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Title: Evolutionary intelligent agents for e-commerce: Generic preference detection with feature analysis
Authors: Guan, SU
Chan, TK
Zhu, F
Keywords: Generic preference
Generic attributes
Feature analysis
Genetic algorithm
Publication Date: 2005
Publisher: Elsevier
Citation: Electronic Commerce and Research Applications. 4 (4) 377-394
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.
ISSN: 1567-4223
Appears in Collections:Electronic and Computer Engineering
Dept of Electronic and Computer Engineering Research Papers

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