Skyline queries based on user locations and preferences for making location-based recommendations

Due to the recent development of mobile computing and communication network technologies, information services for mobile phone users and car navigation systems have becomeof some importance. Since these mobile devices have limited display sizes, we often need to select carefully the appropriate information to be presented to the user. However, it is not easy to select the "appropriate" information because users have different contexts and preferences. In this paper, we present an approach to recommending items such as restaurants to a mobile user taking into account his current location and preferences. In our framework, a user initially provides a profile, which records preferences as relative orders within predefined categories such as food types and prices. We then select items to be recommended from the database based on the user's profile as well as the current location. To select good items, we extend the notion of spatial skyline queries to incorporate not only distance information but also categorical preference information. Based on the proposed approach, a prototype system has been implemented in a small mobile PC containing a small embedded RDBMS. The facilities of the RDBMS, such as spatial indexes, were used to process our skyline queries effectively.