Context-Based Data Tailoring for Mobile Users

Independent, heterogeneous, distributed, sometimes transient and mobile data sources produce an enormous amount of information that should be semantically integrated and filtered, or, as we say, tailored, based on the users’ interests and context. Since both the user and the data sources may be mobile, and communication unreliable, caching the information on the user device is certainly useful. Thus, we propose to exploit knowledge about the user, the adopted device, and the environment altogether called context to the end of information tailoring. The key is context-aware data design where the notion of context must be formally defined, together with its role within the process of information tailoring. This paper presents a context model, called Context Dimension Tree, which plays a fundamental role in tailoring the information domain model within the framework of the Context-ADDICT project, currently under development at Politecnico di Milano. To conclude, we report on other context models, along with a brief comment on their relevant features.