| Summary: | 碩士 === 輔仁大學 === 資訊管理學系 === 99 === With the ubiquity of the Internet and Web 2.0 technologies, the WWW has become the main source of information in the modern era. Wikipedia, one of the most famous collaborative projects on the Web, has become an extremely popular reference database for people seeking information. In this work, we aim at designing a SNA-based Wikipedia navigation interface (i.e., WNavi for short). Technically, we establish a preliminary topic network by applying the semantic relatedness analysis algorithm, i.e. Normalized Google Distance, in an internal link-based network. We then apply the k-clique of cohesive indicator to analyze the sub topics of the seed query and find out the best clustering results via the cosine measure. We conducted a user-task oriented evaluation study to computer science and knowledge management (KM) courses to confirm that the WNavi can help users browse KM related topics and execute tasks easily and efficiently. We further conducted a user-task oriented evaluation approach to confirm the implemented topic-based WNavi can help users browse a topic and accomplish complicated tasks easily and efficiently.
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