Soft computing techniques for product filtering in E-commerce personalisation: A comparison study
Wong, K.W., Fung, C.C. and Eren, H. (2009) Soft computing techniques for product filtering in E-commerce personalisation: A comparison study. In: 3rd IEEE International Conference on Digital Ecosystems and Technologies (DEST '09), 1-3 June 2009, Istanbul, Turkey pp. 402-406.
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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.
|Publication Type:||Conference Paper|
|Murdoch Affiliation:||School of Information Technology|
|Copyright:||(c) Copyright 2009 IEEE|
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