Florian Wenzel

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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,(More)
Our demo application demonstrates a personalized location-based web application using Preference SQL that allows single users as well as groups of users to find accommodations in Istanbul that satisfy both hard constraints and user preferences. The application assists in defining spatial, numerical , and categorical base preferences and composes complex(More)
Location-Based Social Networks (LBSN) are a vast source for personalized geo-social user data with more and more users adding spatial information to their posts and tweets. The potential of spatially rich user models lies in the aggregation of different networks with each network adding a piece to the digital footprint of a user. These user models in turn(More)
Among the goals of statistical genetics is to find associations between genetic data and binary phenotypes, such as heritable diseases. Often, the data are obfuscated by confounders such as age, ethnicity, or population structure. Linear mixed models are linear regression models that correct for confounding by means of correlated label noise; they are(More)
With the beginning of the new millenium, the concept of group interactions in communication systems was boosted by the emergence of Web 2.0 technologies. Based on this new area of application, the notion of group decisions and group preferences also evolved, leading to new requirements for corresponding modeling frameworks. Purely numeric approaches are(More)
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