Next Article in Journal
How Do Vegetation Density and Transportation Network Density Affect Crime across an Urban Central-Peripheral Gradient? A Case Study in Kitchener—Waterloo, Ontario
Next Article in Special Issue
Road Map Inference: A Segmentation and Grouping Framework
Previous Article in Journal
Integrating Spatial and Attribute Characteristics of Extended Voronoi Diagrams in Spatial Patterning Research: A Case Study of Wuhan City in China
Previous Article in Special Issue
Detecting Themed Streets Using a Location Based Service Application
Open AccessArticle

Modeling and Querying Moving Objects with Social Relationships

by 1,2, 1,2,3,* and 4
1
State Key Lab of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
2
Fujian Collaborative Innovation Center for Big Data Applications in Governments, Fuzhou 350003, China
3
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
4
Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
*
Author to whom correspondence should be addressed.
Academic Editors: Georg Gartner, Haosheng Huang and Wolfgang Kainz
ISPRS Int. J. Geo-Inf. 2016, 5(7), 121; https://doi.org/10.3390/ijgi5070121
Received: 23 April 2016 / Revised: 5 July 2016 / Accepted: 8 July 2016 / Published: 15 July 2016
(This article belongs to the Special Issue Location-Based Services)
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. View Full-Text
Keywords: moving objects; social network; data model; graph database; geo-social querying moving objects; social network; data model; graph database; geo-social querying
Show Figures

Figure 1

MDPI and ACS Style

Zhang, H.; Lu, F.; Xu, J. Modeling and Querying Moving Objects with Social Relationships. ISPRS Int. J. Geo-Inf. 2016, 5, 121.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map

1
Back to TopTop