Using Contextual Information for Personalized Recommendation in Mobile Commerce

The rapid development of wireless technology and mobile devices stimulates the emergence of mobile commerce, which extends the nature and scope of traditional e-commerce, enabling users to access information whenever and whatever they want. However, the exponentially increase of resources makes it difficult for users to find the appropriate information. In addition, the certain limitations of mobile devices influence the performance of mobile commerce. Personalized recommendation provides an approach to solve information overload and improve service performance. Traditional recommending approaches are content-based recommendation and collaborative recommendation, mainly considering the user and the items. But this is insufficient for m-commerce. Contextual information plays an indispensable role in the efficient and precise recommendation in mobile commerce. In this paper, we introduce user context and context-aware service, and then propose a personalized recommendation framework based on contextual information and analyze it in detail. Finally, the advantages of the framework are pointed out.