A Preference SQL Approach to Improve Context-Adaptive Location-Based Services for Outdoor Activities

Abstract. Personalized and context-aware information filtering poses a major challenge for the development of meaningful location-based recom- mendation services, and even more for complex mobile apps for planning outdoor activities. To this end search engine technology has to be extended by sophisticated preference handling capabilities for large amounts of ap- plication data, which is typically stored in relational geo-databases like PostGIS. In this paper we propose to employ the Preference SQL query lan- guage with its Best-Matches-Only query model as one key enabling tech- nology. Moreover, we introduce a novel location-based preference construc- tor for querying such geo-databases. We further demonstrate how this ex- tended Preference SQL system can be integrated with an existing commer- cial web platform for planning outdoor activities such as hiking or moun- tain bike tours. By performing personalized and context-aware query com- position, employing a preference repository attached with social networks and using online information like weather conditions, best matching tour recommendations can be computed with one single query and delivered to mobile smart phones. We are highly confident that forthcoming practical use case evaluations will show the effectiveness and efficiency of our ap- proach for a wide range of application scenarios.

Keywords. preference handling, Preference SQL, personalization, mobile Location-Based Services, context-aware search