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An adaptive model for customer targeting

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dc.contributor.advisor Dr. Vatcharaporn Esichaikul (Chairperson) en_US
dc.contributor.advisor Dr. Voratas Kachitvichyanukul (Member) en_US
dc.contributor.advisor Prof. Phan Minh Dung (Member) en_US
dc.contributor.author Theechat Chatvijit en_US
dc.date.accessioned 2015-01-12T10:45:46Z
dc.date.available 2015-01-12T10:45:46Z
dc.date.issued 2007 en_US
dc.identifier.other AIT Thesis no.IM-07-09 en_US
dc.identifier.uri http://www.cs.ait.ac.th/xmlui/handle/123456789/600
dc.description 123 p. en_US
dc.description.abstract Today, there are intensive competitions in marketing world. Marketers have to proactively run their businesses. Customer targeting is an important marketing decision that companies should pay attention to. Using information systems to support decision-making to shortlist potential buyers for certain products based on previous customer profiles or customer’s intrinsic values is one way in targeting customer. Therefore, because of the dynamic behavior of customers, there is a need to respond to such changes immediately. Artificial immune recognition system (AIRS) classifier using value difference metric (VDM) as a distance metric has been created to predict whether customer will buy an insurance policy. Adaptive algorithm was proposed in order to respond to such dynamic change of customers. It can partially retrain or update classifier without starting training from scratch. Its performance was compared to the original training and cascade-correlation network. Results show that it can work well on continuous attribute type. Furthermore, fractal dimension reduction and Grassberger-Procaccia’s algorithms were used together for attribute selection to gain predictive power of classifier. Moreover, difference between buyer and non-buyer in each attribute of profiles was also visualized to provide better understanding for marketers and to support marketing strategy in the future. en_US
dc.description.sponsorship RTG Fellowship en_US
dc.language.iso en en_US
dc.publisher Asian Institute of Technology en_US
dc.relation.ispartofseries AIT Publications; en_US
dc.subject Adaptive model en_US
dc.subject Artificial immune recognition system en_US
dc.subject Value difference metric en_US
dc.subject Customer targeting en_US
dc.title An adaptive model for customer targeting en_US
dc.type Thesis en_US

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