Preference-Implicated Personal Data Model for Personalization Service Collaboration

Nowadays Personalized Service Collaboration (PSC) becomes more feasible due to the increasing availability of mobile application and web service. The semantic user model comprised of Resource Description Framework (RDF) plays a significant role in PSC. In practice, preferences within (personal data/model) often change with different time, context and dimension, which are dynamic information and contribute to PSC. Therefore, personal data model which represents time, context and dimension is increasingly required to provide a more complete user model view and more value-added user information to all relevant applications and services for PSC. In this paper, a novel personal data model based on RDF is proposed, which takes into account how to represent implicated and varied preference that corresponding to different time, context and dimension. The presented model aims to solve the issues that store, organize and represent unified personal data formally in service collaboration environment which harbors different kinds of personal date from various mobile applications and web services. Finally, the comparison and analysis between proposed personal data model and conventional user model are presented. The experiment result on real data set demonstrate the feasibility and effectiveness of proposed personal data model.