Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.elerap.2005.07.002
Title: Evolutionary intelligent agents for e-commerce: Generic preference detection with feature analysis
Authors: Guan, S.-U. 
Chan, T.K.
Zhu, F.
Keywords: E-commerce
Feature analysis
Generic attributes
Generic preference
Genetic algorithm
Issue Date: 2005
Source: 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
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