Skyline query processing in environments incorporating preferences of multiple users

Abstract

Recently, facilitated by the improvement of the mobile environment and the growing number of mobile users, the location-based service(LBS) has become more attractive and widely used. In LBS, the skyline query has been often used to select interesting objects which have spatial attributes. In this thesis, the problem, named the Skyline Query for Multiple User Preferences(SQMUP), is addressed. Given a group of participants, i.e. the users specified in a query, SQMUP finds skyline objects incorporating user-dependent attributes (user preferences and the distance to the user location) for all participants and user-independent attributes (objective characteristics) in order to recommend suitable objects for all participating users. In order to solve SQMUP, an efficient and progressive approach is introduced, that reduces query time and maintains a reasonable index size based on a graph summarizing the dominance relations and the R-trees. In addition, the results of extensive experiments show that the proposed method outperforms a comparison method.