【摘要】 随着互联网技术的不断进步,电子商务得到了快速的发展,通过网络购物平台消费已经逐渐成为一种主要消费渠道。在互联网大发展的背景下,庞大的数据量带来便利的同时又为消费者的消费选择造成了困扰。如何从这些数量庞大的商品信息中快速准确地挖掘出消费者所感兴趣的商品成为当前电子商务领域研究的一大热点。随着人工智能技术的不断进步和突破,电子商务企业对消费者的消费倾向及消费能力等作出预测,以实现精准的商品推荐。为进一步了解国内外对消费者行为预测及精准推荐算法的研究,笔者特查阅相关的文献资料,对文献资料进行了分析总结,撰写文献综述,旨在为消费者行为算法的研究提供理论指导。更多还原

【Abstract】 With the continuous advancement of Internet technology, e-commerce has developed rapidly, and consumption through online shopping platforms has gradually become a major consumer channel. In the context of the great development of the Internet, the huge amount of data brings convenience and at the same time causes confusion for consumers’ consumption choices. How to quickly and accurately dig out the products that consumers are interested in from these huge amounts of commodity information has become a hot spot in the current e-commerce field. With the continuous advancement and breakthrough of artificial intelligence technology, e-commerce companies make predictions on consumers’ consumption propensity and consumption power to achieve accurate product recommendation. In order to further understand the domestic and foreign research on consumer behavior prediction and accurate recommendation algorithm, the author specially checked and read the relevant literature, analyzed and summarized the literature, and wrote literature review, in order to provide theoretical guidance for the research of consumer behavior algorithm.更多还原