Retrieving Top-k Famous Places in Location-Based Social Networks

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9877)

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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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Faculty of Information TechnologyMonash UniversityMelbourneAustralia
  2. 2.IntersectMelbourneAustralia

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