基于人工智能的营销数据精细化推送算法研究

Research on refined marketing data push algorithm based on artificial intelligence

为了提高电子商务系统中商品营销的推送精度,文中基于协同过滤与分布式系统等人工智能技术,提出适用于大多数电子商务系统的精细化推送算法。通过采集与分析用户的多种行为数据,利用协同过滤算法,分别实现了用户端与商品端的精细分类。并在此基础上,利用HDFS存储系统与MapReduce计算框架等分布式架构,同时调用机器学习等人工智能算法完成了营销数据的精细化推送。仿真结果表明,与传统推送算法相比,基于人工智能技术的推送算法具有更高的准确度与可靠性。

In order to improve the push accuracy of commodity marketing in e-commerce system,a refined push algorithm suitable for most e-commerce systems is proposed on the basis of artificial intelligence technologies such as collaborative filtering and distributed system.By collecting and analyzing the user's various behavior data,the fine classification of the user end and the commodity side is realized respectively by using the collaborative filtering algorithm.On this basis,the distributed architectures such as HDFS storage system and MapReduce computing framework is used,and artificial intelligence algorithms such as machine learning are called to complete the refined push of marketing data.The simulation results show that,in comparison with the traditional push algorithm,the push algorithm based on artificial intelligence technology has higher accuracy and reliability.