Extraction of Classification Rules in Databases through Metaheuristic Procedures Based on GRASP

Abstract:

The process of knowledge management in the several areas of society requires constant attention to the multiplicity of decisions to be made about the activities in organizations that constitute them. To make these decisions one should be cautious in relying only on personal knowledge acquired through professional experience, since the whole process based on this method would be slow, expensive and highly subjective. To assist in this management, it is necessary to use mathematical tools that fulfill the purpose of extracting knowledge from database. This article proposes the application of Greedy Randomized Adaptive Search Procedure (GRASP) as Data Mining (DM) tool within the process called Knowledge Discovery in Databases (KDD) for the task of extracting classification rules in databases.

• Periodical: Advanced Materials Research (Volumes 945-949)
• Pages: 3369-3375
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.945-949.3369
• Online since: June 2014
• Authors: Genival Pavanelli*, Maria Teresinha Arns Steiner, Anderson Roges Teixeira Góes, Alessandra Memari Pavanelli, Deise Maria Bertholdi Costa
• Keywords: Data Mining (DM), Greedy Randomized Adaptive Search Procedure, Rules Extraction

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