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BlogRank: ranking weblogs based on connectivity and similarity features

BlogRank: ranking weblogs based on connectivity and similarity features BLOGRANK: RANKING WEBLOGS BASED ON CONNECTIVITY AND SIMILARITY FEATURES Apostolos Kritikopoulos Athens University of Economics and Business Patision 76, Athens, Greece +30 6977687978 Martha Sideri Athens University of Economics and Business Patision 76, Athens, Greece +30 2108203149 Iraklis Varlamis Athens University of Economics and Business Patision 76, Athens, Greece +30 2108203160 [email protected] [email protected] [email protected] ABSTRACT A large part of the hidden web resides in weblog servers; traditional search engines perform poorly on blogs. We present a method for ranking weblogs utilizing both link graph and similarity, and based on an enhanced and weighted graph of weblogs capturing crucial weblog features. Rankings are then assigned using our algorithm, BlogRank, which is a modified version of PageRank. To validate our method we ran experiments on a weblog dataset, processed and adapted to our search engine: http://spiderwave.aueb.gr/Blogwave Our experiments suggest that our algorithm enhances the quality of returned results. the size of blogosphere doubles every 5.5 months [21] and today is 60 times bigger than 3 years ago. Although their structure is simple (text, images and links), and their content corresponds to personal beliefs, weblogs are an important information repository. Communities of weblogs can be related by type or topic, or http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

BlogRank: ranking weblogs based on connectivity and similarity features

Association for Computing Machinery — Oct 10, 2006

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References (24)

Datasource
Association for Computing Machinery
Copyright
Copyright © 2006 by ACM Inc.
ISBN
1-59593-505-3
doi
10.1145/1190183.1190193
Publisher site
See Article on Publisher Site

Abstract

BLOGRANK: RANKING WEBLOGS BASED ON CONNECTIVITY AND SIMILARITY FEATURES Apostolos Kritikopoulos Athens University of Economics and Business Patision 76, Athens, Greece +30 6977687978 Martha Sideri Athens University of Economics and Business Patision 76, Athens, Greece +30 2108203149 Iraklis Varlamis Athens University of Economics and Business Patision 76, Athens, Greece +30 2108203160 [email protected] [email protected] [email protected] ABSTRACT A large part of the hidden web resides in weblog servers; traditional search engines perform poorly on blogs. We present a method for ranking weblogs utilizing both link graph and similarity, and based on an enhanced and weighted graph of weblogs capturing crucial weblog features. Rankings are then assigned using our algorithm, BlogRank, which is a modified version of PageRank. To validate our method we ran experiments on a weblog dataset, processed and adapted to our search engine: http://spiderwave.aueb.gr/Blogwave Our experiments suggest that our algorithm enhances the quality of returned results. the size of blogosphere doubles every 5.5 months [21] and today is 60 times bigger than 3 years ago. Although their structure is simple (text, images and links), and their content corresponds to personal beliefs, weblogs are an important information repository. Communities of weblogs can be related by type or topic, or

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