基于协同过滤的个性化零食推荐微信公众平台设计与实现摘 要 随着社会经济的不断发展和居民消费水平的日益提高，消费者对于零食的需求数量越来越大。但市面上零食的种类很多，用户想要找到一款适合自己口味的零食，需要花费大量的时间和精力。如何快速高效地帮助用户找到自己喜欢的零食是一个问题。由此提出了个性化零食推荐的课题。本课题是设计实现一个基于微信公众平台的零食信息发布系统，每个用户都能将自己喜欢的零食信息发布到系统供其他用户参考，系统会根据用户对零食信息的一些反馈行为，采用协同过滤的算法，为用户个性化推荐零食信息。系统最终经过测试达到了需求标准，并成功的部署在微信公众平台和云服务器上。关键词： 微信公众平台；零食推荐；个性化推荐；协同过滤 Design and implementation of wechat public platform for personalized snack recommendation based on collaborative filteringABSTRACT With the continuous development of social economy and the increasing consumption level of residents, the demand for snacks is growing. But there are many kinds of snacks on the market. It takes a lot of time and energy for users to find a snack that suits their taste. How to help users find their favorite snacks quickly and efficiently is a problem. Therefore, the topic of personalized snack recommendation is put forward.This topic is to design and implement a snack information publishing system based on wechat public platform. Each user can publish their favorite snack information to the system for other users' reference. According to some feedback behaviors of users, the system will adopt collaborative filtering algorithm to personalized recommend snack information for users. Finally, the system has been tested to meet the requirements and successfully deployed on wechat public platform and cloud server.Key words：Wechat public platform; Snack recommendation; Personalized recommendation; Collaborative filtering目 录1. 绪论......................
