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Evolutionary Induction of Descriptive Rules in a Market Problem

By M. J. Del Jesus, P. González, F. Herrera and M. Mesonero

Abstract

Abstract. Nowadays, face to face contact with the client continues to be fundamental to the development of marketing acts. Trade fairs are, in this sense, a basic instrument in company marketing policies, especially in Industrial Marketing. Due to the elevated investment in term of both time and money it is necessary the automatic extraction of relevant and interesting information which helps to improve fair planning policies. In this paper, we analyse this problem and the kind of knowledge the user is interested in. We study the use of Soft Computing methodologies, specifically Fuzzy Logic and Genetic Algorithms, in the design of the Data Mining algorithms most proper to this problem, descriptive induction algorithms for subgroup discovery. Then we present an evolutionary model for the descriptive induction of fuzzy or crisp rules which describe subgroups. The proposal includes a GA in an iterative model which extracts rules while examples are left uncovered and the rules obtained surpass an specified confidence level

Topics: Key words, Data Mining algorithms, Fuzzy Logic, Genetic Algorithms, descriptive induction, Subgroup Discovery, Market problems
Year: 2013
OAI identifier: oai:CiteSeerX.psu:10.1.1.324.8779
Provided by: CiteSeerX
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