Querying geo-social data by bridging spatial networks and social networks

Abstract

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.

Storing routes in socio-spatial networks and supporting social-based route recommendation

“…This paper continues a work that was presented in [2]. The previous work has introduced an initial solution for integration of a social network and a spatial network.…”

“…The previous work has introduced an initial solution for integration of a social network and a spatial network. The main differences between this paper and [2] are the following.…”

“…(1) The model that was suggested in [2] is not designed to maintain information on routes, and is in general, a simpler and less expressive model than the model presented in this paper. (2) A query language that was presented in [2] is based on set operations and not on graph traversal.…”

Querying socio-spatial networks on the world-wide web

“…The language is an algebra that consists of seven operators, under set semantics. The language is formally presented in [1], and here we merely provide a brief overview of the operators. There are four unary operators.…”

“…For example, in SSNQL one can formulate a query that finds friends of Marge who frequently buy at the same grocery store as she does. SSNQL has first been formally introduced in [1], and it was extended in [2] to handle travel routes, however, it was prior to the development and implementation of a complete data management system. In this paper we present a fullfledged system that manages socio-spatial networks and supports the evaluation of SSNQL queries over an SSN.…”