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 preference statements in an intuitive fashion. Unlike existing location-based services, the application considers spatial queries as soft instead of hard constraints to determine the best matches which are finally presented on a map. The underlying Preference SQL framework is implemented on top of a database, therefore enabling a seamless application integration with standard SQL back-end systems as well as efficient and extensible preference query processing.

This paper presents an approach to exploit free text descriptions of TV programmes as available from EPG data sets for a TV recommender system that takes the content of programmes into account. The paper focuses on the natural language understanding problem underlying the analysis of free text descriptions and on methods of classifying free text descriptions with respect to a natural language user query. We close with an evaluation of user acceptance and a discussion of future work.