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

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.

[1]  Raymond J. Mooney and Paul N. Bennett and Loriene Roy,et al.  Book Recommending Using Text Categorization with Extracted Information , 1998 .

[2]  G. Soda,et al.  Data Categorization Using Decision Trellises , 1999, IEEE Trans. Knowl. Data Eng..

[3]  Tom M. Mitchell,et al.  Improving Text Classification by Shrinkage in a Hierarchy of Classes , 1998, ICML.

[4]  Padmini Srinivasan,et al.  Hierarchical neural networks for text categorization , 1999, SIGIR 1999.

[5]  Yoram Singer,et al.  Context-sensitive learning methods for text categorization , 1996, SIGIR '96.

[6]  Stephen Pollock,et al.  A rule-based message filtering system , 1988, TOIS.

[7]  Wai Lam Intelligent content‐based document delivery via automatic filtering profile generation , 1999 .

[8]  Malik Yousef,et al.  Document classification on neural networks using only positive examples (poster session) , 2000, SIGIR '00.

[9]  Michael I. Jordan,et al.  Hierarchical Mixtures of Experts and the EM Algorithm , 1994, Neural Computation.

[10]  Douglas B. Terry,et al.  Using collaborative filtering to weave an information tapestry , 1992, CACM.

[11]  Thomas W. Malone,et al.  Intelligent Information Sharing Systems , 1986 .

[12]  Naohiro Ishii,et al.  Content-based Collaborative Information Filtering: Actively Learning to Classify and Recommend Documents , 1998, CIA.

[13]  Ahmad M. Ahmad Wasfi Collecting user access patterns for building user profiles and collaborative filtering , 1998, IUI '99.

[14]  Mark Claypool,et al.  Combining Content-Based and Collaborative Filters in an Online Newspaper , 1999, SIGIR 1999.

[15]  Hwee Tou Ng,et al.  Feature selection, perceptron learning, and a usability case study for text categorization , 1997, SIGIR '97.

[16]  Yoav Shoham,et al.  Fab: content-based, collaborative recommendation , 1997, CACM.

[17]  Sholom M. Weiss,et al.  Automated learning of decision rules for text categorization , 1994, TOIS.

[18]  Yiming Yang,et al.  An Evaluation of Statistical Approaches to Text Categorization , 1999, Information Retrieval.

[19]  Daphne Koller,et al.  Hierarchically Classifying Documents Using Very Few Words , 1997, ICML.

[20]  Paul Resnick,et al.  Recommender systems , 1997, CACM.

[21]  Pattie Maes,et al.  Social information filtering: algorithms for automating “word of mouth” , 1995, CHI '95.

[22]  Jung-Hsien Chiang,et al.  Comparison of crisp and fuzzy character neural networks in handwritten word recognition , 1995, IEEE Trans. Fuzzy Syst..

[23]  Bradley N. Miller,et al.  Using filtering agents to improve prediction quality in the GroupLens research collaborative filtering system , 1998, CSCW '98.

[24]  Michael J. Pazzani,et al.  Learning Collaborative Information Filters , 1998, ICML.

[25]  Thorsten Joachims,et al.  Text Categorization with Support Vector Machines: Learning with Many Relevant Features , 1998, ECML.

[26]  David E. Johnson,et al.  Maximizing Text-Mining Performance , 1999 .