A Context-Aware Preference Model for Database Querying in an Ambient Intelligent Environment

  • Arthur H. van Bunningen
  • Ling Feng
  • Peter M. G. Apers
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4080)


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 context-aware 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.


Description Logic Preference Model Database Schema Database Query Free Time Activity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Arthur H. van Bunningen
    • 1
  • Ling Feng
    • 1
  • Peter M. G. Apers
    • 1
  1. 1.Centre for Telematics and Information TechnologyUniversity of TwenteEnschedeThe Netherlands

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