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A Fuzzy Logic intelligent agent for Information Extraction: Introducing a new Fuzzy Logic-based term weighting scheme

 

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Autor: Ropero Rodríguez, Jorge
Gómez Gutiérrez, Álvaro Ariel
Carrasco Muñoz, Alejandro
León de Mora, Carlos
Departamento: Universidad de Sevilla. Departamento de Tecnología Electrónica
Fecha: 2012
Publicado en: Expert Systems with Applications, 39 (4), 4567-4581.
Tipo de documento: Artículo
Resumen: In this paper, we propose a novel method for Information Extraction (IE) in a set of knowledge in order to answer to user consultations using natural language. The system is based on a Fuzzy Logic engine, which takes advantage of its flexibility for managing sets of accumulated knowledge. These sets may be built in hierarchic levels by a tree structure. The aim of this system is to design and implement an intelligent agent to manage any set of knowledge where information is abundant, vague or imprecise. The method was applied to the case of a major university web portal, University of Seville web portal, which contains a huge amount of information. Besides, we also propose a novel method for term weighting (TW). This method also is based on Fuzzy Logic, and replaces the classical TF–IDF method, usually used for TW, for its flexibility.
Cita: Ropero Rodríguez, J., Gómez Gutiérrez, Á.A., Carrasco Muñoz, A. y León de Mora, C. (2012). A Fuzzy Logic intelligent agent for Information Extraction: Introducing a new Fuzzy Logic-based term weighting scheme. Expert Systems with Applications, 39 (4), 4567-4581.
Tamaño: 1.740Mb
Formato: PDF

URI: http://hdl.handle.net/11441/61011

DOI: 10.1016/j.eswa.2011.10.009

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