Users’ preferences have traditionally been exploited in query personalization
to better serve their information needs. With the emerging ubiquitous
computing technologies, users will be situated in an Ambient Intelligent (AmI)
environment, where users’ database access will not occur at a single location in a
single context as in the traditional stationary desktop computing, but rather span a
multitude of contexts like office, home, hotel, plane, etc. To deliver personalized
query answering in this environment, the need for context-aware query preferences
arises accordingly. In this paper, we propose a knowledge-based contextaware
query preference model, which can cater for both pull and push queries.
We analyze requirements and challenges that AmI poses upon such a model and
discuss the interpretation of the model in the domain of relational databases. We
implant the model on top of a traditional DBMS to demonstrate the applicability
and feasibility of our approach.
|Name||CTIT Technical Report Series|
|Publisher||Centre for Telematics and Information Technology, University of Twente|
- DB-CAQ: CONTEXT-AWARE QUERYING