Abstract
Location-Based Social Networking Services (LBSNSs) have been becoming increasingly popular. One of the applications provided by LBSNSs is a PoI search based on spatial distance, social relationships, and keywords. In this paper, we propose a novel query, Geo-Social Keyword Skyline Query (GSKSQ), which returns the skyline of a set of PoIs based on a query point, the social relationships of the query owner, and query keywords. Skyline is the set of data objects which are not dominated by others. We also propose an index structure, Social Keyword R-tree, which supports efficient GSKSQ processing. The results of our experiments on two real datasets Gowalla and Brightkite demonstrate the efficiency of our solution.
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Taguchi, N., Amagata, D., Hara, T. (2017). Geo-Social Keyword Skyline Queries. In: Benslimane, D., Damiani, E., Grosky, W., Hameurlain, A., Sheth, A., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2017. Lecture Notes in Computer Science(), vol 10438. Springer, Cham. https://doi.org/10.1007/978-3-319-64468-4_32
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DOI: https://doi.org/10.1007/978-3-319-64468-4_32
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