Analyzing Topics of Blogs based on Wikipedia as a Multilingual Knowledge Source
Kensaku Makita, Daisuke Yokomoto, Hiroko Suzuki, Takehito Utsuro, Kawada Yasuhide, Tomohiro Fukuhara · 2011
Given a search query, most existing search engines simply return a ranked list of search results. However, it is often the case that those search result documents consist of a mixture of documents that are closely related to various sub-topics. This is also true for the case of our previously developed framework of retrieving blog posts which are closely related to a certain topic. In this paper, we propose a framework of categorizing blog posts according to their sub-topics, where, given a search query, those blog posts are automatically collected from the blogosphere. In our framework, the sub-topic of each blog post is identified by utilizing Wikipedia entries as a knowledge source and each Wikipedia entry title is considered as a sub-topic label. This paper especially presents examples of applying the proposed framework to Japanese / Korean / English blogospheres. Through those examples, we show that it becomes much easier to quickly overview the distribution of sub-topics over the whole blog posts collected with a certain search query.