A general framework for geo-social query processing

Abstract

The proliferation of GPS-enabledmobile devises and the popularity of social networking have recently led to the rapid growth of Geo-Social Networks (GeoSNs). GeoSNs have created a fertile ground for novel location-based social interactions and advertising. These can be facilitated by GeoSN queries, which extract useful information combining both the social relationships and the current location of the users. This paper constitutes the first systematic work on GeoSN query processing. We propose a general framework that offers flexible data management and algorithmic design. Our architecture segregates the social, geographical and query processing modules. Each GeoSN query is processed via a transparent combination of primitive queries issued to the social and geographical modules. We demonstrate the power of our framework by introducing several "basic" and "advanced" query types, and devising various solutions for each type. Finally, we perform an exhaustive experimental evaluation with real and synthetic datasets, based on realistic implementations with both commercial software (such as MongoDB) and state-of-the-art research methods. Our results confirm the viability of our framework in typical large-scale GeoSNs.