Now days, E-commerce systems have become extremely important. Large numbers of customers are choosing online shopping because of its convenience, reliability, and cost. Client generated information and especially item reviews are significant sources of data for consumers to make informed buy choices and for makers to keep track of customer’s opinions. It is difficult for customers to make purchasing decisions based on only pictures and short product descriptions. On the other hand, mining product reviews has become a hot research topic and prior researches are mostly based on pre-specified product features to analyse the opinions. Natural Language Processing (NLP) techniques such as NLTK for Python can be applied to raw customer reviews and keywords can be extracted. This paper presents a survey on the techniques used for designing software to mine opinion features in reviews. Elven IEEE papers are selected and a comparison is made between them. These papers are representative of the significant improvements in opinion mining in the past decade.
The Process of Information extraction through Natural Language ProcessingWaqas Tariq
Information Retrieval (IR) is the discipline that deals with retrieval of unstructured data, especially textual documents, in response to a query or topic statement, which may itself be unstructured, e.g., a sentence or even another document, or which may be structured, e.g., a boolean expression. The need for effective methods of automated IR has grown in importance because of the tremendous explosion in the amount of unstructured data, both internal, corporate document collections, and the immense and growing number of document sources on the Internet.. The topics covered include: formulation of structured and unstructured queries and topic statements, indexing (including term weighting) of document collections, methods for computing the similarity of queries and documents, classification and routing of documents in an incoming stream to users on the basis of topic or need statements, clustering of document collections on the basis of language or topic, and statistical, probabilistic, and semantic methods of analyzing and retrieving documents. Information extraction from text has therefore been pursued actively as an attempt to present knowledge from published material in a computer readable format. An automated extraction tool would not only save time and efforts, but also pave way to discover hitherto unknown information implicitly conveyed in this paper. Work in this area has focused on extracting a wide range of information such as chromosomal location of genes, protein functional information, associating genes by functional relevance and relationships between entities of interest. While clinical records provide a semi-structured, technically rich data source for mining information, the publications, in their unstructured format pose a greater challenge, addressed by many approaches.
lectronic-mail is widely used most suitable method of transferring messages electronically from one
person to another, rising from and going to any part of the world. Main features of Electronic mail is its speed,
dependability, well-equipped storage options and a large number of added services make it highly well-liked
among people from all sectors of business and society. But being popular it also has negative side too. Electronics
mails are preferred media for a large number of attacks over the internet.. A number of the most popular attacks over
the internet include spams. Some methods are essentially in detection of spam related mails but they have higher false
positives. A number of filters such as Checksum-based filters, Bayesian filters, machine learning based and
memory-based filters are usually used in order to recognize spams. As spammers constantly try to find a way to
avoid existing filters, a new filters need to be developed to catch spam. This paper proposes to find an
resourceful spam mail filtering method using user profile base ontology. Ontologies permit for machineunderstandable
semantics of data. It is main to interchange information with each other for more efficient spam
filtering. Thus, it is essential to build ontology and a framework for capable email filtering. Using ontology that is
particularly designed to filter spam, bunch of useless bulk email could be filtered out on the system. We propose a
user profile-based spam filter that classifies email based on the likelihood that User profile within it have been
included in spam or valid email.
The Process of Information extraction through Natural Language ProcessingWaqas Tariq
Information Retrieval (IR) is the discipline that deals with retrieval of unstructured data, especially textual documents, in response to a query or topic statement, which may itself be unstructured, e.g., a sentence or even another document, or which may be structured, e.g., a boolean expression. The need for effective methods of automated IR has grown in importance because of the tremendous explosion in the amount of unstructured data, both internal, corporate document collections, and the immense and growing number of document sources on the Internet.. The topics covered include: formulation of structured and unstructured queries and topic statements, indexing (including term weighting) of document collections, methods for computing the similarity of queries and documents, classification and routing of documents in an incoming stream to users on the basis of topic or need statements, clustering of document collections on the basis of language or topic, and statistical, probabilistic, and semantic methods of analyzing and retrieving documents. Information extraction from text has therefore been pursued actively as an attempt to present knowledge from published material in a computer readable format. An automated extraction tool would not only save time and efforts, but also pave way to discover hitherto unknown information implicitly conveyed in this paper. Work in this area has focused on extracting a wide range of information such as chromosomal location of genes, protein functional information, associating genes by functional relevance and relationships between entities of interest. While clinical records provide a semi-structured, technically rich data source for mining information, the publications, in their unstructured format pose a greater challenge, addressed by many approaches.
lectronic-mail is widely used most suitable method of transferring messages electronically from one
person to another, rising from and going to any part of the world. Main features of Electronic mail is its speed,
dependability, well-equipped storage options and a large number of added services make it highly well-liked
among people from all sectors of business and society. But being popular it also has negative side too. Electronics
mails are preferred media for a large number of attacks over the internet.. A number of the most popular attacks over
the internet include spams. Some methods are essentially in detection of spam related mails but they have higher false
positives. A number of filters such as Checksum-based filters, Bayesian filters, machine learning based and
memory-based filters are usually used in order to recognize spams. As spammers constantly try to find a way to
avoid existing filters, a new filters need to be developed to catch spam. This paper proposes to find an
resourceful spam mail filtering method using user profile base ontology. Ontologies permit for machineunderstandable
semantics of data. It is main to interchange information with each other for more efficient spam
filtering. Thus, it is essential to build ontology and a framework for capable email filtering. Using ontology that is
particularly designed to filter spam, bunch of useless bulk email could be filtered out on the system. We propose a
user profile-based spam filter that classifies email based on the likelihood that User profile within it have been
included in spam or valid email.
A Simple Information Retrieval Techniqueidescitation
This research examines and analyzes the
information retrieval techniques. The amount of information
available over networks grows every day. This information
worths being accessed and structured. Indexation and
information retrieval are essential tasks to realize these
objectives. This paper proposes an information retrieval
technique which can retrieve appropriate document among a
lot of documents. For doing this first, simplify all the
documents. Then remove stop words and punctuations. It also
calculates the term frequency, inverse term frequency, weight
of each term etc. Here the proposed technique constructs the
master document matrix. By this information retrieval
technique anyone can easily search expected document from
a collection of documents.
Design of A Spell Corrector For Hausa LanguageWaqas Tariq
In this article, a spell corrector has been designed for the Hausa language which is the second most spoken language in Africa and do not yet have processing tools. This study is a contribution to the automatic processing of the Hausa language. We used existing techniques for other languages and adapted them to the special case of the Hausa language. The corrector designed operates essentially on Mijinguini’s dictionary and characteristics of the Hausa alphabet. After a brief review on spell checking and spell correcting techniques and the state of art in the Hausa language processing, we opted for the data structures trie and hash table to represent the dictionary. The edit distance and the specificities of the Hausa alphabet have been used to detect and correct spelling errors. The implementation of the spell corrector has been made on a special editor developed for that purpose (LyTexEditor) but also as an extension (add-on) for OpenOffice.org. A comparison was made on the performance of the two data structures used.
Natural Language Processing reveals the structure and meaning of text by offering powerful machine learning models. You can use it to extract information about people, places, events and much more, mentioned in text documents, news articles or blog posts. You can use it to understand sentiment about your product on social media or parse intent from customer conversations happening in a call center or a messaging app. You can analyze text uploaded in your request or integrate with your document storage.
• What is Natural Language Processing?
• How & where to use NLP
• NLP for information retrieval
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.
A NOVEL APPROACH FOR WORD RETRIEVAL FROM DEVANAGARI DOCUMENT IMAGESijnlc
Large amount of information is lying dormant in historical documents and manuscripts. This information would go futile if not stored in digital form. Searching some relevant information from these scanned images would ideally require converting these document images to text form by doing optical character
recognition (OCR). For indigenous scripts of India, there are very few OCRs that can successfully recognize printed text images of varying quality, size, style and font. An alternate approach using word spotting can be effective to access large collections of document images. We propose a word spotting
technique based on codes for matching the word images of Devanagari script. The shape information is utilised for generating integer codes for words in the document image and these codes are matched for final retrieval of relevant documents. The technique is illustrated using Marathi document images.
A language independent approach to develop urduir systemcsandit
This is the era of Information Technology. Today the most important thing is how one gets the
right information at right time. More and more data repositories are now being made available
online. Information retrieval systems or search engines are used to access electronic
information available on the internet. These information retrieval systems depend on the
available tools and techniques for efficient retrieval of information content in response to the
user query needs. During last few years, a wide range of information in Indian regional
languages like Hindi, Urdu, Bengali, Oriya, Tamil and Telugu has been made available on web
in the form of e-data. But the access to these data repositories is very low because the efficient
search engines/retrieval systems supporting these languages are very limited. We have
developed a language independent system to facilitate efficient retrieval of information
available in Urdu language which can be used for other languages as well. The system gives
precision of 0.63 and the recall of the system is 0.8.
A LANGUAGE INDEPENDENT APPROACH TO DEVELOP URDUIR SYSTEMcscpconf
This is the era of Information Technology. Today the most important thing is how one gets theright information at right time. More and more data repositories are now being made available online. Information retrieval systems or search engines are used to access electronic information available on the internet. These information retrieval systems depend on the available tools and techniques for efficient retrieval of information content in response to the user query needs. During last few years, a wide range of information in Indian regional languages like Hindi, Urdu, Bengali, Oriya, Tamil and Telugu has been made available on web in the form of e-data. But the access to these data repositories is very low because the efficient search engines/retrieval systems supporting these languages are very limited. We have developed a language independent system to facilitate efficient retrieval of information available in Urdu language which can be used for other languages as well. The system gives precision of 0.63 and the recall of the system is 0.8.
This paper proposes Natural language based Discourse Analysis method used for extracting
information from the news article of different domain. The Discourse analysis used the Rhetorical Structure
theory which is used to find coherent group of text which are most prominent for extracting information
from text. RST theory used the Nucleus- Satellite concept for finding most prominent text from the text
document. After Discourse analysis the text analysis has been done for extracting domain related object
and relates this object. For extracting the information knowledge based system has been used which
consist of domain dictionary .The domain dictionary has a bag of words for domain. The system is
evaluated according gold-of-art analysis and human decision for extracted information.
DataFest 2017. Introduction to Natural Language Processing by Rudolf Eremyanrudolf eremyan
The objective of this workshop is to show how natural language processing applied in modern applications such as Google Search, Apple Siri, Bing Translator and etc. During the workshop we will go through history if natural language processing, talk about typical problems, consider classical approaches and methods, and compare them with state-of-the-art deep learning techniques.
Author: Rudolf Eremyan
Email: eremyan.rudolf@gmail.com
Phone: +995599607066
LinkedIn: https://www.linkedin.com/in/rudolferemyan/
DataFest Tbilisi 2017 website: https://datafest.ge
A Novel Approach for Keyword extraction in learning objects using text miningIJSRD
Keyword extraction, concept finding are in learning objects is very important subject in today’s eLearning environment. Keywords are subset of words that contains the useful information about the content of the document. Keyword extraction is a process that is used to get the important keywords from documents. In this proposed System Decision tree algorithm is used for feature selection process using wordnet dictionary. WordNet is a lexical database of English which is used to find similarity from the candidate words. The words having highest similarity are taken as keywords.
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 Paraffin Section Mounting Bath has been designed for ease of use and maximum safety. The top has generous space for resting the hands and a deep tapered bowl allowing slides to be used at any angle. The four rubber feet and the low level
of the whole instrument provide stability.
A Simple Information Retrieval Techniqueidescitation
This research examines and analyzes the
information retrieval techniques. The amount of information
available over networks grows every day. This information
worths being accessed and structured. Indexation and
information retrieval are essential tasks to realize these
objectives. This paper proposes an information retrieval
technique which can retrieve appropriate document among a
lot of documents. For doing this first, simplify all the
documents. Then remove stop words and punctuations. It also
calculates the term frequency, inverse term frequency, weight
of each term etc. Here the proposed technique constructs the
master document matrix. By this information retrieval
technique anyone can easily search expected document from
a collection of documents.
Design of A Spell Corrector For Hausa LanguageWaqas Tariq
In this article, a spell corrector has been designed for the Hausa language which is the second most spoken language in Africa and do not yet have processing tools. This study is a contribution to the automatic processing of the Hausa language. We used existing techniques for other languages and adapted them to the special case of the Hausa language. The corrector designed operates essentially on Mijinguini’s dictionary and characteristics of the Hausa alphabet. After a brief review on spell checking and spell correcting techniques and the state of art in the Hausa language processing, we opted for the data structures trie and hash table to represent the dictionary. The edit distance and the specificities of the Hausa alphabet have been used to detect and correct spelling errors. The implementation of the spell corrector has been made on a special editor developed for that purpose (LyTexEditor) but also as an extension (add-on) for OpenOffice.org. A comparison was made on the performance of the two data structures used.
Natural Language Processing reveals the structure and meaning of text by offering powerful machine learning models. You can use it to extract information about people, places, events and much more, mentioned in text documents, news articles or blog posts. You can use it to understand sentiment about your product on social media or parse intent from customer conversations happening in a call center or a messaging app. You can analyze text uploaded in your request or integrate with your document storage.
• What is Natural Language Processing?
• How & where to use NLP
• NLP for information retrieval
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.
A NOVEL APPROACH FOR WORD RETRIEVAL FROM DEVANAGARI DOCUMENT IMAGESijnlc
Large amount of information is lying dormant in historical documents and manuscripts. This information would go futile if not stored in digital form. Searching some relevant information from these scanned images would ideally require converting these document images to text form by doing optical character
recognition (OCR). For indigenous scripts of India, there are very few OCRs that can successfully recognize printed text images of varying quality, size, style and font. An alternate approach using word spotting can be effective to access large collections of document images. We propose a word spotting
technique based on codes for matching the word images of Devanagari script. The shape information is utilised for generating integer codes for words in the document image and these codes are matched for final retrieval of relevant documents. The technique is illustrated using Marathi document images.
A language independent approach to develop urduir systemcsandit
This is the era of Information Technology. Today the most important thing is how one gets the
right information at right time. More and more data repositories are now being made available
online. Information retrieval systems or search engines are used to access electronic
information available on the internet. These information retrieval systems depend on the
available tools and techniques for efficient retrieval of information content in response to the
user query needs. During last few years, a wide range of information in Indian regional
languages like Hindi, Urdu, Bengali, Oriya, Tamil and Telugu has been made available on web
in the form of e-data. But the access to these data repositories is very low because the efficient
search engines/retrieval systems supporting these languages are very limited. We have
developed a language independent system to facilitate efficient retrieval of information
available in Urdu language which can be used for other languages as well. The system gives
precision of 0.63 and the recall of the system is 0.8.
A LANGUAGE INDEPENDENT APPROACH TO DEVELOP URDUIR SYSTEMcscpconf
This is the era of Information Technology. Today the most important thing is how one gets theright information at right time. More and more data repositories are now being made available online. Information retrieval systems or search engines are used to access electronic information available on the internet. These information retrieval systems depend on the available tools and techniques for efficient retrieval of information content in response to the user query needs. During last few years, a wide range of information in Indian regional languages like Hindi, Urdu, Bengali, Oriya, Tamil and Telugu has been made available on web in the form of e-data. But the access to these data repositories is very low because the efficient search engines/retrieval systems supporting these languages are very limited. We have developed a language independent system to facilitate efficient retrieval of information available in Urdu language which can be used for other languages as well. The system gives precision of 0.63 and the recall of the system is 0.8.
This paper proposes Natural language based Discourse Analysis method used for extracting
information from the news article of different domain. The Discourse analysis used the Rhetorical Structure
theory which is used to find coherent group of text which are most prominent for extracting information
from text. RST theory used the Nucleus- Satellite concept for finding most prominent text from the text
document. After Discourse analysis the text analysis has been done for extracting domain related object
and relates this object. For extracting the information knowledge based system has been used which
consist of domain dictionary .The domain dictionary has a bag of words for domain. The system is
evaluated according gold-of-art analysis and human decision for extracted information.
DataFest 2017. Introduction to Natural Language Processing by Rudolf Eremyanrudolf eremyan
The objective of this workshop is to show how natural language processing applied in modern applications such as Google Search, Apple Siri, Bing Translator and etc. During the workshop we will go through history if natural language processing, talk about typical problems, consider classical approaches and methods, and compare them with state-of-the-art deep learning techniques.
Author: Rudolf Eremyan
Email: eremyan.rudolf@gmail.com
Phone: +995599607066
LinkedIn: https://www.linkedin.com/in/rudolferemyan/
DataFest Tbilisi 2017 website: https://datafest.ge
A Novel Approach for Keyword extraction in learning objects using text miningIJSRD
Keyword extraction, concept finding are in learning objects is very important subject in today’s eLearning environment. Keywords are subset of words that contains the useful information about the content of the document. Keyword extraction is a process that is used to get the important keywords from documents. In this proposed System Decision tree algorithm is used for feature selection process using wordnet dictionary. WordNet is a lexical database of English which is used to find similarity from the candidate words. The words having highest similarity are taken as keywords.
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 Paraffin Section Mounting Bath has been designed for ease of use and maximum safety. The top has generous space for resting the hands and a deep tapered bowl allowing slides to be used at any angle. The four rubber feet and the low level
of the whole instrument provide stability.
The hidden workforce has the potential to change a million small businesses in the UK. Find out how on-demand freelancers can help small businesses grow.
The Indian Dental Academy is the Leader in continuing dental education , training dentists in all aspects of dentistry and
offering a wide range of dental certified courses in different formats.for more details please visit
www.indiandentalacademy.com
A sprint thru Python's Natural Language ToolKit, presented at SFPython on 9/14/2011. Covers tokenization, part of speech tagging, chunking & NER, text classification, and training text classifiers with nltk-trainer.
16 Decision Support and Business Intelligence Systems (9th E.docxRAJU852744
16 Decision Support and Business Intelligence Systems (9th Edition) Instructor’s Manual
Chapter 7:
Text Analytics, Text Mining, and Sentiment Analysis
Learning Objectives for Chapter 7
1. Describe text mining and understand the need for text mining
2. Differentiate among text analytics, text mining, and data mining
3. Understand the different application areas for text mining
4. Know the process of carrying out a text mining project
5. Appreciate the different methods to introduce structure to text-based data
6. Describe sentiment analysis
7. Develop familiarity with popular applications of sentiment analysis
8. Learn the common methods for sentiment analysis
9. Become familiar with speech analytics as it relates to sentiment analysis
10. Learn three facets of Web analytics—content, structure, and usage mining
11. Know social analytics including social media and social network analyses
CHAPTER OVERVIEW
This chapter provides a comprehensive overview of text analytics/mining and Web analytics/mining along with their popular application areas such as search engines, sentiment analysis, and social network/media analytics. As we have been witnessing in recent years, the unstructured data generated over the Internet of Things (IoT) (Web, sensor networks, radio-frequency identification [RFID]–enabled supply chain systems, surveillance networks, etc.) are increasing at an exponential pace, and there is no indication of its slowing down. This changing nature of data is forcing organizations to make text and Web analytics a critical part of their business intelligence/analytics infrastructure.
CHAPTER OUTLINE
7.1 Opening Vignette: Amadori Group Converts Consumer Sentiments into
Near-Real-Time Sales
7.2 Text Analytics and Text Mining Overview
7.3 Natural Language Processing (NLP)
7.4 Text Mining Applications
7.5 Text Mining Process
7.6 Sentiment Analysis
7.7 Web Mining Overview
7.8 Search Engines
7.9 Web Usage Mining
7.10 Social Analytics
ANSWERS TO END OF SECTION REVIEW QUESTIONS( ( ( ( ( (
Section 7.1 Review Questions
1. According to the vignette and based on your opinion, what are the challenges that the food industry is facing today?
Student perceptions may vary, but some common themes related to the challenges faced by the food industry could include the changing nature and role of food in people’s lifestyles, the shift towards pre-prepared or easily prepared food, and the growing importance of marketing to keep customers interested in brands.
2. How can analytics help businesses in the food industry to survive and thrive in this competitive marketplace?
Analytics can serve dual purposes by both tracking customer interest in the brand as well as providing valuable feedback on customer preferences. An analytics system can be used to evaluate the traffic to various brand marketing campaigns (website or social) that play a pivotal role in ensuring that products are being shown to new pot.
16 Decision Support and Business Intelligence Systems (9th E.docxherminaprocter
16 Decision Support and Business Intelligence Systems (9th Edition) Instructor’s Manual
Chapter 7:
Text Analytics, Text Mining, and Sentiment Analysis
Learning Objectives for Chapter 7
1. Describe text mining and understand the need for text mining
2. Differentiate among text analytics, text mining, and data mining
3. Understand the different application areas for text mining
4. Know the process of carrying out a text mining project
5. Appreciate the different methods to introduce structure to text-based data
6. Describe sentiment analysis
7. Develop familiarity with popular applications of sentiment analysis
8. Learn the common methods for sentiment analysis
9. Become familiar with speech analytics as it relates to sentiment analysis
10. Learn three facets of Web analytics—content, structure, and usage mining
11. Know social analytics including social media and social network analyses
CHAPTER OVERVIEW
This chapter provides a comprehensive overview of text analytics/mining and Web analytics/mining along with their popular application areas such as search engines, sentiment analysis, and social network/media analytics. As we have been witnessing in recent years, the unstructured data generated over the Internet of Things (IoT) (Web, sensor networks, radio-frequency identification [RFID]–enabled supply chain systems, surveillance networks, etc.) are increasing at an exponential pace, and there is no indication of its slowing down. This changing nature of data is forcing organizations to make text and Web analytics a critical part of their business intelligence/analytics infrastructure.
CHAPTER OUTLINE
7.1 Opening Vignette: Amadori Group Converts Consumer Sentiments into
Near-Real-Time Sales
7.2 Text Analytics and Text Mining Overview
7.3 Natural Language Processing (NLP)
7.4 Text Mining Applications
7.5 Text Mining Process
7.6 Sentiment Analysis
7.7 Web Mining Overview
7.8 Search Engines
7.9 Web Usage Mining
7.10 Social Analytics
ANSWERS TO END OF SECTION REVIEW QUESTIONS( ( ( ( ( (
Section 7.1 Review Questions
1. According to the vignette and based on your opinion, what are the challenges that the food industry is facing today?
Student perceptions may vary, but some common themes related to the challenges faced by the food industry could include the changing nature and role of food in people’s lifestyles, the shift towards pre-prepared or easily prepared food, and the growing importance of marketing to keep customers interested in brands.
2. How can analytics help businesses in the food industry to survive and thrive in this competitive marketplace?
Analytics can serve dual purposes by both tracking customer interest in the brand as well as providing valuable feedback on customer preferences. An analytics system can be used to evaluate the traffic to various brand marketing campaigns (website or social) that play a pivotal role in ensuring that products are being shown to new pot.
Natural Language Processing (NLP) is a subfield of artificial intelligence (AI) and computational linguistics that focuses on enabling computers to understand and interact with human language. It combines techniques from computer science, linguistics, and statistics to bridge the gap between human language and machine understanding. NLP has gained significant attention in recent years due to advancements in AI and the increasing need for machines to process and interpret vast amounts of textual data.
Text Mining is the technique that helps users to find out useful information from a large amount of text documents on the web or database. Most popular text mining and classification methods have adopted term-based approaches. The term based approaches and the pattern-based method describing user preferences. This review paper analyse how the text mining work on the three level i.e sentence level, document level and feature level. In this paper we review the related work which is previously done. This paper also demonstrated that what are the problems arise while doing text mining done at the feature level. This paper presents the technique to text mining for the compound sentences.
Natural Language Processing Theory, Applications and Difficultiesijtsrd
The promise of a powerful computing device to help people in productivity as well as in recreation can only be realized with proper human machine communication. Automatic recognition and understanding of spoken language is the first step toward natural human machine interaction. Research in this field has produced remarkable results, leading to many exciting expectations and new challenges. This field is known as Natural language Processing. In this paper the natural language generation and Natural language understanding is discussed. Difficulties in NLU, applications and comparison with structured programming language are also discussed here. Mrs. Anjali Gharat | Mrs. Helina Tandel | Mr. Ketan Bagade "Natural Language Processing Theory, Applications and Difficulties" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-6 , October 2019, URL: https://www.ijtsrd.com/papers/ijtsrd28092.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/28092/natural-language-processing-theory-applications-and-difficulties/mrs-anjali-gharat
COMPREHENSIVE ANALYSIS OF NATURAL LANGUAGE PROCESSING TECHNIQUEJournal For Research
Natural Language Processing (NLP) techniques are one of the most used techniques in the field of computer applications. It has become one of the vast and advanced techniques. Language is the means of communication or interaction among humans and in present scenario when everything is dependent on machine or everything is computerized, communication between computer and human has become a necessity. To fulfill this necessity NLP has been emerged as the means of interaction which narrows the gap between machines (computers) and humans. It was evolved from the study of linguistics which was passed through the Turing test to check the similarity between data but it was limited to small set of data. Later on various algorithms were developed along with the concept of AI (Artificial Intelligence) for the successful execution of NLP. In this paper, the main emphasis is on the different techniques of NLP which have been developed till now, their applications and the comparison of all those techniques on different parameters.
Natural Language Processing (NLP) is a branch of artificial intelligence (AI) that focuses on the interaction between computers and human language. It encompasses a range of techniques and technologies that enable machines to understand, interpret, and generate human language in a way that is meaningful and useful.
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Lexicon Based Emotion Analysis on Twitter Dataijtsrd
This paper presents a system that extracts information from automatically annotated tweets using well known existing opinion lexicons and supervised machine learning approach. In this paper, the sentiment features are primarily extracted from novel high coverage tweet specific sentiment lexicons. These lexicons are automatically generated from tweets with sentiment word hashtags and from tweets with emoticons. The sentence level or tweet level classification is done based on these word level sentiment features by using Sequential Minimal Optimization SMO classifier. SemEval 2013 Twitter sentiment dataset is applied in this work. The ablation experiments show that this system gains in F Score of up to 6.8 absolute percentage points. Nang Noon Kham "Lexicon Based Emotion Analysis on Twitter Data" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26566.pdfPaper URL: https://www.ijtsrd.com/computer-science/data-miining/26566/lexicon-based-emotion-analysis-on-twitter-data/nang-noon-kham
Comparative Analysis of Existing and a Novel Approach to Topic Detection on C...kevig
Topic detection in dialogue datasets has become a significant challenge for unsupervised
and unlabeled data to develop a cohesive and engaging dialogue system. In this paper, we
proposed unsupervised and semi-supervised techniques for topic detection in the conversational dialogue dataset and compared them with existing topic detection techniques. The
paper proposes a novel approach for topic detection, which takes preprocessed data as an
input and performs similarity analysis with the TF-IDF scores bag of words technique
(BOW) to identify higher frequency words from dialogue utterances. It then refines the
higher frequency words by integrating the clustering and elbow methods and using the Parallel Latent Dirichlet Allocation (PLDA) model to detect the topics. The paper comprised a
comparative analysis of the proposed approach on the Switchboard, Personachat and MultiWOZ dataset. The experimental results show that the proposed topic detection approach
performs significantly better using a semi-supervised dialogue dataset. We also performed
topic quantification to check how accurate extracted topics are to compare with manually
annotated data. For example, extracted topics from Switchboard are 92.72%, Peronachat
87.31% and MultiWOZ 93.15% accurate with manually annotated data.
Similar to Mining Opinion Features in Customer Reviews (20)
Light Dimmer with Implementation of Data Abstraction While CrashingIJCERT JOURNAL
The paper proposes a system to automatically dim the headlight of opposite vehicles by changing from high beam to low beam. The system envisioned is automatic collision avoidance and detection. Many methods are available to dim the headlight of vehicles. In the earlier days dip mechanism was used. Similarly there are several mechanisms for automatic accident detection. An automatic alarm gadget for traffic accidents is presented. It can consequently discover a car crash; hunt down the spot and after that send the essential data to hospitals. This system will highly aid the search and rescue of vehicles that have met with an accident.
Augmenting Publish/Subscribe System by Identity Based Encryption (IBE) Techni...IJCERT JOURNAL
Security is one of the extensive and complicated requirements that need to be provided in order to achieve few issues like confidentiality, integrity and authentication. In a content-based publish/subscribe system, authentication is difficult to achieve since there exists no strong bonding between the end parties. Similarly, Integrity and confidentiality needs arise in published events and subscription conflicts with content-based routing. The basic tool to support confidentiality, integrity is encryption. In this paper for providing security mechanism in broker-less content-based publish/subscribe system we adapt pairing-based cryptography mechanism. In this mechanism, we use Identity Based Encryption (IBE) technique to achieve the needs of publish/subscribe system. This approach helps in providing fine-grained key management, effective encryption, decryption operations and routing is carried out in the order of subscribed attributes
Design of an adaptive JPEG Steganalysis with UED IJCERT JOURNAL
Steganography is the art and science of writing hidden messages in such a way that no one apart from the sender and intended recipient suspects the existence of the message a form of security through obscurity. The internet as a whole does not use secure links, thus information in transit may be vulnerable to interception as well. The important of reducing a chance of the information being detected during the transmission is being an issue now days. In this paper, we proposed a class of new distortion functions known as uniform embedding distortion function (UED) is presented. By incorporating the syndrome trellis coding, the best code word with undetectable data hiding is achieved. Due to hiding more amounts of data into the intersected area, embedding capacity is increased. Our aim is to hide the secret information behind the image file. Steganography hides the secret message so that intruder’s can’t detect the communication. When hiding data into the intersected area, thus provides a higher level of security with more efficient data mean square error is reduced and embedding capacity is increased.
In this paper we have penetrate an era of Big Data. Through better analysis of the large volumes of data that are becoming available, there is the potential for making faster advances in many scientific disciplines and improving the profitability and success of many enterprises. However, many technical challenges described in this paper must be addressed before this potential can be realized fully. The challenges include not just the obvious issues of scale, but also heterogeneity, lack of structure, error-handling, privacy, timeliness, provenance, and visualization, at all stages of the analysis pipeline from data acquisition to result interpretation.
Investigation on Revocable Fine-grained Access Control Scheme for Multi-Autho...IJCERT JOURNAL
Cloud computing is one of the emerge technologies in order to outsource huge volume of data inters of storage and sharing. To protect the data and privacy of users the access control methods ensure that authorized users access the data and the system. Fine grained-approach is the appropriate method for data access control in cloud storage. However, CP-ABE schemes to data access control for cloud storage systems are difficult because of the attribute revocation problem. Specifically, in this paper we investigate on revocable multi-authority Fine-grained-Scheme performance.
A Secure Multi-Owner Data Sharing Scheme for Dynamic Group in Public Cloud. IJCERT JOURNAL
In cloud computing outsourcing group resource among cloud users is a major challenge, so cloud computing provides a low-cost and well-organized solution. Due to frequent change of membership, sharing data in a multi-owner manner to an untrusted cloud is still its challenging issue. In this paper we proposed a secure multi-owner data sharing scheme for dynamic group in public cloud. By providing AES encryption with convergent key while uploading the data, any cloud user can securely share data with others. Meanwhile, the storage overhead and encryption computation cost of the scheme are independent with the number of revoked users. In addition, I analyze the security of this scheme with rigorous proofs. One-Time Password is one of the easiest and most popular forms of authentication that can be used for securing access to accounts. One-Time Passwords are often referred to as secure and stronger forms of authentication in multi-owner manner. Extensive security and performance analysis shows that our proposed scheme is highly efficient and satisfies the security requirements for public cloud based secure group sharing.
Secure Redundant Data Avoidance over Multi-Cloud Architecture. IJCERT JOURNAL
Redundant data avoidance systems, the Private Cloud are involved as a proxy to allow data owner/users to securely perform duplicate check with differential privileges. Such architecture is practical and has attracted much attention from researchers. The data owners only outsource their data storage by utilizing public cloud while the data operation is managed in private cloud, in this connection our presented system has follows traditional encryption while providing data confidentiality, is incompatible with redundant data avoidance. Identical data copies of different users will lead to different ciphertexts, making data avoidance impossible. To address above issues convergent encryption technique has been proposed to encrypt the data before outsourcing. To better protect data security, this paper makes the first attempt to formally address the problem of authorized redundant data avoidance. Different from traditional redundant data avoidance systems, the differential privileges of users are further considered in duplicate check besides the data itself. We also present several new redundant data avoidance constructions supporting authorized duplicate check in a multi-cloud architecture. Security analysis demonstrates that our scheme is secure in terms of the definitions specified in the proposed security model. In order to perform secure access controlling scheme user may satisfy fine-grained approach at cloud level towards access restricting from unauthorized users or adversaries.
SURVEY ON IMPLEMANTATION OF COLUMN ORIENTED NOSQL DATA STORES ( BIGTABLE & CA...IJCERT JOURNAL
NOSQL is a database provides a mechanism for storage and retrieval of data that is modeled for huge amount of data which is used in big data and Cloud Computing . NOSQL systems are also called "Not only SQL" to emphasize that they may support SQL-like query languages. A basic classification of NOSQL is based on data model; they are like column, Document, Key-Value etc. The objective of this paper is to study and compare the implantation of various column oriented data stores like Bigtable, Cassandra.
Security Issues’ in Cloud Computing and its Solutions. IJCERT JOURNAL
Cloud computing is a set of IT services that are provided to a customer over a network on a leased basis and with the ability to scale up or down their service requirements. Usually cloud computing services are delivered by a third party provider who owns the infrastructure. It advantages to mention but a few include scalability, resilience, flexibility, efficiency and outsourcing non-core activities. Cloud computing offers an innovative business model for organizations to adopt IT services without upfront investment. Despite the potential gains achieved from the cloud computing, the organizations are slow in accepting it due to security issues and challenges associated with it. Security is one of the major issues which hamper the growth of cloud. The idea of handing over important data to another company is worrisome; such that the consumers need to be vigilant in understanding the risks of data breaches in this new environment. This paper introduces a detailed analysis of the cloud computing security issues and challenges focusing on the cloud computing types and the service delivery types.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/