Mining user similarity based on location history
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
Mining interesting locations and travel sequences from GPS trajectories
Proceedings of the 18th international conference on World wide web
Mining Individual Life Pattern Based on Location History
MDM '09 Proceedings of the 2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware
GeoLife2.0: A Location-Based Social Networking Service
MDM '09 Proceedings of the 2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware
Analysis of a Location-Based Social Network
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 04
Storing routes in socio-spatial networks and supporting social-based route recommendation
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Location-Based Social Networks
Querying socio-spatial networks on the world-wide web
Proceedings of the 21st international conference companion on World Wide Web
Circle of friend query in geo-social networks
DASFAA'12 Proceedings of the 17th international conference on Database Systems for Advanced Applications - Volume Part II
Proceedings of the ACM SIGKDD International Workshop on Urban Computing
A general framework for geo-social query processing
Proceedings of the VLDB Endowment
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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 socio-spatial 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.