Ranking Query Results using Context-Aware Preferences

Authors:
Arthur H. van Bunningen;Maarten M. Fokkinga;Peter M. G. Apers;Ling Feng
Affiliations:
Centre for Telematics and Information Technology, University of Twente, The Netherlands. bunninge@cs.utwente.nl;Centre for Telematics and Information Technology, University of Twente, The Netherlands. fokkinga@cs.utwente.nl;Centre for Telematics and Information Technology, University of Twente, The Netherlands. apers@cs.utwente.nl;Department of Computer Science&Technology, Tsinghua University, China. fengling@tsinghua.edu.cn
Venue:
ICDEW '07 Proceedings of the 2007 IEEE 23rd International Conference on Data Engineering Workshop
Year:
2007

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Abstract

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.