Ranking Query Results using Context-Aware Preferences

A.H. van Bunningen, M.M. Fokkinga, Peter M.G. Apers, L. Feng

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

16 Citations (Scopus)
228 Downloads (Pure)


To better serve users’ information needs without requiring comprehensive queries from users, a simple yet effective technique is to explore the preferences of users. Since these preferences can differ for each context of the user, we introduce context-aware preferences. To anchor the semantics of context-aware preferences in a traditional probabilistic model of information retrieval, we present a semantics for context-aware preferences based on the history of the user. An advantage of this approach is that the inherent uncertainty of context information, due to the fact that context information is often acquired through sensors, can be easily integrated in the model. To demonstrate the feasibility of our approach and current bottlenecks we provide a naive implementation of our technique based on database views.
Original languageUndefined
Title of host publicationFirst International Workshop on Ranking in Databases (DBRank 2007)
Place of PublicationLos Alamitos
Number of pages8
ISBN (Print)978-1-4244-0832-0
Publication statusPublished - 16 Apr 2007
Event23rd International Conference on Data Engineering, ICDE 2007 - Istanbul, Turkey
Duration: 17 Apr 200720 Apr 2007
Conference number: 23

Publication series

PublisherIEEE Computer Society Press
Number1, suppl.


Workshop23rd International Conference on Data Engineering, ICDE 2007
Abbreviated titleICDE


  • EWI-10279
  • METIS-241682
  • IR-64121

Cite this