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Personalization of e-services poses new challenges to database technology, demanding a powerful and flexible modeling technique for complex preferences. Preference queries have to be answered cooperatively by treating preferences as soft constraints, attempting a best possible match-making. We propose a strict partial order semantics for preferences, which(More)
Personalization of database queries requires a semantically rich, easy to handle and flexible preference model. Building on preferences as strict partial orders we provide a variety of intuitive base preference constructors for numerical and categorical data, including so-called d-parameters. As a novel semantic concept for complex preferences we introduce(More)
Applications like multimedia databases or enterprise-wide information management systems have to meet the challenge of efficiently retrieving best matching objects from vast collections of data. We present a new algorithm Stream-Combine for processing multi-feature queries on heterogeneous data sources. Stream-Combine is self-adapting to different data(More)
Advanced personalized web applications require a carefully dealing with their users' wishes and preferences. Since such preferences do not always hold in general, personalized applications also have to consider the user's current situation. In this paper we present a novel framework for modeling situations and situated preferences. Our approach consists of(More)
– We present a new XML-based search technology for e-commerce that enables users to formulate complex customer or vendor preferences, which typically occur within B2C or B2B applications. Preferences are modeled in a very natural way by partial orders. Since our semantics of multi-attribute preferences implements the Pareto-optimality principle, Preference(More)
The DUCK-calculus presented here is a recent approach to cope with probabilistic uncertainty in a sound and eecient way. Uncertain rules with bounds for probabilities and explicit conditional independences can be maintained incrementally. The basic inference mechanism relies on local bounds propagation, implementable by deductive databases with a bottom-up(More)
In digital libraries image retrieval queries can be based on the similarity of objects, using several feature attributes like shape, texture, color or text. Such multi-feature queries return a ranked result set instead of exact matches. Besides, the user wants to see only the k top-ranked objects. We present a new algorithm called Quick-Combine (European(More)