Abstract
Current moving-object database (MOD) systems focus on management of movement data, but pay less attention to modelling social relationships between moving objects and spatial-temporal trajectories in an integrated manner. This paper combines moving-object database and social network systems and presents a novel data model called Geo-Social-Moving (GSM) that enables the unified management of trajectories, underlying geographical space and social relationships for mass moving objects. A bulk of user-defined data types and corresponding operators are also proposed to facilitate geo-social queries on moving objects. An implementation framework for the GSM model is proposed, and a prototype system based on native Neo4J is then developed with two real-world data sets from the location-based social network systems. Compared with solutions based on traditional extended relational database management systems characterized by time-consuming table join operations, the proposed GSM model characterized by graph traversal is argued to be more powerful in representing mass moving objects with social relationships, and more efficient and stable for geo-social querying.
Highlights
Moving object databases (MOD) allow modelling, manage moving entities such as people, vehicles and vessels, and have been extensively studied over the past few years, such as data modelling [1,2,3,4,5,6], indexing [7,8,9,10], and querying [11,12,13,14,15]
We focus on modelling the moving objects with social relationships and propose a composite graph-based data model called Geo-Social-Moving (GSM) where geographical space, trajectories and social relationships are all represented with graph structures
With the increase in check-in records or social relations of moving objects, the relational table join operations made the naive implementation impractical, whereas the performance of the implementation supported with the GSM model remained stable
Summary
Moving object databases (MOD) allow modelling, manage moving entities such as people, vehicles and vessels, and have been extensively studied over the past few years, such as data modelling [1,2,3,4,5,6], indexing [7,8,9,10] , and querying [11,12,13,14,15]. This research focuses on the management of movements and involved geographic environments, but ignores the social relationships between moving objects. The user has some online relationships in social networks, such as Facebook, Twitter or Foursquare. In so called location based social networks (LBSN) [16,17,18], there have been a bulk of query requests concerning movements with spatial and temporal characteristics, and dynamic variation of social relationships:
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