Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/1125
Title: | Evolutionary intelligent agents for e-commerce: Generic preference detection with feature analysis |
Authors: | Guan, SU Chan, TK Zhu, F |
Keywords: | Generic preference;e-Commerce;Generic attributes;Feature analysis;Genetic algorithm |
Issue 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. |
URI: | http://bura.brunel.ac.uk/handle/2438/1125 |
ISSN: | 1567-4223 |
Appears in Collections: | Electronic and Electrical Engineering Dept of Electronic and Electrical Engineering Research Papers |
Files in This Item:
File | Description | Size | Format | |
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ECRA 260 Evolutionary Intelligent Agents for e-Commerce - Generic Preference Detection with Feature Analysis.pdf | 661.66 kB | Adobe PDF | View/Open |
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