MASACAD: A Multiagent-Based Approach to Information Customization

Authors:
Mohamed Salah Hamdi
Affiliations:
University of Qatar
Venue:
IEEE Intelligent Systems
Year:
2006

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Abstract

The huge amount of content available on the World Wide Web raises important questions over its effective use. To cope with such environments, the promise of information customization systems is becoming highly attractive. MASACAD is a multiagent system that learns to advise students by mining the Web. It approaches information customization using a multiagent paradigm in combination with aspects from machine learning, user modeling, and Web mining.This article is part of a special issue on AI, Agents, and the Web.