set of documents. For this purpose, a
cluster-based information retrieval framework was proposed in this paper, in order to design and develop
a system for analysing and extracting useful patterns from text documents. In this approach, a pre-
processing step is first performed to find frequent and high-utility patterns in the data set. Then a Vector
Space Model (VSM) is performed to represent the dataset. The system was implemented through two main
phases. In phase 1, the clustering analysis process is designed and implemented to group documents into
several clusters, while in phase 2, an information retrieval process was implemented to rank clusters
according to the user queries in order to retrieve the relevant documents from specific clusters deemed
relevant to the query. Then the results are evaluated according to evaluation criteria. Recall and Precision
(P@5, P@10) of the retrieved results. P@5 was 0.660 and P@10 was 0.655.
INFORMATION RETRIEVAL BASED ON CLUSTER ANALYSIS APPROACHijcsit
The huge volume of text documents available on the internet has made it difficult to find valuable
information for specific users. In fact, the need for efficient applications to extract interested knowledge
from textual documents is vitally important. This paper addresses the problem of responding to user
queries by fetching the most relevant documents from a clustered set of documents. For this purpose, a
cluster-based information retrieval framework was proposed in this paper, in order to design and develop
a system for analysing and extracting useful patterns from text documents. In this approach, a preprocessing step is first performed to find frequent and high-utility patterns in the data set. Then a Vector
Space Model (VSM) is performed to represent the dataset. The system was implemented through two main
phases. In phase 1, the clustering analysis process is designed and implemented to group documents into
several clusters, while in phase 2, an information retrieval process was implemented to rank clusters
according to the user queries in order to retrieve the relevant documents from specific clusters deemed
relevant to the query. Then the results are evaluated according to evaluation criteria. Recall and Precision
(P@5, P@10) of the retrieved results. P@5 was 0.660 and P@10 was 0.655.
Similar to Data and Information Integration: Information Extraction (20)
A Study on Translucent Concrete Product and Its Properties by Using Optical F...IJMER
- Translucent concrete is a concrete based material with light-transferring properties,
obtained due to embedded light optical elements like Optical fibers used in concrete. Light is conducted
through the concrete from one end to the other. This results into a certain light pattern on the other
surface, depending on the fiber structure. Optical fibers transmit light so effectively that there is
virtually no loss of light conducted through the fibers. This paper deals with the modeling of such
translucent or transparent concrete blocks and panel and their usage and also the advantages it brings
in the field. The main purpose is to use sunlight as a light source to reduce the power consumption of
illumination and to use the optical fiber to sense the stress of structures and also use this concrete as an
architectural purpose of the building
Developing Cost Effective Automation for Cotton Seed DelintingIJMER
A low cost automation system for removal of lint from cottonseed is to be designed and
developed. The setup consists of stainless steel drum with stirrer in which cottonseeds having lint is mixed
with concentrated sulphuric acid. So lint will get burn. This lint free cottonseed treated with lime water to
neutralize acidic nature. After water washing this cottonseeds are used for agriculter purpose
Study & Testing Of Bio-Composite Material Based On Munja FibreIJMER
The incorporation of natural fibres such as munja fiber composites has gained
increasing applications both in many areas of Engineering and Technology. The aim of this study is to
evaluate mechanical properties such as flexural and tensile properties of reinforced epoxy composites.
This is mainly due to their applicable benefits as they are light weight and offer low cost compared to
synthetic fibre composites. Munja fibres recently have been a substitute material in many weight-critical
applications in areas such as aerospace, automotive and other high demanding industrial sectors. In
this study, natural munja fibre composites and munja/fibreglass hybrid composites were fabricated by a
combination of hand lay-up and cold-press methods. A new variety in munja fibre is the present work
the main aim of the work is to extract the neat fibre and is characterized for its flexural characteristics.
The composites are fabricated by reinforcing untreated and treated fibre and are tested for their
mechanical, properties strictly as per ASTM procedures.
Hybrid Engine (Stirling Engine + IC Engine + Electric Motor)IJMER
Hybrid engine is a combination of Stirling engine, IC engine and Electric motor. All these 3 are
connected together to a single shaft. The power source of the Stirling engine will be a Solar Panel. The aim of
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Fabrication & Characterization of Bio Composite Materials Based On Sunnhemp F...IJMER
This document summarizes research on the fabrication and characterization of bio-composite materials using sunnhemp fibre. The document discusses how sunnhemp fibre was used to reinforce an epoxy matrix through hand lay-up methods. Various mechanical properties of the bio-composites were tested, including tensile, flexural, and impact properties. The results of the mechanical tests on the bio-composite specimens are presented. Potential applications of the sunnhemp fibre bio-composites are also suggested, such as in fall ceilings, partitions, packaging, automotive interiors, and toys.
Geochemistry and Genesis of Kammatturu Iron Ores of Devagiri Formation, Sandu...IJMER
The Greenstone belts of Karnataka are enriched in BIFs in Dharwar craton, where Iron
formations are confined to the basin shelf, clearly separated from the deeper-water iron formation that
accumulated at the basin margin and flanking the marine basin. Geochemical data procured in terms of
major, trace and REE are plotted in various diagrams to interpret the genesis of BIFs. Al2O3, Fe2O3 (T),
TiO2, CaO, and SiO2 abundances and ratios show a wide variation. Ni, Co, Zr, Sc, V, Rb, Sr, U, Th,
ΣREE, La, Ce and Eu anomalies and their binary relationships indicate that wherever the terrigenous
component has increased, the concentration of elements of felsic such as Zr and Hf has gone up. Elevated
concentrations of Ni, Co and Sc are contributed by chlorite and other components characteristic of basic
volcanic debris. The data suggest that these formations were generated by chemical and clastic
sedimentary processes on a shallow shelf. During transgression, chemical precipitation took place at the
sediment-water interface, whereas at the time of regression. Iron ore formed with sedimentary structures
and textures in Kammatturu area, in a setting where the water column was oxygenated.
Experimental Investigation on Characteristic Study of the Carbon Steel C45 in...IJMER
In this paper, the mechanical characteristics of C45 medium carbon steel are investigated
under various working conditions. The main characteristic to be studied on this paper is impact toughness
of the material with different configurations and the experiment were carried out on charpy impact testing
equipment. This study reveals the ability of the material to absorb energy up to failure for various
specimen configurations under different heat treated conditions and the corresponding results were
compared with the analysis outcome
Non linear analysis of Robot Gun Support Structure using Equivalent Dynamic A...IJMER
Robot guns are being increasingly employed in automotive manufacturing to replace
risky jobs and also to increase productivity. Using a single robot for a single operation proves to be
expensive. Hence for cost optimization, multiple guns are mounted on a single robot and multiple
operations are performed. Robot Gun structure is an efficient way in which multiple welds can be done
simultaneously. However mounting several weld guns on a single structure induces a variety of
dynamic loads, especially during movement of the robot arm as it maneuvers to reach the weld
locations. The primary idea employed in this paper, is to model those dynamic loads as equivalent G
force loads in FEA. This approach will be on the conservative side, and will be saving time and
subsequently cost efficient. The approach of the paper is towards creating a standard operating
procedure when it comes to analysis of such structures, with emphasis on deploying various technical
aspects of FEA such as Non Linear Geometry, Multipoint Constraint Contact Algorithm, Multizone
meshing .
Static Analysis of Go-Kart Chassis by Analytical and Solid Works SimulationIJMER
This paper aims to do modelling, simulation and performing the static analysis of a go
kart chassis consisting of Circular beams. Modelling, simulations and analysis are performed using 3-D
modelling software i.e. Solid Works and ANSYS according to the rulebook provided by Indian Society of
New Era Engineers (ISNEE) for National Go Kart Championship (NGKC-14).The maximum deflection is
determined by performing static analysis. Computed results are then compared to analytical calculation,
where it is found that the location of maximum deflection agrees well with theoretical approximation but
varies on magnitude aspect.
In récent year various vehicle introduced in market but due to limitation in
carbon émission and BS Séries limitd speed availability vehicle in the market and causing of
environnent pollution over few year There is need to decrease dependancy on fuel vehicle.
bicycle is to be modified for optional in the future To implement new technique using change in
pedal assembly and variable speed gearbox such as planetary gear optimise speed of vehicle
with variable speed ratio.To increase the efficiency of bicycle for confortable drive and to
reduce torque appli éd on bicycle. we introduced epicyclic gear box in which transmission done
throgh Chain Drive (i.e. Sprocket )to rear wheel with help of Epicyclical gear Box to give
number of différent Speed during driving.To reduce torque requirent in the cycle with change in
the pedal mechanism
Integration of Struts & Spring & Hibernate for Enterprise ApplicationsIJMER
This document discusses integrating the Spring, Struts, and Hibernate frameworks to develop enterprise applications. It provides an overview of each framework and their features. The Spring Framework is a lightweight, modular framework that allows for inversion of control and aspect-oriented programming. It can be used to develop any or all tiers of an application. The document proposes an architecture for an e-commerce website that integrates these three frameworks, with Spring handling the business layer, Struts the presentation layer, and Hibernate the data access layer. This modular approach allows for clear separation of concerns and reduces complexity in application development.
Microcontroller Based Automatic Sprinkler Irrigation SystemIJMER
Microcontroller based Automatic Sprinkler System is a new concept of using
intelligence power of embedded technology in the sprinkler irrigation work. Designed system replaces
the conventional manual work involved in sprinkler irrigation to automatic process. Using this system a
farmer is protected against adverse inhuman weather conditions, tedious work of changing over of
sprinkler water pipe lines & risk of accident due to high pressure in the water pipe line. Overall
sprinkler irrigation work is transformed in to a comfortableautomatic work. This system provides
flexibility & accuracy in respect of time set for the operation of a sprinkler water pipe lines. In present
work the author has designed and developed an automatic sprinkler irrigation system which is
controlled and monitored by a microcontroller interfaced with solenoid valves.
On some locally closed sets and spaces in Ideal Topological SpacesIJMER
This document introduces and studies the concept of δˆ s-locally closed sets in ideal topological spaces. Some key points:
- A subset A is δˆ s-locally closed if A can be written as the intersection of a δˆ s-open set and a δˆ s-closed set.
- Various properties of δˆ s-locally closed sets are introduced and characterized, including relationships to other concepts like generalized locally closed sets.
- It is shown that a subset A is δˆ s-locally closed if and only if A can be written as the intersection of a δˆ s-open set and the δˆ s-closure of A.
- Theore
Intrusion Detection and Forensics based on decision tree and Association rule...IJMER
This paper present an approach based on the combination of, two techniques using
decision tree and Association rule mining for Probe attack detection. This approach proves to be
better than the traditional approach of generating rules for fuzzy expert system by clustering methods.
Association rule mining for selecting the best attributes together and decision tree for identifying the
best parameters together to create the rules for fuzzy expert system. After that rules for fuzzy expert
system are generated using association rule mining and decision trees. Decision trees is generated for
dataset and to find the basic parameters for creating the membership functions of fuzzy inference
system. Membership functions are generated for the probe attack. Based on these rules we have
created the fuzzy inference system that is used as an input to neuro-fuzzy system. Fuzzy inference
system is loaded to neuro-fuzzy toolbox as an input and the final ANFIS structure is generated for
outcome of neuro-fuzzy approach. The experiments and evaluations of the proposed method were
done with NSL-KDD intrusion detection dataset. As the experimental results, the proposed approach
based on the combination of, two techniques using decision tree and Association rule mining
efficiently detected probe attacks. Experimental results shows better results for detecting intrusions as
compared to others existing methods
Natural Language Ambiguity and its Effect on Machine LearningIJMER
This document discusses natural language ambiguity and its effect on machine learning. It begins by introducing different types of ambiguity that exist in natural languages, including lexical, syntactic, semantic, discourse, and pragmatic ambiguities. It then examines how these ambiguities present challenges for computational linguistics and machine translation systems. Specifically, it notes that ambiguity is a major problem for computers in processing human language as they lack the world knowledge and context that humans use to resolve ambiguities. The document concludes by outlining the typical process of machine translation and how ambiguities can interfere with tasks like analysis, transfer, and generation of text in the target language.
Today in era of software industry there is no perfect software framework available for
analysis and software development. Currently there are enormous number of software development
process exists which can be implemented to stabilize the process of developing a software system. But no
perfect system is recognized till yet which can help software developers for opting of best software
development process. This paper present the framework of skillful system combined with Likert scale. With
the help of Likert scale we define a rule based model and delegate some mass score to every process and
develop one tool name as MuxSet which will help the software developers to select an appropriate
development process that may enhance the probability of system success.
Material Parameter and Effect of Thermal Load on Functionally Graded CylindersIJMER
The present study investigates the creep in a thick-walled composite cylinders made
up of aluminum/aluminum alloy matrix and reinforced with silicon carbide particles. The distribution
of SiCp is assumed to be either uniform or decreasing linearly from the inner to the outer radius of
the cylinder. The creep behavior of the cylinder has been described by threshold stress based creep
law with a stress exponent of 5. The composite cylinders are subjected to internal pressure which is
applied gradually and steady state condition of stress is assumed. The creep parameters required to
be used in creep law, are extracted by conducting regression analysis on the available experimental
results. The mathematical models have been developed to describe steady state creep in the composite
cylinder by using von-Mises criterion. Regression analysis is used to obtain the creep parameters
required in the study. The basic equilibrium equation of the cylinder and other constitutive equations
have been solved to obtain creep stresses in the cylinder. The effect of varying particle size, particle
content and temperature on the stresses in the composite cylinder has been analyzed. The study
revealed that the stress distributions in the cylinder do not vary significantly for various combinations
of particle size, particle content and operating temperature except for slight variation observed for
varying particle content. Functionally Graded Materials (FGMs) emerged and led to the development
of superior heat resistant materials.
Energy Audit is the systematic process for finding out the energy conservation
opportunities in industrial processes. The project carried out studies on various energy conservation
measures application in areas like lighting, motors, compressors, transformer, ventilation system etc.
In this investigation, studied the technical aspects of the various measures along with its cost benefit
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Investigation found that major areas of energy conservation are-
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3. Use of wind ventilators for ventilation.
4. Use of VFD for compressor.
5. Transparent roofing sheets to reduce energy consumption.
So Energy Audit is the only perfect & analyzed way of meeting the Industrial Energy Conservation.
An Implementation of I2C Slave Interface using Verilog HDLIJMER
This document describes the implementation of an I2C slave interface using Verilog HDL. It introduces the I2C protocol which uses only two bidirectional lines (SDA and SCL) for communication. The document discusses the I2C protocol specifications including start/stop conditions, addressing, read/write operations, and acknowledgements. It then provides details on designing an I2C slave module in Verilog that responds to commands from an I2C master and allows synchronization through clock stretching. The module is simulated in ModelSim and synthesized in Xilinx. Simulation waveforms demonstrate successful read and write operations to the slave device.
Discrete Model of Two Predators competing for One PreyIJMER
This paper investigates the dynamical behavior of a discrete model of one prey two
predator systems. The equilibrium points and their stability are analyzed. Time series plots are obtained
for different sets of parameter values. Also bifurcation diagrams are plotted to show dynamical behavior
of the system in selected range of growth parameter
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
Discover the latest insights on Data Driven Maintenance with our comprehensive webinar presentation. Learn about traditional maintenance challenges, the right approach to utilizing data, and the benefits of adopting a Data Driven Maintenance strategy. Explore real-world examples, industry best practices, and innovative solutions like FMECA and the D3M model. This presentation, led by expert Jules Oudmans, is essential for asset owners looking to optimize their maintenance processes and leverage digital technologies for improved efficiency and performance. Download now to stay ahead in the evolving maintenance landscape.
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
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- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
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- Attach least privilege policy to IAM user.
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- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
Data and Information Integration: Information Extraction
1. International
OPEN ACCESS Journal
Of Modern Engineering Research (IJMER)
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss. 2 | Feb 2014 | 55 |
Data and Information Integration: Information Extraction
Varnica Verma1
1
(Department of Computer Science Engineering, Guru Nanak Dev University, Gurdaspur Campus, Punjab,
India)
I. Introduction
Information Extraction (IE) is used to identify a predefined set of concepts in a specific domain,
ignoring other irrelevant information, where a domain consists of a corpus of texts together with a clearly
specified information need. In other words, IE is about deriving structured factual information from unstructured
text. For instance, consider as an example the extraction of information on violent events from online news,
where one is interested in identifying the main actors of the event, its location and number of people affected.
Information extraction identifies class of pre-specified entities and relationships and their relevant properties.
The main aim of information extraction is to represent the data in the database in structured view i.e., in a
machine understandable form [6].
II. Literature Survey
According to Jakub Piskorski and Roman Yangarber [1], information extraction is an area of natural
language processing that deals with finding information from free text. Sunita Sarawagi [2] studies the different
techniques used for information extraction, the different input resources used and the type of output produced.
She says that information extraction can be studied in diverse communities. Devika K and Subu Surendran [3]
provide different tools for web data extraction. Jie Tang [5] details on the challenges in the field of information
extraction.
2.1 Early Years: Knowledge Extraction Systems
In the early years, information extraction systems were developed using the knowledge engineering
approaches where the creation of knowledge in the form of rules and patterns, for detecting and extracting the
required information from the database, was done by human experts. Most of the early IE systems had a
drawback that they showed a black-box character, which were not easily adaptable to the new scenarios. The aim
of knowledge based systems is put efforts for general purpose information extraction systems and frameworks
which are easier to adapt and learn by the new domains and languages [1]. Modularized approach was used for
the development of such systems. Two examples of modular approach used are IE2 and REES. The
ABSTRACT: Information extraction is generally concerned with the location of different items in any
document, may be textual or web document. This paper is concerned with the methodologies and
applications of information extraction. The field of information extraction plays a very important role in
the natural language processing community. The architecture of information extraction system which acts
as the base for all languages and fields is also discussed along with its different components. Information
is hidden in the large volume of web pages and thus it is necessary to extract useful information from the
web content, called Information Extraction. In information extraction, given a sequence of instances, we
identify and pull out a sub-sequence of the input that represents information we are interested in.
Manual data extraction from semi supervised web pages is a difficult task. This paper focuses on study of
various data extraction techniques and also some web data extraction techniques. In the past years, there
was a rapid expansion of activities in the information extraction area. Many methods have been proposed
for automating the process of extraction. We will survey various web data extraction tools. Several real-
world applications of information extraction will be introduced. What role information extraction plays in
different fields is discussed in these applications. Current challenges being faced by the available
information extraction techniques are briefly discussed along with the future work going on using the
current researches is discussed.
Keywords: DELA, HTML, IE, NLP, REES.
2. Data and Information Integration: Information Extraction
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss. 2 | Feb 2014 | 56 |
first one achieved the highest scores for all IE tasks and the second had been the first attempt for large scale
events and relation extraction systems based on shallow text analysis methods.
2.2 Architecture: Components of Information Extraction System
Different IE systems are developed for performing different tasks but some components always remain
the same. These components typically include core linguistic components-which are useful to perform NLP
(natural language processing) tasks in general- and IE specific components which address the IE specific tasks.
Also, domain-independent and domain specific components are also included [1].
The following steps are followed in order to extract information:-
2.2.1 Domain Independent Components
Meta-Data Analysis: - Extracts the title, body, structure of the body and the date of the document i.e.,
the date when the document was created [1].
Tokenization: - Text is segmented into different parts called tokens which constitute words with capital
letters, punctuation marks, numbers used in the whole text etc. All the tokens are provided with
different headings and the relevant data from the text is added to the respective tokens [1].
Morphological Analysis: - In this step the information is extracted from the tokens [1].
Sentence or Utterance Boundary Detection: - This performs the formation of sequence of sentences
from the text, along with different items associated with it and their different features [1].
Common Named-Entity Extraction: - Extraction of domain-independent entities is performed. These
entities are represented with common names like number, currency, geographical references etc [1].
Phrase Recognition: - Recognition of verbs, nouns, abbreviations, prepositional phrases etc. is
performed in this step [1].
Syntactic Analysis:-Structure for sentences is designed based on the sequence of different items being
used in the sentence. The structure can be of two types: one is deep i.e. includes each and every detail
of the items being consumed and second is shallow i.e. includes only the specific items and not their
further properties or attributes. The structure can be like parse trees. The shallow structure fails to
represent ambiguities (if any) [1].
2.2.2 Domain Specific Components
The core IE tasks are domain specific and are therefore implemented by domain specific components.
Domain specific tasks can also be performed at lower level of database extraction. The following steps are
applied:-
Specific Named-Entity Recognition: - The text is extracted using some specifically highlighted terms
from the text. For example, in domains related to medicine some specialized terms related to medicine are
required whereas in case of a large enterprise there is no such requirement [1].
Pattern Matching: - The entities and their key attributes are extracted. These must be relevant to the target
relation or event. All the properties of each and every entity are detected from the text. The entities
constitute different patterns according to the properties inherited by them [1].
Co-Reference Resolution: - Implementation of inference rules is done in this step in order to create fully
fledged relations or events [1].
Information Fusion: - The entities with same attributes are combined to constitute one entity set. The
related information is generally grouped together in different sentences and documents. All this data is
collected and grouped together in the pattern of their properties so that a proper relation can be made [1].
3. Data and Information Integration: Information Extraction
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss. 2 | Feb 2014 | 57 |
DATA-INDEPENDENT LINGUISTIC ANALYSIS
DOMAIN-SPECIFIC CORE IE COMPONENTS
Figure: 1. Architecture of information extraction system
2.3 Knowledge Extraction Techniques
2.3.1 Rule Based Technique
The detection and extraction of information and data is performed by using some knowledge based
rules. Human expertise plays an important role in this method [5].
Advantages:
Fast
Simple
Easy to understand
Easily implementable
Can be implemented on different data standards [4].
Disadvantages:
Ambiguity cannot be resolved
Cannot deal with facts
Mono-lingual technique
INPUT
TEXT
META-DATA ANALYSIS
TOKENIZATION
MORPHOLOGICAL ANALYSIS
SENTENCE BOUNDARY DETECTION
COMMON NAMED ENTITY DETECTION
PHRASE RECOGNITION
SYNTACTIC ANALYSIS
SPECIFIC NAMED-ENTITY RECOGNITION
PATTERN MATCHING
CO-REFERENCE RESOLUTION
INFORMATION FUSION
EXTRACTED FACTS
INFERENCE
RULES
4. Data and Information Integration: Information Extraction
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss. 2 | Feb 2014 | 58 |
Not easily adaptable on different platforms [4].
2.3.2 Pattern Learning Technique
This technique involves writing and editing patterns which requires a lot of skill. It also consumes a
considerable amount of time. These patterns are not easily adaptable to new platforms used for different
databases [4].
2.3.3 Supervised Learning Technique
This is pipeline style information extraction technique. In this method the task is split into different
components and data annotation is prepared for these components. Several machine learning methods are used to
address these components separately. Name tagging and relation extraction are some of the progress made using
this field [4].
2.4 Web Data Extraction
Internet is a very powerful source of information. A lot many business applications depend on the
internet for collecting information which plays a very crucial role in the decision making process. Using web
data extraction we can analyze the current market trends, product details, price details etc. [7].
Web page generation is the process of combining data into a particular format. Web data extraction is the reverse
process of web page generation. If multiple pages are given as input then the extraction target will be the page
wide information and in case of a single page the extraction target will be record level information. Manual data
extraction is time consuming and error prone [3].
Figure: 2 web data extraction
2.4.1 WEB DATA EXTRACTION TOOLS
1) DELA (Data Extraction And Label Assignment For Web Databases)
DELA automatically extracts data from web site and assigns meaningful labels to data. This technique
concentrates on pages that querying back end database using complex search forms other than using keywords
[3].
DELA comprises of four basic components:-
a. A form crawler
b. Wrapper generator
c. Data aligner
d. Label assigner
FORM CRAWLER
It collects labels of the website form elements. Most form elements contain text that helps users to
understand the characteristics and semantics of the element. So, form elements are labeled by the descriptive
text. These labels are compared with the attributes of the data extracted from the query-result page [3].
WRAPPER GENERATOR
Pages gathered by the form crawler are given as input to the wrapper generator. Wrapper generator
produces regular expression wrapper based on HTML tag structures of the page. If a page contains more than
one instance of data objects then tags enclosing data objects may appear repeatedly. Wrapper generator
considers each page as a sequence of tokens composed of HTML tags. Special token “text” is used to represent
text string enclosed with in HTML tag pairs. Wrapper generator then extracts repeated HTML tag substring and
introduces a regular expression wrapper according to some hierarchical relationship between them [3].
THE WEB
EXTRACTINGDATA.COM
THE DATA YOU NEED
5. Data and Information Integration: Information Extraction
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss. 2 | Feb 2014 | 59 |
DATA ALIGNER
Data aligner has two phases. They are data extraction and attribute separation [3].
DATA EXTRACTION
This phase extracts data from web pages according to the wrapper produced by wrapper generator.
Then it will load extracted data into a table. In data extraction phase we have regular expression pattern and
token sequence that representing web page. A nondeterministic finite automation is constructed to match the
occurrence of token sequences representing web pages. A data-tree will be constructed for each regular
expression.
ATTRIBUTE SEPARATION
Before attribute separation it is needed to remove all HTML tags. If several attributes are encoded in to
one text string then they should be separated by special symbol(s) as separator. For instances "@", "$", "." are
not valid separator. When several separators are found to be valid for one column, the attributes strings of this
column are separated from beginning to end in the order of occurrence portion of each separator.
Figure: 3 DELA (Data extraction and label assignment for web data extraction)
2) FIFA TECH
Fifa Tech is a page level web data extraction technique. It comprises of two data modules through
which data extraction is performed [3].
First module takes DOM trees of web pages as input and merges all DOM trees into a structure called
fixed/variant pattern tree.
In the second module template and schema are detected from fixed/variant pattern tree.
Peer node recognition: Peer nodes are identified and they are assigned same symbol.
Matrix alignment: This step aligns peer matrix to produce a list of aligned nodes. Matrix alignment
recognizes leaf nodes which represent data item.
Optional node merging: This step recognizes optional nodes, the nodes which are which disappears in
some column of the matrix.
Schema detection: This module detects structure of the website i.e., identifying the schema and defining
the template.
6. Data and Information Integration: Information Extraction
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss. 2 | Feb 2014 | 60 |
Figure: 4 Fifa tech for web data extraction
3) IEPAD
It is an information extraction system which applying pattern discovery techniques. It has three
components, an extraction rule generator, pattern viewer and an extract module [3].
Extraction rule generator accepts input web page and generate extraction rules. It includes a token
translator, PAT tree constructor, pattern discoverer, a pattern validator and an extraction rule composer
as shown in Fig.
Pattern viewer is a graphical user interface which shows the repetitive pattern discovered.
Extractor module extracts desired information from pages. [3]Translator generates tokens from input
webpage. Each token is represented by a binary code of fixed length l.PAT tree constructor receives the
binary file to construct a PAT tree. PAT tree is a PATRICIA tree (Practical Algorithm to Retrieve
Information Coded in Alphanumeric). PAT tree is used for pattern discovery. Discoverer uses PAT tree
to discover repetitive patterns called maximal repeats. Validator filters out undesired patterns from
maximal repeats and generates candidate patterns.
HTML PAGE
EXTRACTION RULES
Figure: 5 IEPAD for web data extraction
III. Applications Of Information Extraction
Information extraction is used in different areas like business enterprises, personal applications,
scientific applications etc. Information extraction plays a very important role in each and every field we work in.
Various applications are listed as:-
INPUT WEB PAGES
DOM TREES
TREE MERGING
SCHEMA DETECTION
SCHEMA AND
TEMPLATE DATA
7. Data and Information Integration: Information Extraction
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss. 2 | Feb 2014 | 61 |
3.1 Enterprise Applications
News Tracking
Information extraction plays a very important role in extracting information from different sources.
There are two recent applications of information extraction on news articles: it integrates the data from
videos and pictures of different events and entities of news articles and gathers background information
on people, locations and companies [2].
Customer Care
A customer oriented enterprise requires to integrate itself with the customer requirements provided by
them through mails and other means. This can be done by integrating customer interaction with the
enterprise’s own structured databases and business’s ontologies [2].
Data Cleaning
Duplicacy of data needs to be removed from the databases. Data warehouse cleaning process is used to
clean the information by keeping the similar data in same format at one place so that no redundancy
arises. By dividing an entity into its properties it becomes easy to do the deduplication [2].
3.2 Personal Information Management
Personal information management systems aims to integrate the information provided in the form of e-mails,
documents, projects and people in a structured format which links them with each other. Such systems are
successful only if they are able to extract data from the predefined unstructured domains [2].
3.3 Scientific Applications
The rise in the field of bio-informatics has lead to the development of data extraction from terms like proteins
and genes. Earlier it was not possible to extract the data from such biological terms but with the success in the
field of information extraction and advancement in the techniques of data extraction it has become possible to
extract data from various scientific entities and not stay limited only to the classical terms like people and
companies [2].
3.4 Web Oriented Applications
Citation Databases
Many citation databases require different structure extraction steps for its creation. These are navigating
websites for locating pages containing publication records, extracting individual publication records as
per requirement of the database, extracting title, authors and references and segmenting all of them
resulting in a structured database [2].
Opinion Databases
There is a lot of data available on the web related to any topic but in rough format. By using different
structured techniques this data can be organized and all the reviews which lie behind the blogs, review
sites, newspaper reports etc. can be extracted [2].
Community Websites
These are the websites which are created using data about researchers, conferences, projects and events
which are related to a particular community. These structured databases require these steps for it’s
creation: locating the talks of the departments, finding the title of the conference, collecting the names
of the speakers and so on [2].
Comparison Shopping
Different websites are created listing the information of their products and their price details. Such
websites are used when looking for any product and its data is extracted from these collectively in order
to form a structured database [2].
IV. Challenges and Future
Traditionally the task of information extraction was carried out in only one language i.e., English. But
with the growing textual data available in other languages there had become a need to extract data in all
these languages [1].
Designing information extraction techniques in different languages creates a difficulty in implementation.
Hence, in order to remove this difficulty such techniques are designed which work for all languages [1].
The different protocols to be used for information extraction are designed and formulated in such a way
that all the textual data from different languages can be extracted easily [1].
Thus, it is harder to implement information extraction using different languages and also the performance
of non-English information extraction techniques is also lower [1].
8. Data and Information Integration: Information Extraction
| IJMER | ISSN: 2249–6645 | www.ijmer.com | Vol. 4 | Iss. 2 | Feb 2014 | 62 |
Extracting different entities from database has become easy by the different methodologies being
developed but the identification of the relationship among these is still a very challenging task to
perform. Bunescu and Mooney (2005b) have introduced a Statistical Relational Learning model to deal
with this complex problem and are trying to investigate and find results on this side [5].
In current researches, emphasis is also laid on the characteristic of extracting information not only from
one single source but from multiple sources [5].
Extracting facts from multiple sources helps in defining them and understanding them more precisely and
accurately. Many efforts are being laid in this affect.
As another future work, more emphasis is required to be laid on the applications of information
extraction. Investigation on these applications will provide more sources of information extraction and
can bring new challenges to this field. This is because different applications have different
characteristics and different techniques are required to extract information from these fields.
V. Conclusion
This paper includes the study of information extraction systems in the past. Then comes the architecture
of the knowledge extraction system and the different components included in it. It includes domain independent
and domain specific components. Different knowledge extraction techniques are discussed like rule based
technique, pattern learning technique and supervised learning technique. A method of data extraction, web data
extraction, is detailed with its different tools. Tools like DELA (data extraction and label assignment), fifa tech
and IEPAD have been discussed.
Extracting information from web plays a very important role in different business, personal and
scientific applications. The next part of the paper includes the various applications of information extraction.
The different techniques of information extraction helps in designing customer care applications, citation
databases, news tracking applications etc. and in used for the purpose of data cleaning.
A vast progress has been made in this field but a more lot is still to be done. Researches continue in this
field, emerging with new techniques with more efficiency and more performance. A model for information
extraction system which acts as the base model for all the language dependent databases has been developed and
removed the complex problem of developing a separate model for each database with different language as its
base. A great future development is expected in this field with the researches continuing to move in more depth
and bringing in new terms and techniques towards information extraction.
REFERENCES
[1] Jakub Piskorski and Yoman Yangarber (2013), “Information extraction- past, present and future”, The 4th
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