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|Title:||Evolutionary intelligent agents for e-commerce: Generic preference detection with feature analysis||Authors:||Guan, S.-U.
|Issue Date:||2005||Citation:||Guan, S.-U., Chan, T.K., Zhu, F. (2005). Evolutionary intelligent agents for e-commerce: Generic preference detection with feature analysis. Electronic Commerce Research and Applications 4 (4) : 377-394. ScholarBank@NUS Repository. https://doi.org/10.1016/j.elerap.2005.07.002||Abstract:||Product recommendation and preference tracking systems have been adopted extensively in e-commerce businesses. However, the heterogeneity of product attributes results in undesired impediment for an efficient yet personalized e-commerce product brokering. Amid the assortment of product attributes, there are some intrinsic generic attributes having significant relation to a customer's generic preference. This paper proposes a novel approach in the detection of generic product attributes through feature analysis. The objective is to provide an insight to the understanding of customers' generic preference. Furthermore, a genetic algorithm is used to find the suitable feature weight set, hence reducing the rate of misclassification. A prototype has been implemented and the experimental results are promising. © 2005 Elsevier B.V. All rights reserved.||Source Title:||Electronic Commerce Research and Applications||URI:||http://scholarbank.nus.edu.sg/handle/10635/55930||ISSN:||15674223||DOI:||10.1016/j.elerap.2005.07.002|
|Appears in Collections:||Staff Publications|
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