基于旅游业移动电子商务的个性化推荐模型研究

摘要

通过建立个性化推荐模型，分析用户的网络访问行为，利用 KSP 算法以及 MIAR 算法获取关联规则，从海量的模糊数据中挖掘出个性化信息，修改移动网站的内容和结构以满足用户信息需求，并对用户的移动网络搜索数据进行智能挖掘，推荐相关的Top-N 旅游产品。同时针对以上研究设计旅游业移动电子商务个性化推荐模型，并对该模型流程进行分析，探讨后台移动数据库设计。%The paper established the PRM to analyse users′network access behaviors,obtained the association rules by KSP algorithm and MIAR algorithm ,which are used for relational user to dig out the personalized information from fuzzy data,modified the content and structure of mo-bile web site to meet the needs of users.Through establishing the PRM to carry out intelligent mining on searching data of mobile web,it then recommended Top-N related tourist products.A PRM for tourist industry of mobile e-commerce was then designed and analyzed.The paper finally discussed the design of the backstage of mobile database.