Ontology-based data mining approach implemented on exploring product and brand spectrum

doi:10.1016/j.eswa.2009.04.030

機構典藏 > College of Business and Management > Department of Management Sciences > Journal Article > Item 987654321/64927

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/64927

Title:	Ontology-based data mining approach implemented on exploring product and brand spectrum
Authors:	Liao, Shu-hsien;Ho, Hsu-hui;Yang, Feng-chich
Contributors:	淡江大學經營決策學系
Keywords:	Ontology;Data mining;Apriori algorithm;Clustering analysis;Product spectrum;Brand spectrum
Date:	2009-11
Issue Date:	2011-10-20 16:11:11 (UTC+8)
Publisher:	Kidlington: Pergamon
Abstract:	In physics, a spectrum is, the series of colored bands diffracted and arranged in the order of their respective wave lengths by the passage of white light through a prism or other diffracting medium. Outside of physics, a spectrum is a condition that is not limited to a specific set of values but can vary infinitely within a continuum. In commerce, an effective visualization tool, especially for stakeholders or managers, is a brand spectrum diagram highlighting where the company’s brands and products are situated compared to other competitors. This paper investigates the research issues on product and brand spectrum in the beverage product market of Taiwan, which proposes using the Apriori algorithm of association rules, and clustering analysis based on an ontology-based data mining approach, for mining customer and product knowledge from the database. Knowledge extracted from data-mining results is illustrated as knowledge patterns, rules, and maps in order to propose suggestions and solutions to beverage firms for possible product development, promotion, and marketing.
Relation:	Expert Systems with Applications 36(9), pp.11730-11744
DOI:	10.1016/j.eswa.2009.04.030
Appears in Collections:	[Department of Management Sciences] Journal Article

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