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Abstract
Data mining is the discovery of patterns that may exist implicitly in a large database. In this paper, we study a combined model for cluster discovery. We build a multi dimensional data model (MDDM) and transform tuple of database into vector of MDDM then we use Kohonen's self-organizing algorithm to discover the potential clusters and Genetic Algorithm (GA) for validating these clusters. By combining MDDM with GA, we propose a heuristic for improving the efficiency of cluster discovery.
Issue: Vol 2 No 2&3 (1999)
Page No.: 62-73
Published: Mar 31, 1999
Section: Article
DOI: https://doi.org/10.32508/stdj.v2i2&3.3620
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