Clustering Short Texts using Wikipedia

Banerjee, Somnath ; Ramanathan, Krishnan ; Gupta, Ajay

HP Development Company

关键词: Clustering;    Wikipedia;    Feed Reader;   

RP-ID  :  HPL-2008-41

学科分类：计算机科学（综合）

美国|英语

来源: HP Labs

【 摘 要 】

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