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http://dx.doi.org/10.7236/JIWIT.2011.11.6.063

Discovering News Keyword Associations Using Association Rule Mining  

Kim, Han-Joon (서울시립대학교 전자전기컴퓨터공학부)
Chang, Jae-Young (한성대학교 컴퓨터공학과)
Publication Information
The Journal of the Institute of Internet, Broadcasting and Communication / v.11, no.6, 2011 , pp. 63-71 More about this Journal
Abstract
The current Web portal sites provide significant keywords with high popularity or importance; specifically, user-friendly services such as tag clouds and associated word search are provided. However, in general, since news articles are classified only with their date and categories, it is not easy for users to find other articles related to some articles while reading news articles classified with categories. And the conventional associated keyword service has not satisfied users sufficiently because it depends only upon user queries. This paper proposes a way of searching news articles by utilizing the keywords tightly associated with users' queries. Basically, the proposed method discovers a set of keyword association patterns by using the association rule mining technique that extracts association patterns for keywords by focusing upon sentences containing some keywords. The method enables users to navigate the space of associated keywords hidden in large news articles.
Keywords
Association Rule Mining; Keyword Analysis; Data Mining; Information Retrieval;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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