Publication Type
Journal Article
Version
publishedVersion
Publication Date
6-2010
Abstract
Spatio-temporal data concerning the movement of individuals over space and time contains latent information on the associations among these individuals. Sources of spatio-temporal data include usage logs of mobile and Internet technologies. This article defines a spatio-temporal event by the co-occurrences among individuals that indicate potential associations among them. Each spatio-temporal event is assigned a weight based on the precision and uniqueness of the event. By aggregating the weights of events relating two individuals, we can determine the strength of association between them. We conduct extensive experimentation to investigate both the efficacy of the proposed model as well as the computational complexity of the proposed algorithms. Experimental results on three real-life spatio-temporal datasets cross-validate each other, lending greater confidence on the reliability of our proposed model.
Keywords
Data mining, Social network, Spatio-temporal databases
Discipline
Databases and Information Systems | Numerical Analysis and Scientific Computing
Publication
ACM Transactions on Information Systems
Volume
28
Issue
3
First Page
1
Last Page
32
ISSN
1046-8188
Identifier
10.1145/1777432.1777438
Publisher
ACM
Citation
LAUW, Hady W.; LIM, Ee Peng; PANG, Hwee Hwa; and TAN, Teck-Tim.
STEvent: Spatio-Temporal Event Model for Social Network Discovery. (2010). ACM Transactions on Information Systems. 28, (3), 1-32.
Available at: https://ink.library.smu.edu.sg/sis_research/782
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://doi.org/10.1145/1777432.1777438
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons