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 two new types of queries called Top-k famous places TkFP and Socio-Spatial Skyline Query SSSQ query, which enrich the semantics of the
conventional spatial queries 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 TkFP and SSSQ queries. Finally, we conduct an extensive evaluation of the proposed schemes using real and synthetic datasets and demonstrate the effectiveness of the proposed approaches.
conventional spatial queries 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 TkFP and SSSQ queries. Finally, we conduct an extensive evaluation of the proposed schemes using real and synthetic datasets and demonstrate the effectiveness of the proposed approaches.
| Original language | English |
|---|---|
| Pages (from-to) | 1-19 |
| Number of pages | 19 |
| Journal | The Computer Journal |
| DOIs | |
| Publication status | Published - 2018 |