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Analyzing Customer Behavior Using Online Analytical Mining (OLAM)

Analyzing Customer Behavior Using Online Analytical Mining (OLAM)

Thanachart Ritbumroong
Copyright: © 2015 |Pages: 21
ISBN13: 9781466664777|ISBN10: 1466664770|EISBN13: 9781466664784
DOI: 10.4018/978-1-4666-6477-7.ch006
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MLA

Ritbumroong, Thanachart. "Analyzing Customer Behavior Using Online Analytical Mining (OLAM)." Integration of Data Mining in Business Intelligence Systems, edited by Ana Azevedo and Manuel Filipe Santos, IGI Global, 2015, pp. 98-118. https://doi.org/10.4018/978-1-4666-6477-7.ch006

APA

Ritbumroong, T. (2015). Analyzing Customer Behavior Using Online Analytical Mining (OLAM). In A. Azevedo & M. Santos (Eds.), Integration of Data Mining in Business Intelligence Systems (pp. 98-118). IGI Global. https://doi.org/10.4018/978-1-4666-6477-7.ch006

Chicago

Ritbumroong, Thanachart. "Analyzing Customer Behavior Using Online Analytical Mining (OLAM)." In Integration of Data Mining in Business Intelligence Systems, edited by Ana Azevedo and Manuel Filipe Santos, 98-118. Hershey, PA: IGI Global, 2015. https://doi.org/10.4018/978-1-4666-6477-7.ch006

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Abstract

Online Analytical Mining (OLAM) is an architecture integrating data mining into OLAP. With this integration, data mining algorithms can be performed with OLAP abilities. OLAM enables users to choose a particular portion of data and analyze them with data mining models. Previous studies have provided examples of OLAM applications with the motivation to improve technical performance. This chapter reviews the capabilities of OLAM and discusses the well-known concept encompassing the analysis of customer behavior. The underlying motivation of this chapter is to present the opportunities for the development of OLAM to support the customer behavior analysis. Three main directions of the advancement in OLAM are proposed for future research.

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