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Evolutionary intelligent agents for e-commerce: Generic preference detection with feature analysis
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DOI：10.1016/j.elerap.2005.07.002.png)
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摘要
En 中文
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. (c) 2005 Elsevier B.V. All rights reserved.
Keyword:
generic preference
e-commerce
generic attributes
feature analysis
genetic algorithm
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