A Method for Identifying Topic-changing Articles in Discussion-type Newsgroups within the Intelligent Network News Reader HISHO

We are developing an Intelligent Network News Reader for discussion-type newsgroups. It can automatically extract and present articles related to the focus article, which is the article selected by the user. we can automatically retrieve the stream of the discussion as a series of articles by referring to the "References " information that is collected to facilitate the gathering of related articles. To present a suitable number of articles to the user, however, a news reader must be able to gather more related articles when the number of articles is too small and must be able to prune articles which are only weakly related, namely, articles whose central topic is different from previous one when the number of articles is too large. In this paper, therefore, we present a new method for identifying articles which change the topic, a method that uses only clue words and the frequency of strings and does not use dictionaries. An evaluation of our method on real network newsgroups has show..