TourViz: Interactive visualization of connection pathways in large graphs

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn , Issue , 2012, Pages 1516-1519

  Chau, Duen Horng ^a   Akoglu, Leman ^a   Vreeken, Jilles ^b   Tong, Hanghang ^c   Faloutsos, Christos ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

^b UNIVERSITY OF ANTWERP   (Belgium)

^c IBM T J WATSON RESEARCH CENTER   (United States)

Author keywords

connection subgraphs; large networks; sensemaking

Indexed keywords

COAUTHORSHIP; CONNECTION SUBGRAPHS; DATA SETS; GRAPH DATA; INPUT NODE; INTERACTIVE VISUALIZATIONS; LARGE GRAPHS; LARGE NETWORKS; SENSEMAKING; SUBGRAPHS; USER INTERACTION;

DATA MINING; VISUALIZATION;

GRAPH THEORY;

EID: 84866036459     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2339530.2339769     Document Type: Conference Paper

References (13)

1. L. Akoglu, J. Vreeken, H. Tong, D. H. Chau, and C. Faloutsos. Islands and bridges: Making sense of marked nodes in large graphs. Technical Report CMU-CS-12-124, Carnegie Mellon University, 2012.
2. D. Chau, A. Kittur, J. I. Hong, and C. Faloutsos. Apolo: Making Sense of Large Network Data by Combining Rich User Interaction and Machine Learning. In CHI, 2011.
3. D. H. Chau, C. Faloutsos, H. Tong, J. I. Hong, B. Gallagher, and T. Eliassi-Rad. Graphite: A visual query system for large graphs. In ICDM Workshops, pages 963-966, 2008.
4. C. Faloutsos, K. S. McCurley, and A. Tomkins. Fast discovery of connection subgraphs. In KDD, 2004.
5. J. F. R. Jr., H. Tong, A. J. M. Traina, C. Faloutsos, and J. Leskovec. Gmine: A system for scalable, interactive graph visualization and mining. In VLDB, pages 1195-1198, 2006.
6. Y. Koren, S. C. North, and C. Volinsky. Measuring and extracting proximity in networks. In KDD, 2006.
7. B. Kules. From keyword search to exploration: How result visualization aids discovery on the web.
8. J. O'Madadhain, D. Fisher, P. Smyth, S. White, and Y. Boey. Analysis and visualization of network data using JUNG. Journal of Statistical Software, 10:1-35, 2005.
9. C. Ramakrishnan, W. H. Milnor, M. Perry, and A. P. Sheth. Discovering informative connection subgraphs in multi-relational graphs. 7(2):56-63, 2005.
10. J. Riedy, D. A. Bader, K. Jiang, P. Pande, , and R. Sharma. Detecting communities from given seeds in social networks. Technical Report GT-CSE-11-01, 2011.
11. P. Sevon and L. Eronen. Subgraph queries by context-free grammars. J. Integrative Bioinformatics, 5(2), 2008.
12. D. A. Spielman and S.-H. Teng. A local clustering algorithm for massive graphs and its application to nearly-linear time graph partitioning. CoRR, abs/0809.3232, 2008.
13. H. Tong and C. Faloutsos. Center-piece subgraphs: problem definition and fast solutions. In KDD, pages 404-413, 2006.