Computational Intelligence Techniques Driven Intelligent Agents for Web Data Mining and Information Retrieval

Computational Intelligence Techniques Driven Intelligent Agents for Web Data Mining and Information Retrieval

Masoud Mohammadian (University of Canberra, Australia) and Ric Jentzsch (University of Canberra, Australia)
Copyright: © 2004 |Pages: 16
DOI: 10.4018/978-1-59140-194-0.ch002
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Abstract

The World Wide Web has added an abundance of data and information to the complexity of information for disseminators and users alike. With this complexity has come the problem of finding useful and relevant information. There is a need for improved and intelligent search and retrieval engines. Current search engines are primarily passive tools. To improve the results returned by searches, intelligent agents and other technology have the potential, when used with existing search and retrieval engines, to provide a more comprehensive search with an improved performance. This research provides the building blocks for integrating intelligent agents with current search engines. It shows how an intelligent system can be constructed to assist in better information filtering, gathering and retrieval. The research is unique in the way the intelligent agents are directed and in how computational intelligence techniques (such as evolutionary computing and fuzzy logic) and intelligent agents are combined to improve information filtering and retrieval. Fuzzy logic is used to access the performance of the system and provide evolutionary computing with the necessary information to carry out its search.

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