Topic Detection from Blog Documents Using Users´ Interests

In this paper, we describe a method to detect topic words from blog documents. We define "topic words" as words frequently used by people who share the same interests. In this method, each blogger’s interests are extracted from each blog site, and interest similarities between bloggers are calculated. Unusual words that are used by bloggers who have a high level of similarity are then extracted as topic words. We evaluated the precision of this method using blog documents, and the results show that the proposed method is superior (by 4.4 %) to the traditional TF-IDF method in terms of precision.