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

Authors:
Shu-hsien Liao;Hsu-hui Ho;Feng-chich Yang
Affiliations:
Department of Management Sciences and Decision Making, Tamkang University, No. 151, Yingjuan Rd., Danshuei Jen, Taipei County, 251 Taipei, Taiwan, ROC;Department of Business Administration, Technology and Science Institute of Northern Taiwan, No. 2, Xueyuan Rd., Peitou, 112 Taipei, Taiwan, ROC;Department of Management Sciences and Decision Making, Tamkang University, No. 151, Yingjuan Rd., Danshuei Jen, Taipei County, 251 Taipei, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

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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.