Jump to content United States-English
HP.com Home Products and Services Support and Drivers Solutions How to Buy
» Contact HP

HP Labs home

Technical reports

» 

HP Labs

» Research
» News and events
» Technical reports
» About HP Labs
» Careers @ HP Labs
» People
» Worldwide sites
» Downloads
Content starts here

 
Click here for full text: PDF

Clustering Short Texts using Wikipedia

Banerjee, Somnath; Ramanathan, Krishnan; Gupta, Ajay

HPL-2008-41

Keyword(s): Clustering, Wikipedia, Feed Reader

Abstract: Subscribers to the popular news or blog feeds (RSS/Atom) often face the problem of information overload as these feed sources usually deliver large number of items periodically. One solution to this problem could be clustering similar items in the feed reader to make the information more manageable for a user. Clustering items at the feed reader end is a challenging task as usually only a small part of the actual article is received through the feed. In this paper, we propose a method of improving the accuracy of clustering short texts by enriching their representation with additional features from Wikipedia. Empirical results indicate that this enriched representation of text items can substantially improve the clustering accuracy when compared to the conventional bag of words representation. Publication Info: Published and presented at SIGIR 2007, the 30th Annual International ACM SIGIR Conference, 23-27 July 2007, Amsterdam, Netherlands

2 Pages

Back to Index

»Technical Reports

» 2009
» 2008
» 2007
» 2006
» 2005
» 2004
» 2003
» 2002
» 2001
» 2000
» 1990 - 1999

Heritage Technical Reports

» Compaq & DEC Technical Reports
» Tandem Technical Reports
Printable version
Privacy statement Using this site means you accept its terms Feedback to HP Labs
© 2009 Hewlett-Packard Development Company, L.P.