A Personalized Recommendation Model for Tourist Industry of Mobile E-commerce
Chen Zhigan · Journal of Hubei University of Technology · 2014
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 mobile 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.