Title: Products Recommendation in a B2C E-Commerce Using Fuzzy Logic
Brief Intro: One of the most important types of e-Commerce, classified according to the nature of the supplier and client, is Business to Consumer (B2C). In this type that consumer accesses the system of the supplier.Extensive research has been done investigating the role of trust in online purchase intention and behaviors, and the difference between initial and repeat trust formation and maintenance. On the other hand, much research on the area of recommendation systems has focused on improving recommendation accuracy and computational performances. Recommendation systems have achieved great success in generating accurate and ersonalized recommendations to their customers. The two important ways have been used nowadays which are data mining and live customer support. The motivation of this paper aims is to replace the data mining methods and human live support by an intelligent system that uses the fuzzy logic, that use rule base made by a human. In other words, this project aims to design an expert e-Commerce System (EECS) that helps the customer who browses a site to make the right decision, which means reducing the cost and time for the e-Commerce sites' owners.
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 the e-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 Keywords:E-commerce service, B2C, Fuzzy logic, Products Recommendation.
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Index Keywords:E-commerce service, B2C, Fuzzy logic, Products Recommendation.
You can also Subscribe to PROJECTSWORLDS by Email for more such projects and seminar.
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