Evolutionary intelligent agents for e-commerce: Generic preference detection with feature analysis [An article from: Electronic Commerce Research and Applications]

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Description - Evolutionary intelligent agents for e-commerce: Generic preference detection with feature analysis [An article from: Electronic Commerce Research and Applications]

This digital document is a journal article from Electronic Commerce Research and Applications, published by Elsevier in . The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

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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.





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