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A comparison of MCDM techniques for product recommendation

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dc.contributor.advisor Dr. Peter Haddawy (Chairperson) en_US
dc.contributor.advisor Prof. Phan Minh Dung (Member) en_US
dc.contributor.advisor Dr. Vatcharaporn Esichaikul (Member) en_US
dc.contributor.author Kanokporn Klangboonkrong en_US
dc.date.accessioned 2015-01-12T10:44:36Z
dc.date.available 2015-01-12T10:44:36Z
dc.date.issued 2001 en_US
dc.identifier.other AIT Thesis no.IM-01-06 en_US
dc.identifier.uri http://www.cs.ait.ac.th/xmlui/handle/123456789/522
dc.description 51 p. en_US
dc.description.abstract Recently, e-commerce has become popular and competition in the world of business-to-customer electronic commerce has intensified. It is more important than ever to attract business and retain customers. Personalization is involved for customizing some features of a product or service in order that the customer enjoy more convenience, low cost, or some other benefit. Many of the personalized Web sites use recommender system to help their customers find product to purchase. Computer-Assisted Self-Explication (CASE) is a personalization technology that uses knowledge about users and products to generate recommendations. The recommendations can be improved by utilizing MCDM techniques. In this study, mobile phone recommender system has been developed for implementing CASE and MCDM methods – SMART and AHP. The system users are required to evaluate the satisfaction of the performance of both SMART and AHP. A majority of them has considered that SMART provides higher quality recommendations than AHP. en_US
dc.description.sponsorship Royal Thai Government 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 E-commerce en_US
dc.subject MCDM techniques en_US
dc.title A comparison of MCDM techniques for product recommendation en_US
dc.type Thesis en_US

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