The Journal of Machine Learning Research
Enhancing clustering blog documents by utilizing author/reader comments
ACM-SE 45 Proceedings of the 45th annual southeast regional conference
Expertise networks in online communities: structure and algorithms
Proceedings of the 16th international conference on World Wide Web
Ranking Weblogs by Analyzing Reading and Commenting Activities
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
User comments for news recommendation in forum-based social media
Information Sciences: an International Journal
Exploiting tag and word correlations for improved webpage clustering
SMUC '10 Proceedings of the 2nd international workshop on Search and mining user-generated contents
Preprocessing of Slovak Blog Articles for Clustering
WI-IAT '10 Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Comment-based multi-view clustering of web 2.0 items
Proceedings of the 23rd international conference on World wide web
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Web environment gives us an opportunity to take broader aspects of textual information into account, for example information about behavior of web users, global web trends or social interactions between users. In this paper we present and evaluate method suitable for enhancing blog clustering using the information hidden in web comments. We found out that blog clusters based on clustering of the commentators differ significantly from the content clusters. But according to the results of our experiments implicit relations between commentators can be used in addition to content clustering and improve the quality of content clusters.