电子商务推荐系统中的推荐技术研究

Ming Chen
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引用次数: 4

摘要

如今,电子商务公司之间相互竞争,而赢得竞争的一个解决方案是了解客户的消费偏好,从而建立更好的充分的个性化服务,以满足客户。在此背景下,为了使电子商务系统根据用户的兴趣主动向用户推荐产品,在人工智能衍生的代理技术的支持下,电子商务推荐系统应运而生并逐步发展起来。本文简要介绍了电子商务推荐系统的概念和功能。对推荐系统中常用的过滤算法进行了比较,并介绍了几种主要的过滤算法。给出了上述技术建议的优缺点。最后,指出了电子商务推荐方法中几个有待研究的问题和方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on recommender technology in E-commerce recommendation system
E-commerce companies compete with each other nowadays, and one solution to winning the competition is to get knowledge about customers' consuming preferences so as to establish better adequate personalized services to satisfy the customers. On this surrounding, to make E-commerce system actively recommend products to users according to their interests, the E-commerce recommendation system is arrived and gradually develops which supported by the agent technologies derived from Artificial Intelligence. In the paper, concepts and functions of E-commerce recommender systems are briefly introduced. The algorithms using in recommendation systems are comparing with each other, and several main filtering algorithms are described. Advantages and disadvantages of these above mentioned technical recommendations were provided. At last, point out several open research problems and directions in the E-commerce recommendation methods.
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