Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Bringing order to the Web: automatically categorizing search results
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
ACM SIGKDD Explorations Newsletter
A vector space model for automatic indexing
Communications of the ACM
Modern Information Retrieval
Data Mining and Knowledge Discovery with Evolutionary Algorithms
Data Mining and Knowledge Discovery with Evolutionary Algorithms
A Study of Approaches to Hypertext Categorization
Journal of Intelligent Information Systems
Information Retrieval on the World Wide Web
IEEE Internet Computing
A fuzzy system for the web page representation
Intelligent exploration of the web
A Web page classification system based on a genetic algorithm using tagged-terms as features
Expert Systems with Applications: An International Journal
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The Internet makes it possible to share and manipulate a vast quantity of information efficiently and effectively, but the rapid and chaotic growth experienced by the Net has generated a poorly organized environment that hinders the sharing and mining of useful data. The need for meaningful web-page classification techniques is therefore becoming an urgent issue. This paper describes a novel approach to web-page classification based on a fuzzy representation of web pages. A doublet representation that associates a weight with each of the most representative words of the web document so as to characterize its relevance in the document. This weight is derived by taking advantage of the characteristics of HTML language. Then a fuzzy-rule-based classifier is generated from a supervised learning process that uses a genetic algorithm to search for the minimum fuzzy-rule set that best covers the training examples. The proposed system has been demonstrated with two significantly different classes of web pages.