期刊
INTERNATIONAL JOURNAL OF ELECTRONIC COMMERCE
卷 11, 期 2, 页码 11-34出版社
ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
DOI: 10.2753/JEC1086-4415110201
关键词
end-user programming; knowledge acquisition; knowledge-based recommenders; model-based diagnosis; personalization; recommender systems; testing recommender knowledge bases
The complexity of the product assortments offered by on-line selling platforms makes selection a challenging task. Customers differ in respect to expertise and product knowledge, but intelligent recommender systems offer personalized dialogues that support the product-selection process. This paper describes CWAdvisor, a domain-independent, knowledge-based recommender environment that provides users with consistently appropriate solutions, identifies additional selling opportunities, and explains solutions. The discussion uses examples from several application domains to show how model-based diagnosis, personalization, and intuitive knowledge-acquisition techniques support customer-oriented sales dialogues. Experience obtained in industrial projects is reported, and successfully deployed recommender applications are evaluated.
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