University of Muenster
This paper outlines a model that enriches the user experience of using Mobile Value Added Services (MVAS). Specifically the location based data services segment of MVAS is taken into consideration for experimentation purposes. The model describes a method to personalize user information related to various data services offered to the user on a mobile phone. The authors' model is trained to predict the services required by specific set of users at a given time and location. In addition to prediction the algorithm ranks services to personalize the user experience; anticipating user's need and preferences. The model delineated is an intelligent model that evolves with usage of the application. The user interacts via query-alert and feedback.