Abstract—Customer is the most important success factor for Business to Costumer (B2C) e-Commerce. There are two important ways have been used nowadays which are data mining and live customer support. These two ways are effective and reliable, but each one has its own problem. In this paper, an intelligent algorithm developed to replace these two methods with fuzzy rules. The fuzzy rules are generated from history data mining and an expert converts that data to rules. The solutions made through designing and implementing two databases, one for the fuzzy memberships and the other for thee-Commerce catalogue system. Then using PHP programming language, a script made to deal with these databases and link between them, then read data and process them using fuzzy logic to generate a recommendation to the customer.The algorithm is applied to three kinds of products, and the results are compared with Amazon site and give high agreement.
Index Terms—E-commerce service; B2C; Fuzzy logic, Products Recommendation
Cite: Salam A. Ismaeel, Karim M. Ahjebory and Oras I. Sulaiman, "Products Recommendation in a B2CE-Commerce Using Fuzzy Logic," International Journal of Computer Theory and Engineering vol. 1, no. 2, pp. 183-187, 2009.
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