DATA MINING USING CONCEPTUAL CLUSTERING

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DATA MINING USING CONCEPTUAL CLUSTERING

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[pami.uwaterloo.ca]

by Khaled Hammouda

BibTeX

@MISC{Hammouda_datamining,
    author = {Khaled Hammouda},
    title = {DATA MINING USING CONCEPTUAL CLUSTERING },
    year = {}
}

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Abstract

The task of data mining is mainly concerned with the extraction of knowledge from large sets of data. Clustering techniques are usually used to find regular structures in data. Conceptual clustering is one technique that forms concepts out of data incrementally by subdividing groups into subclasses iteratively; thus building a hierarchy of concepts. This paper presents the use of conceptual clustering in data mining a large set of documents to find meaningful groupings among them. An incremental conceptual clustering technique based on probabilistic guidance function is implemented and tested against the data set for cohesion of the resulting cluster structure.

Keyphrases

data mining using conceptual clustering large set conceptual clustering probabilistic guidance function regular structure meaningful grouping data set incremental conceptual clustering technique data mining resulting cluster structure

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