This document discusses an approach to document clustering called "Semantic Lingo" which aims to identify key concepts in documents and automatically generate an ontology based on these concepts to better conceptualize the documents. It provides background on challenges with traditional document clustering techniques and search engines. The proposed approach uses semantic information from domain ontologies to improve web search clustering quality by addressing issues like synonyms, polysemy and high dimensionality. It also discusses using text segments within documents that focus on one or more topics to aid multi-topic document clustering.
`A Survey on approaches of Web Mining in Varied Areasinventionjournals
There has been lot of research in recent years for efficient web searching. Several papers have proposed algorithm for user feedback sessions, to evaluate the performance of inferring user search goals. When the information is retrieved, user clicks on a particular URL. Based on the click rate, ranking will be done automatically, clustering the feedback sessions. Web search engines have made enormous contributions to the web and society. They make finding information on the web quick and easy. However, they are far from optimal. A major deficiency of generic search engines is that they follow the ‘‘one size fits all’’ model and are not adaptable to individual users.
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 is an update on the status of federal requirements for data sharing in 2015. These slides were presented at ACRL in Portland in March 2015, by Linda Detterman and Jared Lyle of ICPSR, based at the University of Michigan. The session includes overviews of federal requirements, data curation, data management plans, data sharing services, and lots of fun!
`A Survey on approaches of Web Mining in Varied Areasinventionjournals
There has been lot of research in recent years for efficient web searching. Several papers have proposed algorithm for user feedback sessions, to evaluate the performance of inferring user search goals. When the information is retrieved, user clicks on a particular URL. Based on the click rate, ranking will be done automatically, clustering the feedback sessions. Web search engines have made enormous contributions to the web and society. They make finding information on the web quick and easy. However, they are far from optimal. A major deficiency of generic search engines is that they follow the ‘‘one size fits all’’ model and are not adaptable to individual users.
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 is an update on the status of federal requirements for data sharing in 2015. These slides were presented at ACRL in Portland in March 2015, by Linda Detterman and Jared Lyle of ICPSR, based at the University of Michigan. The session includes overviews of federal requirements, data curation, data management plans, data sharing services, and lots of fun!
Data Sharing with ICPSR: Fueling the Cycle of Science through Discovery, Acce...ICPSR
Data Sharing with ICPSR was presented at IASSIST 2015 in Minneapolis, MN.
The learning objectives and content cover:
- Federal data sharing requirements and
other good reasons to share data
• Options for sharing data
• Protection of confidentiality when
sharing data
• Data discovery tools
• Online data exploration tools from ICPSR
Classification-based Retrieval Methods to Enhance Information Discovery on th...IJMIT JOURNAL
The widespread adoption of the World-Wide Web (the Web) has created challenges both for society as a whole and for the technology used to build and maintain the Web. The ongoing struggle of information retrieval systems is to wade through this vast pile of data and satisfy users by presenting them with information that most adequately it’s their needs. On a societal level, the Web is expanding faster than we can comprehend its implications or develop rules for its use. The ubiquitous use of the Web has raised important social concerns in the areas of privacy, censorship, and access to information. On a technical level, the novelty of the Web and the pace of its growth have created challenges not only in the development of new applications that realize the power of the Web, but also in the technology needed to scale applications to accommodate the resulting large data sets and heavy loads. This thesis presents searching algorithms and hierarchical classification techniques for increasing a search service's understanding of web queries. Existing search services rely solely on a query's occurrence in the document collection to locate relevant documents. They typically do not perform any task or topic-based analysis of queries using other available resources, and do not leverage changes in user query patterns over time. Provided within are a set of techniques and metrics for performing temporal analysis on query logs. Our log analyses are shown to be reasonable and informative, and can be used to detect changing trends and patterns in the query stream, thus providing valuable data to a search service.
Information technology and resources are an integral and indispensable part of the contemporary academic enterprise. In particular, technological advances have nurtured a new paradigm of data-intensive research. However, far too much of this activity still takes place in silos, to the detriment of open scholarly inquiry, integrity, and advancement. To counteract this tendency, the University of California Curation Center (UC3) has been developing and deploying a comprehensive suite of curation services that facilitate widespread data management, preservation, publication, sharing, and reuse. Through these services UC3 is engaging with new communities of use: in addition to its traditional stakeholders in cultural heritage memory organizations, e.g., libraries, museums, and archives, the UC3 service suite is now attracting significant adoption by research projects, laboratories, and individual faculty researchers. This webinar will present an introduction to five specific services – DMPTool, DataUp, EZID, Merritt, Web Archiving Service (WAS) – applicable to data curation throughout the scholarly lifecycle, two recent initiatives in collaboration with UC campuses, UC Berkeley Research Hub and UC San Francisco DataShare, and the ways in which they encourage and promote new communities of practice and greater transparency in scholarly research.
Integration of research literature and data (InFoLiS)Philipp Zumstein
Talk at CNI 2015 Spring Membership Meeting in Seattle on April 14th, 2015, see http://www.cni.org/events/membership-meetings/upcoming-meeting/spring-2015/
Abstract: The goal of the InFoLiS project is to connect research data and publications. Links between data and literature are created automatically by means of text mining and made available as Linked Open Data (LOD) for seamless integration into different retrieval systems. This enables scientists to directly access information about corresponding research data in a literature information system, and, vice versa, it is possible to directly find different interpretations and analyses in the literature of the same research data. In our talk, we will describe our methods for generating the links and give insight into the Linked Data infrastructure including the services we are currently building. Most importantly, we will detail how our solutions can be used by other institutions and invite all interested participants to discuss with us their ideas and thoughts on the requirements for these services to ensure broad interoperability with existing systems and infrastructures. InFoLiS is a joint project by the GESIS – Leibniz Institute for the Social Sciences, Cologne, Mannheim University Library, and Mannheim University supported by a grant from the DFG – German Research Foundation.
Meeting Federal Research Requirements for Data Management Plans, Public Acces...ICPSR
These slides cover evolving federal research requirements for sharing scientific data. Provided are updates on federal agency responses to the 2013 OSTP memo, guidance on data management plans, resources for data management and curation training for staff/researchers, and tips for evaluating public data-sharing services. ICPSR's public data-sharing service, openICPSR, is also presented. Recording of this presentation is here: https://www.youtube.com/watch?v=2_erMkASSv4&feature=youtu.be
Performance Evaluation of Query Processing Techniques in Information Retrievalidescitation
The first element of the search process is the query.
The user query being on an average restricted to two or three
keywords makes the query ambiguous to the search engine.
Given the user query, the goal of an Information Retrieval
[IR] system is to retrieve information which might be useful
or relevant to the information need of the user. Hence, the
query processing plays an important role in IR system.
The query processing can be divided into four categories
i.e. query expansion, query optimization, query classification and
query parsing. In this paper an attempt is made to evaluate the
performance of query processing algorithms in each of the
category. The evaluation was based on dataset as specified by
Forum for Information Retrieval [FIRE15]. The criteria used
for evaluation are precision and relative recall. The analysis is
based on the importance of each step in query processing. The
experimental results show that the significance of each step
in query processing and also the relevance of web semantics
and spelling correction in the user query.
WEB SEARCH ENGINE BASED SEMANTIC SIMILARITY MEASURE BETWEEN WORDS USING PATTE...cscpconf
Semantic Similarity measures plays an important role in information retrieval, natural language processing and various tasks on web such as relation extraction, community mining, document clustering, and automatic meta-data extraction. In this paper, we have proposed a Pattern Retrieval Algorithm [PRA] to compute the semantic similarity measure between the words by
combining both page count method and web snippets method. Four association measures are used to find semantic similarity between words in page count method using web search engines. We use a Sequential Minimal Optimization (SMO) support vector machines (SVM) to find the optimal combination of page counts-based similarity scores and top-ranking patterns from the web snippets method. The SVM is trained to classify synonymous word-pairs and nonsynonymous word-pairs. The proposed approach aims to improve the Correlation values,
Precision, Recall, and F-measures, compared to the existing methods. The proposed algorithm outperforms by 89.8 % of correlation value.
Research on Document Indexing in the Search Engines. The main theme of Informational retrieval is to send the exact response of a user for specific Query.
The information search retrieval is a very big process, to achieve this concept we need to develop an application with more effect and we have to use techniques like Document indexing, page ranking, clustering technique. Among all of these Document index is plays avital role while searching why since instead of searching hundreds of thousands of documents it will directly go to the particular index and will give the output here. Here our achievement mainly is indexing, the clear meaning of the indexing is storing an index is to optimize speed and performance in finding the appropriate/corresponding document for the user searched query.
My conclusion is the context based index approach is used in the query retrieval, this is mainly from the source document. Instead of searching every page on server, finding technically is better. Due to this we can save our time, we can reduce the burden of server.
An Advanced IR System of Relational Keyword Search Techniquepaperpublications3
Abstract: Now these days keyword search to relational data set becomes an area of research within the data base and Information Retrieval. There is no standard process of information retrieval, which will clearly show the accurate result also it shows keyword search with ranking. Execution time is retrieving of data is more in existing system. We propose a system for increasing performance of relational keyword search systems. In the proposed system we combine schema-based and graph-based approaches and propose a Relational Keyword Search System to overcome the mentioned disadvantages of existing systems and manage the information and user access the information very efficiently. Keyword Search with the ranking requires very low execution time. Execution time of retrieving information and file length during Information retrieval can be display using chart.Keywords: Keyword Search, Datasets, Information Retrieval Query Workloads, Schema-based Systems, Graph-based Systems, ranking, relational databases.
Title: An Advanced IR System of Relational Keyword Search Technique
Author: Dhananjay A. Gholap, Gumaste S. V
ISSN 2350-1022
International Journal of Recent Research in Mathematics Computer Science and Information Technology
Paper Publications
Context Driven Technique for Document ClassificationIDES Editor
In this paper we present an innovative hybrid Text
Classification (TC) system that bridges the gap between
statistical and context based techniques. Our algorithm
harnesses contextual information at two stages. First it extracts
a cohesive set of keywords for each category by using lexical
references, implicit context as derived from LSA and wordvicinity
driven semantics. And secondly, each document is
represented by a set of context rich features whose values are
derived by considering both lexical cohesion as well as the extent
of coverage of salient concepts via lexical chaining. After
keywords are extracted, a subset of the input documents is
apportioned as training set. Its members are assigned categories
based on their keyword representation. These labeled
documents are used to train binary SVM classifiers, one for
each category. The remaining documents are supplied to the
trained classifiers in the form of their context-enhanced feature
vectors. Each document is finally ascribed its appropriate
category by an SVM classifier.
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.
Enhanced Web Usage Mining Using Fuzzy Clustering and Collaborative Filtering ...inventionjournals
Information is overloaded in the Internet due to the unstable growth of information and it makes information search as complicate process. Recommendation System (RS) is the tool and largely used nowadays in many areas to generate interest items to users. With the development of e-commerce and information access, recommender systems have become a popular technique to prune large information spaces so that users are directed toward those items that best meet their needs and preferences. As the exponential explosion of various contents generated on the Web, Recommendation techniques have become increasingly indispensable. Web recommendation systems assist the users to get the exact information and facilitate the information search easier. Web recommendation is one of the techniques of web personalization, which recommends web pages or items to the user based on the previous browsing history. But the tremendous growth in the amount of the available information and the number of visitors to web sites in recent years places some key challenges for recommender system. The recent recommender systems stuck with producing high quality recommendation with large information, resulting unwanted item instead of targeted item or product, and performing many recommendations per second for millions of user and items. To avoid these challenges a new recommender system technologies are needed that can quickly produce high quality recommendation, even for a very large scale problems. To address these issues we use two recommender system process using fuzzy clustering and collaborative filtering algorithms. Fuzzy clustering is used to predict the items or product that will be accessed in the future based on the previous action of user browsers behavior. Collaborative filtering recommendation process is used to produce the user expects result from the result of fuzzy clustering and collection of Web Database data items. Using this new recommendation system, it results the user expected product or item with minimum time. This system reduces the result of unrelated and unwanted item to user and provides the results with user interested domain.
Majority of the computer or mobile phone enthusiasts make use of the web for searching
activity. Web search engines are used for the searching; The results that the search engines get
are provided to it by a software module known as the Web Crawler. The size of this web is
increasing round-the-clock. The principal problem is to search this huge database for specific
information. To state whether a web page is relevant to a search topic is a dilemma. This paper
proposes a crawler called as “PDD crawler” which will follow both a link based as well as a
content based approach. This crawler follows a completely new crawling strategy to compute
the relevance of the page. It analyses the content of the page based on the information contained
in various tags within the HTML source code and then computes the total weight of the page. The page with the highest weight, thus has the maximum content and highest relevance.
Data Sharing with ICPSR: Fueling the Cycle of Science through Discovery, Acce...ICPSR
Data Sharing with ICPSR was presented at IASSIST 2015 in Minneapolis, MN.
The learning objectives and content cover:
- Federal data sharing requirements and
other good reasons to share data
• Options for sharing data
• Protection of confidentiality when
sharing data
• Data discovery tools
• Online data exploration tools from ICPSR
Classification-based Retrieval Methods to Enhance Information Discovery on th...IJMIT JOURNAL
The widespread adoption of the World-Wide Web (the Web) has created challenges both for society as a whole and for the technology used to build and maintain the Web. The ongoing struggle of information retrieval systems is to wade through this vast pile of data and satisfy users by presenting them with information that most adequately it’s their needs. On a societal level, the Web is expanding faster than we can comprehend its implications or develop rules for its use. The ubiquitous use of the Web has raised important social concerns in the areas of privacy, censorship, and access to information. On a technical level, the novelty of the Web and the pace of its growth have created challenges not only in the development of new applications that realize the power of the Web, but also in the technology needed to scale applications to accommodate the resulting large data sets and heavy loads. This thesis presents searching algorithms and hierarchical classification techniques for increasing a search service's understanding of web queries. Existing search services rely solely on a query's occurrence in the document collection to locate relevant documents. They typically do not perform any task or topic-based analysis of queries using other available resources, and do not leverage changes in user query patterns over time. Provided within are a set of techniques and metrics for performing temporal analysis on query logs. Our log analyses are shown to be reasonable and informative, and can be used to detect changing trends and patterns in the query stream, thus providing valuable data to a search service.
Information technology and resources are an integral and indispensable part of the contemporary academic enterprise. In particular, technological advances have nurtured a new paradigm of data-intensive research. However, far too much of this activity still takes place in silos, to the detriment of open scholarly inquiry, integrity, and advancement. To counteract this tendency, the University of California Curation Center (UC3) has been developing and deploying a comprehensive suite of curation services that facilitate widespread data management, preservation, publication, sharing, and reuse. Through these services UC3 is engaging with new communities of use: in addition to its traditional stakeholders in cultural heritage memory organizations, e.g., libraries, museums, and archives, the UC3 service suite is now attracting significant adoption by research projects, laboratories, and individual faculty researchers. This webinar will present an introduction to five specific services – DMPTool, DataUp, EZID, Merritt, Web Archiving Service (WAS) – applicable to data curation throughout the scholarly lifecycle, two recent initiatives in collaboration with UC campuses, UC Berkeley Research Hub and UC San Francisco DataShare, and the ways in which they encourage and promote new communities of practice and greater transparency in scholarly research.
Integration of research literature and data (InFoLiS)Philipp Zumstein
Talk at CNI 2015 Spring Membership Meeting in Seattle on April 14th, 2015, see http://www.cni.org/events/membership-meetings/upcoming-meeting/spring-2015/
Abstract: The goal of the InFoLiS project is to connect research data and publications. Links between data and literature are created automatically by means of text mining and made available as Linked Open Data (LOD) for seamless integration into different retrieval systems. This enables scientists to directly access information about corresponding research data in a literature information system, and, vice versa, it is possible to directly find different interpretations and analyses in the literature of the same research data. In our talk, we will describe our methods for generating the links and give insight into the Linked Data infrastructure including the services we are currently building. Most importantly, we will detail how our solutions can be used by other institutions and invite all interested participants to discuss with us their ideas and thoughts on the requirements for these services to ensure broad interoperability with existing systems and infrastructures. InFoLiS is a joint project by the GESIS – Leibniz Institute for the Social Sciences, Cologne, Mannheim University Library, and Mannheim University supported by a grant from the DFG – German Research Foundation.
Meeting Federal Research Requirements for Data Management Plans, Public Acces...ICPSR
These slides cover evolving federal research requirements for sharing scientific data. Provided are updates on federal agency responses to the 2013 OSTP memo, guidance on data management plans, resources for data management and curation training for staff/researchers, and tips for evaluating public data-sharing services. ICPSR's public data-sharing service, openICPSR, is also presented. Recording of this presentation is here: https://www.youtube.com/watch?v=2_erMkASSv4&feature=youtu.be
Performance Evaluation of Query Processing Techniques in Information Retrievalidescitation
The first element of the search process is the query.
The user query being on an average restricted to two or three
keywords makes the query ambiguous to the search engine.
Given the user query, the goal of an Information Retrieval
[IR] system is to retrieve information which might be useful
or relevant to the information need of the user. Hence, the
query processing plays an important role in IR system.
The query processing can be divided into four categories
i.e. query expansion, query optimization, query classification and
query parsing. In this paper an attempt is made to evaluate the
performance of query processing algorithms in each of the
category. The evaluation was based on dataset as specified by
Forum for Information Retrieval [FIRE15]. The criteria used
for evaluation are precision and relative recall. The analysis is
based on the importance of each step in query processing. The
experimental results show that the significance of each step
in query processing and also the relevance of web semantics
and spelling correction in the user query.
WEB SEARCH ENGINE BASED SEMANTIC SIMILARITY MEASURE BETWEEN WORDS USING PATTE...cscpconf
Semantic Similarity measures plays an important role in information retrieval, natural language processing and various tasks on web such as relation extraction, community mining, document clustering, and automatic meta-data extraction. In this paper, we have proposed a Pattern Retrieval Algorithm [PRA] to compute the semantic similarity measure between the words by
combining both page count method and web snippets method. Four association measures are used to find semantic similarity between words in page count method using web search engines. We use a Sequential Minimal Optimization (SMO) support vector machines (SVM) to find the optimal combination of page counts-based similarity scores and top-ranking patterns from the web snippets method. The SVM is trained to classify synonymous word-pairs and nonsynonymous word-pairs. The proposed approach aims to improve the Correlation values,
Precision, Recall, and F-measures, compared to the existing methods. The proposed algorithm outperforms by 89.8 % of correlation value.
Research on Document Indexing in the Search Engines. The main theme of Informational retrieval is to send the exact response of a user for specific Query.
The information search retrieval is a very big process, to achieve this concept we need to develop an application with more effect and we have to use techniques like Document indexing, page ranking, clustering technique. Among all of these Document index is plays avital role while searching why since instead of searching hundreds of thousands of documents it will directly go to the particular index and will give the output here. Here our achievement mainly is indexing, the clear meaning of the indexing is storing an index is to optimize speed and performance in finding the appropriate/corresponding document for the user searched query.
My conclusion is the context based index approach is used in the query retrieval, this is mainly from the source document. Instead of searching every page on server, finding technically is better. Due to this we can save our time, we can reduce the burden of server.
An Advanced IR System of Relational Keyword Search Techniquepaperpublications3
Abstract: Now these days keyword search to relational data set becomes an area of research within the data base and Information Retrieval. There is no standard process of information retrieval, which will clearly show the accurate result also it shows keyword search with ranking. Execution time is retrieving of data is more in existing system. We propose a system for increasing performance of relational keyword search systems. In the proposed system we combine schema-based and graph-based approaches and propose a Relational Keyword Search System to overcome the mentioned disadvantages of existing systems and manage the information and user access the information very efficiently. Keyword Search with the ranking requires very low execution time. Execution time of retrieving information and file length during Information retrieval can be display using chart.Keywords: Keyword Search, Datasets, Information Retrieval Query Workloads, Schema-based Systems, Graph-based Systems, ranking, relational databases.
Title: An Advanced IR System of Relational Keyword Search Technique
Author: Dhananjay A. Gholap, Gumaste S. V
ISSN 2350-1022
International Journal of Recent Research in Mathematics Computer Science and Information Technology
Paper Publications
Context Driven Technique for Document ClassificationIDES Editor
In this paper we present an innovative hybrid Text
Classification (TC) system that bridges the gap between
statistical and context based techniques. Our algorithm
harnesses contextual information at two stages. First it extracts
a cohesive set of keywords for each category by using lexical
references, implicit context as derived from LSA and wordvicinity
driven semantics. And secondly, each document is
represented by a set of context rich features whose values are
derived by considering both lexical cohesion as well as the extent
of coverage of salient concepts via lexical chaining. After
keywords are extracted, a subset of the input documents is
apportioned as training set. Its members are assigned categories
based on their keyword representation. These labeled
documents are used to train binary SVM classifiers, one for
each category. The remaining documents are supplied to the
trained classifiers in the form of their context-enhanced feature
vectors. Each document is finally ascribed its appropriate
category by an SVM classifier.
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.
Enhanced Web Usage Mining Using Fuzzy Clustering and Collaborative Filtering ...inventionjournals
Information is overloaded in the Internet due to the unstable growth of information and it makes information search as complicate process. Recommendation System (RS) is the tool and largely used nowadays in many areas to generate interest items to users. With the development of e-commerce and information access, recommender systems have become a popular technique to prune large information spaces so that users are directed toward those items that best meet their needs and preferences. As the exponential explosion of various contents generated on the Web, Recommendation techniques have become increasingly indispensable. Web recommendation systems assist the users to get the exact information and facilitate the information search easier. Web recommendation is one of the techniques of web personalization, which recommends web pages or items to the user based on the previous browsing history. But the tremendous growth in the amount of the available information and the number of visitors to web sites in recent years places some key challenges for recommender system. The recent recommender systems stuck with producing high quality recommendation with large information, resulting unwanted item instead of targeted item or product, and performing many recommendations per second for millions of user and items. To avoid these challenges a new recommender system technologies are needed that can quickly produce high quality recommendation, even for a very large scale problems. To address these issues we use two recommender system process using fuzzy clustering and collaborative filtering algorithms. Fuzzy clustering is used to predict the items or product that will be accessed in the future based on the previous action of user browsers behavior. Collaborative filtering recommendation process is used to produce the user expects result from the result of fuzzy clustering and collection of Web Database data items. Using this new recommendation system, it results the user expected product or item with minimum time. This system reduces the result of unrelated and unwanted item to user and provides the results with user interested domain.
Majority of the computer or mobile phone enthusiasts make use of the web for searching
activity. Web search engines are used for the searching; The results that the search engines get
are provided to it by a software module known as the Web Crawler. The size of this web is
increasing round-the-clock. The principal problem is to search this huge database for specific
information. To state whether a web page is relevant to a search topic is a dilemma. This paper
proposes a crawler called as “PDD crawler” which will follow both a link based as well as a
content based approach. This crawler follows a completely new crawling strategy to compute
the relevance of the page. It analyses the content of the page based on the information contained
in various tags within the HTML source code and then computes the total weight of the page. The page with the highest weight, thus has the maximum content and highest relevance.
Optimization of Search Results with Duplicate Page Elimination using Usage DataIDES Editor
The performance and scalability of search engines
are greatly affected by the presence of enormous amount of
duplicate data on the World Wide Web. The flooded search
results containing a large number of identical or near identical
web pages affect the search efficiency and seek time of the users
to find the desired information within the search results. When
navigating through the results, the only information left behind
by the users is the trace through the pages they accessed. This
data is recorded in the query log files and usually referred to
as Web Usage Data. In this paper, a novel technique for
optimizing search efficiency by removing duplicate data from
search results is being proposed, which utilizes the usage data
stored in the query logs. The duplicate data detection is
performed by the proposed Duplicate Data Detection (D3)
algorithm, which works offline on the basis of favored user
queries found by pre-mining the logs with query clustering.
The proposed result optimization technique is supposed to
enhance the search engine efficiency and effectiveness to a large
scale.
An Improvised Fuzzy Preference Tree Of CRS For E-Services Using Incremental A...IJTET Journal
Abstract—Web mining is the amalgamation of information accumulated by traditional data mining methodologies and techniques with information collected over the World Wide Web. A Recommendation system is a profound application that comforts the user in a decision-making process, where they lack of personal experience to choose an item from the confound set of alternative products or services. The key challenge in the development of recommender system is to overcome the problems like single level recommendation and static recommendation, which are exists in the real world e-services. The goal is to achieve and enhance predicting algorithm to discover the frequent items, which are feasible to be purchasable. At this point, we examine the prior buying patterns of the customers and use the knowledge thus procured, to achieve an item set, which co-ordinates with the purchasing mentality of a particular set of customers. Potential recommendation is concerned as a link structure among the items within E-commerce website, which supports the new customers to find related products in a hurry. In Existing system, a fuzzy set consists of user preference and item features alone, so the recommendations to the customers are irrelevant and anonymous. In this paper, we suggest a recommendation technique, which practices the wild spreading and data sharing competency of a huge customer linkage and also this method follows a fuzzy tree- structured model, in which fuzzy set techniques are utilized to express user preferences and purchased items are in a clustered form to develop a user convenient recommendations. Here, an incremental association rule mining is employed to find interesting relation between variables in a large database.
Semantic Search of E-Learning Documents Using Ontology Based Systemijcnes
The keyword searching mechanism is traditionally used for information retrieval from Web based systems. However, this system fails to meet the requirements in Web searching of the expert knowledge base based on the popular semantic systems. Semantic search of E-learning documents based on ontology is increasingly adopted in information retrieval systems. Ontology based system simplifies the task of finding correct information on the Web by building a search system based on the meaning of keyword instead of the keyword itself. The major function of the ontology based system is the development of specification of conceptualization which enhances the connection between the information present in the Web pages with that of the background knowledge.The semantic gap existing between the keyword found in documents and those in query can be matched suitably using Ontology based system. This paper provides a detailed account of the semantic search of E-learning documents using ontology based system by making comparison between various ontology systems. Based on this comparison, this survey attempts to identify the possible directions for future research.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
Contact with Dawood Bhai Just call on +92322-6382012 and we'll help you. We'll solve all your problems within 12 to 24 hours and with 101% guarantee and with astrology systematic. If you want to take any personal or professional advice then also you can call us on +92322-6382012 , ONLINE LOVE PROBLEM & Other all types of Daily Life Problem's.Then CALL or WHATSAPP us on +92322-6382012 and Get all these problems solutions here by Amil Baba DAWOOD BANGALI
#vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore#blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #blackmagicforlove #blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #Amilbabainuk #amilbabainspain #amilbabaindubai #Amilbabainnorway #amilbabainkrachi #amilbabainlahore #amilbabaingujranwalan #amilbabainislamabad
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.