Web Structure Mining: Exploring Hyperlinks and Algorithms for Information Retrieval

Problem statement: A study on hyperlink analysis and the algorithms used for link analysis in the Web Information retrieval was done. Approach: This research was initiated because of the dependability of search engines for information retrieval in the web. Understand the web structure mining and det...

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Main Authors: Kumar, R., Singh, Ashutosh Kumar
Format: Journal Article
Published: Science Publication 2010
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/44448
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author Kumar, R.
Singh, Ashutosh Kumar
author_facet Kumar, R.
Singh, Ashutosh Kumar
author_sort Kumar, R.
building Curtin Institutional Repository
collection Online Access
description Problem statement: A study on hyperlink analysis and the algorithms used for link analysis in the Web Information retrieval was done. Approach: This research was initiated because of the dependability of search engines for information retrieval in the web. Understand the web structure mining and determine the importance of hyperlink in web information retrieval particularly using the Google Search engine. Hyperlink analysis was important methodology used by famous search engine Google to rank the pages. Results: The different algorithms used for link analysis like PageRank (PR), Weighted PageRank (WPR) and Hyperlink-Induced Topic Search (HITS) algorithms are discussed andcompared. PageRank algorithm was implemented using a Java program and the convergence of the PageRank values are shown in a chart form. Conclusion: This study was done basically to explore the link structure algorithms for ranking and compare those algorithms. The further research on this area will be problems facing PageRank algorithm and how to handle those problems.
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institution Curtin University Malaysia
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publishDate 2010
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spelling curtin-20.500.11937-444482017-01-30T15:14:13Z Web Structure Mining: Exploring Hyperlinks and Algorithms for Information Retrieval Kumar, R. Singh, Ashutosh Kumar web content weighted PageRank and HITS information retrieval web graph web structure PageRank hyperlink analysis Web mining Problem statement: A study on hyperlink analysis and the algorithms used for link analysis in the Web Information retrieval was done. Approach: This research was initiated because of the dependability of search engines for information retrieval in the web. Understand the web structure mining and determine the importance of hyperlink in web information retrieval particularly using the Google Search engine. Hyperlink analysis was important methodology used by famous search engine Google to rank the pages. Results: The different algorithms used for link analysis like PageRank (PR), Weighted PageRank (WPR) and Hyperlink-Induced Topic Search (HITS) algorithms are discussed andcompared. PageRank algorithm was implemented using a Java program and the convergence of the PageRank values are shown in a chart form. Conclusion: This study was done basically to explore the link structure algorithms for ranking and compare those algorithms. The further research on this area will be problems facing PageRank algorithm and how to handle those problems. 2010 Journal Article http://hdl.handle.net/20.500.11937/44448 Science Publication restricted
spellingShingle web content
weighted PageRank and HITS
information retrieval
web graph
web structure
PageRank
hyperlink analysis
Web mining
Kumar, R.
Singh, Ashutosh Kumar
Web Structure Mining: Exploring Hyperlinks and Algorithms for Information Retrieval
title Web Structure Mining: Exploring Hyperlinks and Algorithms for Information Retrieval
title_full Web Structure Mining: Exploring Hyperlinks and Algorithms for Information Retrieval
title_fullStr Web Structure Mining: Exploring Hyperlinks and Algorithms for Information Retrieval
title_full_unstemmed Web Structure Mining: Exploring Hyperlinks and Algorithms for Information Retrieval
title_short Web Structure Mining: Exploring Hyperlinks and Algorithms for Information Retrieval
title_sort web structure mining: exploring hyperlinks and algorithms for information retrieval
topic web content
weighted PageRank and HITS
information retrieval
web graph
web structure
PageRank
hyperlink analysis
Web mining
url http://hdl.handle.net/20.500.11937/44448