A Literature Review of Data Mining Techniques Used in Collaborative Filtering Recommender Systems

Ashrf Althbiti, Rayan Alshamrani, Xiaogang Ma
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Abstract

As a result of the ever-increasing number of available items in e-services, users are often overwhelmed. Therefore, it is essential to develop and apply algorithms to address the challenge of selection overload. Collaborative Filtering (CF) systems have been developed to help users to find what they might be interested in among a range of available selections. Moreover, CF systems have been widely discussed as an efficient approach to cope with the selection overload issue. This paper presents a literature review of the common CF techniques and data mining techniques used for CF.
协同过滤推荐系统中数据挖掘技术的文献综述
由于电子服务中可用项目的数量不断增加,用户常常不堪重负。因此,有必要开发和应用算法来解决选择过载的挑战。协作过滤(CF)系统的开发是为了帮助用户在一系列可用的选择中找到他们可能感兴趣的内容。此外,CF系统作为一种处理选择过载问题的有效方法已被广泛讨论。本文介绍了常用的CF技术和用于CF的数据挖掘技术的文献综述。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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