An intelligent news recommender agent for filtering and categorizing large volumes of text corpus
International Journal of Intelligent SystemsPublished 1 January 2004
Jung-Hsien Chiang, Yancheng Chen
Citations17
SJR quartileQ1
SJR score1.14
SNIP1.40
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TL;DR
An intelligent news recommender agent (INRA) is presented, which can be used to filter news articles as well as to recommend relevant news for individual user automatically, and the basic architecture of this approach is described.
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.
Keywords
Computer Science
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