Modeling and Analysis of Demand for Personalized Portal

E-commerce1 has experienced great growth during the past two decades, which changes the consumption mode of consumers significantly. All researchers from institutions and enterprises want to identify and satisfy the personalized demand intelligently and conveniently by every possible means. In this paper, we proposed smart demand strategy based on holographic demand and model of transaction subject, which is applicable for the decentralized, disintermediated, intelligent e-commerce platform. User demands are classified from two aspects, which will improve the accuracy of demand obtaining. In addition, from standardized description of demand and full life cycle tracking of demand, the user demand will be identified comprehensively. Meanwhile, models of the user, including physical, preference, knowledge, digital label, and social attributes, are built based on his standard description and fragmented description from his interactive objects, which results in a holographic demander. Then, smart demand strategy, i.e. demand forecast and recommendation are proposed. Based on trigger point and demand attributes, the user demand will be updated in real time, which ensures the accuracy of demand accusation and recommendation. The relationship and help degree, based on the interactions within the cyberspace, are important references in filtering the recommendation.