An intelligent news recommender agent for filtering and categorizing large volumes of text corpus

  • Authors:
  • Jung-Hsien Chiang;Yan-Cheng Chen

  • Affiliations:
  • Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan;Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan

  • Venue:
  • International Journal of Intelligent Systems
  • Year:
  • 2004

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Abstract

This article presents an intelligent news recommender agent (INRA), which can be used to filter news articles as well as to recommend relevant news for individual user automatically. Three specific objectives underlie the presentation of the intelligent news recommender agent in this study. The first is to describe the basic architecture of this approach, and the second is to show the design of the fuzzy hierarchical mixture of the expert model for text categorization. The third and more elaborate goal is to show that the proposed system is able to perform a news-recommending process. We show this approach with standard benchmark examples of the Reuters-21578 in order to verify the effectiveness of news recommending. © 2004 Wiley Periodicals, Inc.