WIT Press


A Fuzzy - Based Conceptual KDD Approach: The SaintEtiQ System

Price

Free (open access)

Paper DOI

10.2495/DATA000251

Volume

25

Pages

10

Published

2000

Size

1,095 kb

Author(s)

G. Raschia & N. Mouaddib

Abstract

A fuzzy-based conceptual KDD approach; The SaintEtiQ system G. Raschia & N. Mouaddib Institut de Recherche en Informatique de Nantes Universite de Nantes, France Abstract Knowledge Discovery in Databases (KDD) systems are basically designed to extract knowledge nuggets from data, i.e. a very precise and hidden knowledge, rather than to provide a global view on database. Moreover, knowledge represen- tation is often unintelligible for the user, such that a post-processing visualization step is necessary. Therefore, we propose a fuzzy-based summarization system named S AINTE- TlQ, providing different levels of summaries covering all the database. Summaries are output concepts of an incremental conceptual clustering algorithm performed on database records. Concept formation is the fundamental activity which struc- tures objects into a concise form of knowledge that can be efficiently used in the future. It includes the classification of new objects based on a subset of their pr

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