EasyMall - An Interactive Virtual Shopping System

Nowadays, most e-Commerce platforms only provide users simple, 2D image-based and text-based interfaces to access the products. Such kind of tedious environment neither makes consumers enjoy fun during purchase, nor provides real-time personalized services according to different personal attributes and actual shopping behaviors of consumers on base of assisting both of buyers and vendors. In this paper a general framework of VRML-based virtual shopping mall (EasyMall) is presented. We stress comprehensively analyzing customers´ personal information, special demands, shopping behaviors and related historical records recorded by the Virtual shopping mall system, as well as the matching state of the consumer groups derived from the historical data of consumers´ shopping behaviors by applying data mining technology and then construct a marketing decision model for EasyMall droved by multi-factor. In the end, we present how to employ intelligent agent technology based on above marketing decision model to interactively provide consumers a good purchase guidance service.