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
Analysis of a Location-Based Social Network
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 04
Querying geo-social data by bridging spatial networks and social networks
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Location Based Social Networks
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
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navigation systems, allow users to record their location history. The location history data can be analyzed to generate life patterns|patterns that associate people to places they frequently visit. Accordingly, an SSN is a graph that consists of (1) a social network, (2) a spatial network, and (3) life patterns that connect the users of the social network to locations, i.e., to geographical entities in the spatial network. In this paper we present a system that stores SNN in a graph-based database management system and provides a novel query language, namely SSNQL, for querying the integrated data. The system includes a Web-based graphical user interface that allows presenting the social network, presenting the spatial network and posing SSNQL queries over the integrated data. The user interface also depicts the structure of queries for the purpose of debugging and optimization. Our demonstration presents the management of the integrated data as an SSN and it illustrates the query evaluation process in SSNQL.