Topic word selection for blogs by topic richness using web search result clustering
Jinhee Park, Sungwoo Lee, Hye-Wuk Jung, Jee-Hyong Lee · 2012
Blogs are one of popular services to publish and archive posts with personal opinions on the web. The topics of a blog can be used for classification, recommendation, opinion mining, and ranking, etc. In this paper, we propose a method for extracting important topic words from a blog. Our method selects topic words by measuring whether the blog includes rich content on the word. To measure the richness of a blog on candidate topic words, we compare web search results by the candidate words with the content of the blog. We used document clustering and cluster matching in order to compare them.