Abstract
Preference SQL is a declarative extension of standard SQL by strict partial order preferences, behaving like soft constraints under the BMO query model. Preference queries can be formulated intuitively following an inductive constructor-based approach. Both qualitative methods like e.g. Pareto / skyline and quantative methods like numerical ranking, definable over categorical as well as numerical attribute domains can be used. The Preference SQL System is implemented as a middleware component, enabling a seamless application integration with standard SQL back-end systems. The preference query optimizer performs algebraic transformations of preference relational algebra as well as cost-based algorithm selection e.g. for efficient Pareto / skyline evaluation. Ongoing work extends Preference SQL towards efficient support for personalized location-based mobile geo-services and social networks.
Authors
Werner Kießling, Markus Endres, Florian Wenzel
Publication
Bulletin of the Technical Committee on Data Engineering, Vol. 34 No. 2, June 2011, p. 11-18