Abstract
The widespread proliferation of location-acquisition techniques and GPS-embedded mobile devices have resulted in the generation of geo-tagged data at unprecedented scale and have essentially enhanced the user experience in location-based services associated with social networks. Such location-based social networks allow people to record and share their location and are a rich source of information which can be exploited to study people’s various attributes and characteristics to provide various Geo-Social (GS) services. In this paper, we propose a new type of query called Top-k famous places \(T_kFP\) query, which enriches the semantics of the conventional spatial query by introducing a social relevance component. In addition, three approaches namely, (1) Social-First (2) Spatial-First and (3) Hybrid are proposed to efficiently process \(T_kFP\) queries. Finally, we conduct an exhaustive evaluation of the proposed schemes using real and synthetic datasets and demonstrate the effectiveness of the proposed approaches.
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Sohail, A., Murtaza, G., Taniar, D. (2016). Retrieving Top-k Famous Places in Location-Based Social Networks. In: Cheema, M., Zhang, W., Chang, L. (eds) Databases Theory and Applications. ADC 2016. Lecture Notes in Computer Science(), vol 9877. Springer, Cham. https://doi.org/10.1007/978-3-319-46922-5_2
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DOI: https://doi.org/10.1007/978-3-319-46922-5_2
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