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Wikipedia-based Topic Clustering for Microblogs

Tan Xu and Douglas Oard

ASIST 2011 Annual Meeting
New Orleans, LA, October 9-12, 2011


Summary

Microblogging has become a primary channel by which people not only share information, but also search for information. However, microblog search results are most often displayed by simple criteria such as creation time or author. A review of the literature suggests that clustering by topic may be useful, but short posts offer limited scope for clustering using lexical evidence alone. This paper therefore presents an approach to topical clustering based on augmenting lexical evidence with the use of Wikipedia as an external source of evidence for topical similarity. The main idea is to link terms in microblog posts to Wikipedia pages and then to leverage Wikipedia's link structure to estimate semantic similarity, Results show statistically significant relative improvements of about 8% in cluster purity using a relatively small (7500-post, 5-topic) Twitter test collection. Linking terms in microblog posts to Wikipedia pages is also shown to offer a useful basis for cluster labeling.


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