A framework for discovering spatio-temporal cohesive networks

Authors:
Jin Soung Yoo;Joengmin Hwang
Affiliations:
Department of Computer Science, Indiana University-Purude University, Fort Wayne, Indiana;Computer Science & Engineering Department, University of Minnesota, Minneapolis, Minnesota
Venue:
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
Year:
2008

Citing 2
Cited 1

Frequent Subgraph Discovery

ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
A Join-Less Approach for Co-Location Pattern Mining: A Summary of Results

ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining

Social Media Business Intelligence: A Pharmaceutical Domain Analysis Study

International Journal of Sociotechnology and Knowledge Development

Quantified Score

Hi-index	0.00

Visualization

Abstract

A spatio-temporal cohesive network represents a social network in which people often interact closely in both space and time. Spatially and temporally close people tend to share information and show homogeneous behavior.We discuss modeling social networks from spatiotemporal human activity data, and alternative interest measures for estimating the strength of subgroup cohesion in spatial and temporal space. We present an algorithm for mining spatio-temporal cohesive networks.