An Intelligent News Recommender Agent for Filtering and Categorizing Large Volumes of Text Corpus

Jung-Hsien Chiang, Yan Cheng Chen

Research output: Contribution to journalArticle

17 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)201-216
Number of pages16
JournalInternational Journal of Intelligent Systems
Volume19
Issue number3
DOIs
Publication statusPublished - 2004 Jan 1

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Filtering
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Filter
Benchmark
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Corpus
Text
Model
Presentation
Architecture
Design
Standards

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Human-Computer Interaction
  • Artificial Intelligence

Cite this

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An Intelligent News Recommender Agent for Filtering and Categorizing Large Volumes of Text Corpus. / Chiang, Jung-Hsien; Chen, Yan Cheng.

In: International Journal of Intelligent Systems, Vol. 19, No. 3, 01.01.2004, p. 201-216.

Research output: Contribution to journalArticle

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