Optimizing Preference Queries for Personalized Web Services

Personalization of Web services requires a powerful preference model that smoothly and efficiently integrates with standard database query languages. We make the case for preferences as strict partial orders, supported in Preference SQL and Preference XPATH. Performance of Web services will crucially depend on various architectural design decisions. We pointed out that a central server architecture is desirable. Concerning the implementation of preference queries we investigated the tightly coupled architecture, presenting a novel approach for algebraic optimization based on preference algebra. We provided new transformation laws and gave evidence for the power of this heuristic optimization. This forms the basis for a new preference query optimization methodology, promising sufficient performance even for complex Web services.