Providing personalized services for mobile commerce (m-commerce) can improve user satisfaction and merchant profits, which are important to the success of m-commerce. This paper proposes a Bayesian network (BN)-based framework for personalization in m-commerce applications. The framework helps to identify the target mobile users and to deliver relevant information to them at the right time and in the right way. Under the framework, a personalization model is generated using a new method and the model is implemented in an m-commerce application for the food industry. The new method is based on function dependencies of a relational database and rough set operations. The framework can be applied to other industries such as movies, CDs, books, hotel booking, flight booking, and all manner of shopping settings.
Liao, S., Li, Q., & Xu, D. (2005). A Bayesian Network-Based Framework for Personalization in Mobile Commerce Applications. Communications of the Association for Information Systems, 15, pp-pp. https://doi.org/10.17705/1CAIS.01528