TourViz: interactive visualization of connection pathways in large graphs

Authors:
Duen Horng Chau;Leman Akoglu;Jilles Vreeken;Hanghang Tong;Christos Faloutsos
Affiliations:
Carnegie Mellon University, Pittsburgh, PA, USA;Carnegie Mellon University, Pittsburgh, PA, USA;University of Antwerp, Antwerp, Belgium;IBM T.J. Watson Research, Hawthorne, NY, USA;Carnegie Mellon University, Pittsburgh, PA, USA
Venue:
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Year:
2012

Citing 7
Cited 0

Fast discovery of connection subgraphs

Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Discovering informative connection subgraphs in multi-relational graphs

ACM SIGKDD Explorations Newsletter
Measuring and extracting proximity in networks

Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Center-piece subgraphs: problem definition and fast solutions

Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
GMine: a system for scalable, interactive graph visualization and mining

VLDB '06 Proceedings of the 32nd international conference on Very large data bases
GRAPHITE: A Visual Query System for Large Graphs

ICDMW '08 Proceedings of the 2008 IEEE International Conference on Data Mining Workshops
Apolo: making sense of large network data by combining rich user interaction and machine learning

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present TourViz, a system that helps its users to interactively visualize and make sense in large network datasets. In particular, it takes as input a set of nodes the user specifies as of interest and presents the user with a visualization of connection subgraphs around these input nodes. Each connection subgraph contains good pathways that highlight succinct connections among a "close-by" group of input nodes. TourViz combines visualization with rich user interaction to engage and help the user to further understand the relations among the nodes of interest,by exploring their neighborhood on demand as well as modifying the set of interest nodes. We demonstrate TourViz's usage and benefits using the DBLP graph, consisting of authors and their co-authorship relations, while our system is designed generally to work with any kind of graph data. We will invite the audience to experiment with our system and comment on its usability, usefulness, and how our system can help with their research and improve the understanding of data in other domains.