This paper presents a text categorization system, capable of analyzing HTML/text documents collected from the Web. The system is a component of a more extensive intelligent agent for adaptive information ltering on the Web. It is based on a hybrid case-based architecture, where two multilayer perceptrons are integrated into a case-based reasoner. An empirical evaluation of the system was performed by means of a con dence interval technique. The experimental results obtained are encouraging and support the choice of a hybrid case-based approach to text categorization.

Text Categorization in an Intelligent Agent for Filtering Information on the Web

Sciarrone F
2001-01-01

Abstract

This paper presents a text categorization system, capable of analyzing HTML/text documents collected from the Web. The system is a component of a more extensive intelligent agent for adaptive information ltering on the Web. It is based on a hybrid case-based architecture, where two multilayer perceptrons are integrated into a case-based reasoner. An empirical evaluation of the system was performed by means of a con dence interval technique. The experimental results obtained are encouraging and support the choice of a hybrid case-based approach to text categorization.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12606/4489
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
social impact