Modeling and evaluation of knowledge discovery in wholesale and retail industry

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dc.contributor.advisor Lingras, Pawan
dc.creator Mizuhara, Tokuyo 2011-06-09T17:18:47Z 2011-06-09T17:18:47Z 2009
dc.identifier.other HF5429.15 M59 2009
dc.description x, 168 leaves : ill. ; 29 cm. en_CA
dc.description Includes abstract.
dc.description Includes bibliographical references (leaves 163-168).
dc.description.abstract This thesis demonstrates an enterprise-wide Knowledge Discovery in Databases (KDD) process CRISP for wholesale and retail industry, which can facilitate business decision-making processes and improve corporate profits. While part of the KDD process described here is well documented, the modeling and evaluations used in the commercial products is not reported in literature. Hence, the focus of this thesis is on the development and evaluation of models used in the knowledge discovery. Description of the underlying models will help the decision makers better understand the quality and limitations of the KDD process. The usefulness of KDD process CRISP is illustrated for two companies, i.e. a multinational retailer and a small chain of specialty grocery stores. The detailed steps highlight business understanding, data exploration, data preparation. data modeling, results evaluation, and interpretation. The methodologies applied in this thesis include prediction, clustering and association to discover knowledge about products/suppliers, consumers, and business units. en_CA
dc.description.provenance Submitted by Dianne MacPhee ( on 2011-06-09T17:18:47Z No. of bitstreams: 0 en
dc.description.provenance Made available in DSpace on 2011-06-09T17:18:47Z (GMT). No. of bitstreams: 0 Previous issue date: 2009 en
dc.language.iso en en_CA
dc.publisher Halifax, N.S. : Saint Mary's University en_CA
dc.subject.lcc HF5429.15
dc.subject.lcsh Data mining
dc.subject.lcsh Retail trade
dc.subject.lcsh Wholesale trade
dc.title Modeling and evaluation of knowledge discovery in wholesale and retail industry en_CA
dc.type Text en_CA Master of Science in Applied Science Masters Mathematics and Computing Science Saint Mary's University (Halifax, N.S.)
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