KBCT: A Knowledge Extraction and Representation Tool for Fuzzy Logic Based Systems
KBCT: Una herramienta para adquisicion y representacion de conocimiento usando logica fuzzy
KBCT : Un logiciel pour l'acquisition et la représentation des connaissances utilisant la logique floue
Résumé
Este articulo presenta una herramienta multiplataforma y multilingue, con una interfaz grafica amigable, que facilita la extraccion y representacion de conocimiento en sistemas basados en logica fuzzy. Su objetivo es la construccion o el refinamiento de bases de conocimiento integrando conocimiento experto e inducido, realizandose todo el proceso bajo el control del experto. La expresividad semantica de la logica fuzzy, proxima al lenguaje natural usado por el experto, simplifica el proceso de adquisicion y aumenta la interpretabilidad. / This paper presents a user-friendly portable tool designed and developed in order to make easier knowledge extraction and representation for fuzzy logic based systems. KBCT is an open source software that could be executed under Linux or Windows Operating Systems. Main goal of KBCT is the generation or refinement of fuzzy knowledge bases with a particular interest of obtaining interpretable partitions and rules. The use of fuzzy logic simplifies the knowledge extraction process and increase interpretability of rules because of the fuzzy rule expression is closed to expert natural language. KBCT lets the user define expert variables and rules, but also provide induction capabilities for partitions and rules. Both types of knowledge, expert and induced, are integrated under the expert control. In addition to this, the user can check consistency and quality of rule base at any moment. A simplify option is implemented in order to allow the user to reduce the size of rule base. The main objective consists of ensuring interpretability, non redundancy and consistency of the knowledge base along the whole process.
Cette communication présente un logiciel multiplateforme et multilingue, avec une interface graphique développée, qui facilite l'extraction et la représentation de la connaissance sous la forme de systèmes basés sur la logique floue. Son objectif est la construction ou le raffinement de bases de connaissances qui intègrent de la connaissance experte comme de la connaissance induite. L'ensemble des procédures d'intégration est sous le contrôle de l'expert. L'utilisation de la logique floue, qui permet de modéliser le langage naturel, simplifie le processus d'acquisition et conduit à des systèmes hautement interprétables.