Linking topics of news and blogs with wikipedia for complementary navigation

  • Authors:

  • Yuki Sato;Daisuke Yokomoto;Hiroyuki Nakasaki;Mariko Kawaba;Takehito Utsuro;Tomohiro Fukuhara

  • Affiliations:

  • Graduate School of Systems and Information Engineering, University of Tsukuba, Tsukuba, Japan;Graduate School of Systems and Information Engineering, University of Tsukuba, Tsukuba, Japan;NTT Data Corporation, Tokyo, Japan;NTT Cyber Space Laboratories, NTT Corporation, Yokosuka, Kanagawa, Japan;Graduate School of Systems and Information Engineering, University of Tsukuba, Tsukuba, Japan;Center for Service Research, National Institute of Advanced Industrial Science and Technology, Tokyo, Japan

  • Venue:
  • BlogTalk'08/09 Proceedings of the 2008/2009 international conference on Social software: recent trends and developments in social software
  • Year:
  • 2008

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Abstract

We study complementary navigation of news and blog, where Wikipedia entries are utilized as fundamental knowledge source for linking news articles and blog feeds/posts. In the proposed framework, given a topic as the title of a Wikipedia entry, its Wikipedia entry body text is analyzed as fundamental knowledge source for the given topic, and terms strongly related to the given topic are extracted. Those terms are then used for ranking news articles and blog posts. In the scenario of complementary navigation from a news article to closely related blog posts, Japanese Wikipedia entries are ranked according to the number of strongly related terms shared by the given news article and each Wikipedia entry. Then, top ranked 10 entries are regarded as indices for further retrieving closely related blog posts. The retrieved blog posts are finally ranked all together. The retrieved blog posts are then shown to users as blogs of personal opinions and experiences that are closely related to the given news article. In our preliminary evaluation, through an interface for manually selecting relevant Wikipedia entries, the rate of successfully retrieving relevant blog posts improved.