| Summary: | 碩士 === 國立臺灣師範大學 === 資訊工程研究所 === 98 === In recent years, micro-blogging has been widely used by users. Micro-blog users usually share their interests, feelings, and information with their friends. The implicit topics covered in the micro-blog articles of a user usually show the user’ interests. Therefore, the goal of this study is to discover the implicit topics of micro-blog articles posted by micro-blog users to find users' interests. In this thesis, we first extract the important terms in a micro-blog article, and then Wikipedia is used to look up the corresponding categories of each term. For the terms which that can’t be found by Wikipedia directly, the Wikipedia online is linked to find the categories of their redirected terms. For each non-Wikipedia term, through the clustering analysis of related terms, the other terms in the same cluster with the non-Wikipedia term are used instead to get the corresponding categories. An evaluation method is proposed to measure the topic concentration degree of a micro-blog user. The results of experiments show that the proposed method can judge the topic concentration degree of micro-blog users with high precision. Moreover, the interest categories of micro-blog users discovered by the proposed method has high consistency with the results decided by the testers.
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