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With the advent of e-commerce, there are hundreds of websites being deployed and each site offers millions of products. This means that a substantial amount of information is being provided by these websites which cause the problem of information overload and in turn results in reduced customer satisfaction and interest. Recommender systems are designed to overcome such problems. They are intelligent...
Accounting for the characteristics of E-commerce Website personal service and the features of users' and goods' similarities distribution, an E-commerce recommendation method based on clustering using genetic algorithm is designed. By using a composite weight matrix to integrate the situation of users purchasing, this method improves the result of clustering, and the result of clustering reflects...
The main purpose of this paper is to study the process of Web mining techniques and its application in e-commerce applications. This paper using the methods that introducing the concept of Web mining, and describing the process of Web data mining in detail: source data collection, data pre-processing, pattern discovery and pattern analysis, using a detailed case of Web mining application in e-commerce:...
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