Soft Computing Techniques for Product Filtering in E-commerce Personalisation: A Comparison Study

被引：0

作者：

Wong, Kok Wai ^{[1
]}

Fung, Chun Che ^{[1
]}

Eren, Halit ^{[2
]}

机构：

[1] Murdoch Univ, Sch Informat Technol, Murdoch, WA 6150, Australia

[2] Curtin Univ Technol, Sch Elect & Comp Engn, Perth, WA 6845, Australia

来源：

2009 3RD IEEE INTERNATIONAL CONFERENCE ON DIGITAL ECOSYSTEMS AND TECHNOLOGIES | 2009年

关键词：

Product Filtering; E-commerce; Soft Computing; Artificial Neural Networks; Fuzzy Systems;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we compare two soft computing methods used for product filtering in web personalisation for E-commerce. Due to the diversely behaving nature, and the complexity to model the customers' behaviour using market research methodologies, it is difficult to build a universal model relating the purchasing behaviour mathematical in E-commerce. For this reason, soft computing techniques may be considered as more appropriate in such case. In this study, we have investigated and compared an artificial neural network (ANN) and a fuzzy based method on a particular simulated data set. Initial results indicated that the fuzzy method could be a better choice as there are means to improve the results and human users may understand and modify the model.

引用

页码：593 / +

页数：2

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