Recording the location of people using location-acquisition technologies, such as GPS, allows generating life patterns, which associate people to places they frequently visit. Considering life patterns as edges that connect users of a social network to geographical entities on a spatial network, enriches the social network, providing an integrated sociospatial graph. Queries over such graph extract information on users, in correspondence with their location history, and extract information on geographical entities in correspondence with users who frequently visit these entities. In this paper we present the concept of a socio-spatial graph that is based on life patterns, where users are connected to geographical entities using life-pattern edges. We provide a set of operators that form a query language suitable for the integrated data. We consider two implementations of a socio-spatial graph storage-one implementation uses a relational database system as the underline data storage, and the other employs a graph database system. The two implementations are compared, experimentally, for various queries and data. An important contribution of this work is in illustrating the usefulness and the feasibility of maintaining and querying integrated socio-spatial graphs.
Y. Doytsher, et al. REF propose a sociospatial graph model and introduce a query language formed by a set of sociospatial operators.
Querying geo-social data by bridging spatial networks and social networks
LBSN '10
Computer Science