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VI Brazilian Symposium on Neural Networks (SBRN'00)
Web Text Mining Using a Hybrid System
Rio de Janeiro, Brazil
January 22-January 25
ISBN: 0-7695-0856-1
Fernando Hideo Fukuda, Universidade Veiga de Almeida
Luiz Biondi Neto, Universidade Veiga de Almeida
Vincenzo de Roberto, Jr., Universidade Veiga de Almeida
Elias Restum Antonio, Universidade Veiga de Almeida
Luiz Chiganer, Universidade Veiga de Almeida
Emmanuel L.P. Passos, Pontif?cia Universidade Cat?lica do Rio de Janeiro
Marco Aurélio Pacheco, Pontif?cia Universidade Cat?lica do Rio de Janeiro
Jorge Valério, Universidade do Estado do Rio de Janeiro
This paper presents the research of artificial intelligence techniques based on KDD (Knowledge Discovery in Databases), KDT (Knowledge Discovery in Texts), Expert System and ANN (Artificial Neural Network) applied for evaluation and selection of textual documents found on WWW (World Wide Web). These techniques are useful because nowadays we have a explosive growth of the Web that provides a great amount of documents of many different subjects and the user needs to select these documents regarding to theirs particular interests. We considered the Web as a large data warehouse and applied the KDD fundaments and Text Mining procedures to develop these techniques. The techniques developed are language syntax independent because don't use NLP parser and provide an automatic text evaluation based on user profile interests acquired by examples using ANN. Finally, we developed a system using these techniques and compared with a similar commercial system available in the Web.
Citation:
Fernando Hideo Fukuda, Luiz Biondi Neto, Vincenzo de Roberto, Jr., Elias Restum Antonio, Luiz Chiganer, Emmanuel L.P. Passos, Marco Aurélio Pacheco, Jorge Valério, "Web Text Mining Using a Hybrid System," sbrn, pp.131, VI Brazilian Symposium on Neural Networks (SBRN'00), 2000
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