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An Intelligent E-commerce Recommender System Based on Web Mining

机译:基于Web挖掘的智能电子商务推荐系统

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The prosperity of e-commerce has changed the whole outlook of traditional trading behavior. More and more people are willing to conduct Internet shopping. However, the massive product information provided by the Internet Merchants causes the problem of information overload and this will reduces the customer’s satisfaction and interests. To overcome this problem, a recommender system based on web mining is proposed in this paper. The system utilizes web mining techniques to trace the customer’s shopping behavior and learn his/her up-to-date preferences adaptively. The experiments have been conducted to evaluate its recommender quality and the results show that the system can give sensible recommendations, and is able to help customers save enormous time for Internet shopping.
机译:电子商务的繁荣改变了传统贸易行为的整体面貌。越来越多的人愿意进行互联网购物。但是,Internet商户提供的大量产品信息会导致信息过载的问题,这将降低客户的满意度和兴趣。为了克服这个问题,本文提出了一种基于Web挖掘的推荐系统。该系统利用网络挖掘技术来追踪客户的购物行为,并自适应地了解其最新偏好。已经进行了实验以评估其推荐器质量,结果表明该系统可以给出明智的推荐,并且能够帮助客户节省大量的互联网购物时间。

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