Design of a Self-Learning Recommendation System with Integration of Personal Cloud Storage Technology

Abstract

The success of mobile commerce adoption hinges on their ability to cover user shopping behaviors and attract consumer interest. In addition to anytime and anywhere paradigm, mobile commerce applications required to be flexible and personalized. In this work, we develop a mobile commerce system which introduces the Personal and Entry Level Storage (PELS) technology and its integration and applications with other e-commerce modules such as POS and vendor system. The benefits of the proposed system include: (1) Against advertising harassment, (2) Expanding the ability of personal cloud storage, (3) Analyzing the shopping trend for consumers and (4) Explicit shopping recommendation and shopping discount message delivery. A system scenario process is depicted to provide a generic paradigm for consumers and vendors. Furthermore, in terms of this innovative personalized e-commerce system, we discuss three managerial implications for future research and practice.