Hierarchical focus+context heterogeneous network visualization

IEEE Pacific Visualization Symposium

Volumn , Issue , 2014, Pages 89-96

  Shi, Lei ^a   Liao, Qi ^b   Tong, Hanghang ^c   Hu, Yifan ^d   Zhao, Yue ^e   Lin, Chuang ^e  

^a INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

^b CENTRAL MICHIGAN UNIVERSITY   (United States)

^c CITY UNIVERSITY OF NEW YORK   (United States)

^d ATandT Labs Research   (Germany)

^e TSINGHUA UNIVERSITY   (China)

Author keywords

Graph visualization; heterogeneous network; visual exploration

Indexed keywords

AGGREGATES; ELECTRIC NETWORK TOPOLOGY; HETEROGENEOUS NETWORKS;

GRAPH VISUALIZATION; INTEGRATED FRAMEWORKS; INTERACTION MODEL; LEVELS OF ABSTRACTION; MULTIPLE CONCENTRIC CIRCLES; NETWORK VISUALIZATION; PERFORMANCE EXPERIMENT; VISUAL EXPLORATION;

VISUALIZATION;

EID: 84899581994     PISSN: 21658765     EISSN: 21658773     Source Type: Conference Proceeding    
DOI: 10.1109/PacificVis.2014.44     Document Type: Conference Paper

References (28)

1. IEEE VAST Challenge, 2012. http://www.vacommunity. org/ VAST+Challenge+2012.
2. KDD Cup, 2012. http://www.kddcup2012.org/.
3. VizSec community, 2013. http://vizsec.org.
4. J. Abello, F. van Ham, and N. Krishnan. ASK-GraphView: A large scale graph visualization system. IEEE Transactions on Visualization and Computer Graphics, 12(5):669-676, 2006.
5. D. Archambault, T. Munzner, and D. Auber. Multi-level graph layout by topological features. IEEE Transactions on Visualization and Computer Graphics, 13(2):305-317, 2007.
6. D. Archambault, T. Munzner, and D. Auber. Grouseflocks: Steerable exploration of graph hierarchy space. IEEE Transactions on Visualization and Computer Graphics, 14(4):900-913, 2008.
7. D. Auber, Y. Chiricota, F. Jourdan, and G. Melancon. Multiscale visualization of small world networks. In IEEE Symposium on Information Visualization (InfoVis'03), pages 75-81, 2003.
8. A. Bezerianos1, F. Chevalier, P. Dragicevic, N. Elmqvist, and J. D. Fekete. Graphdice: A system for exploring multivariate social networks. Computer Graphics Forum, 29(3):863-872, 2010.
9. D. M. Blei, A. Y. Ng, and M. I. Jordan. Latent dirichlet allocation. Journal of Machine Learning Research, 3:993-1022, 2003.
10. N. Cao, J. Sun, Y.-R. Lin, D. Gotz, S. Liu, and H. Qu. Facetatlas: Multifaceted visualization for rich text corpora. IEEE Transactions on Visualization and Computer Graphics, 16(6):1172-1181, 2010.
11. C. Dunne, N. H. Riche, B. Lee, R. Metoyer, and G. Robertson. Graphtrail: analyzing large multivariate, heterogeneous networks while supporting exploration history. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pages 1663-1672, 2012.
12. N. Elmqvist and J.-D. Fekete. Hierarchical aggregation for information visualization: Overview, techniques and design guidelines. IEEE Transactions on Visualization and Computer Graphics, 16(3):439-454, 2010.
13. E. Gansner, Y. Koren, and S. North. Topological fisheye views for visualizing large graphs. In IEEE Symposium on Information Visualization (InfoVis'04), 2004.
14. J. Heer and D. Boyd. Vizster: visualizing online social networks. In IEEE Symposium on Information Visualization (InfoVis'05), pages 32-39, 2005.
15. H. Kang, C. Plaisant, B. Lee, and B. B. Bederson. Netlens: Iterative exploration of content-actor network data. Information Visualization, 6(1):18-31, 2007.
16. J. Lamping, R. Rao, and P. Pirolli. A focus+context technique based on hyperbolic geometry for visualizing large hierarchies. In Proceedings of the international conference on Human factors in computing systems (CHI'95), 1995.
17. B. Lee, C. Plaisant, C. S. Parr, J.-D. Fekete, and N. Henry. Task taxonomy for graph visualization. In Proceedings of BEyond time and errors: novel evaLuation methods for Information Visualization (BELIV), pages 82-86, 2006.
18. B. Lee, G. Smith, G. Robertson, M. Czerwinski, and D. S. Tan. Facetlens: exposing trends and relationships to support sensemaking within faceted datasets. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pages 1293-1302, 2009.
19. F. Lorrain and H. C. White. Structural equivalence of individuals in social networks. The Journal of Mathematical Sociology, 1(1):49-80, 1971.
20. J. B. MacQueen. Some methods for classification and analysis of multivariate observations. Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability, Berkeley, University of California Press, 1:281-297, 1967.
21. Z. Shen, K.-L. Ma, and T. Eliassi-Rad. Visual analysis of large heterogeneous social networks by semantic and structural abstraction. IEEE Transactions on Visualization and Computer Graphics, 12(6):1427-1439, 2006.
22. B. Shneiderman. The eyes have it: A task by data type taxonomy for information visualizations. In Proceedings of the IEEE Symposium on Visual Languages, pages 336-343, 1996.
23. B. Shneiderman and A. Aris. Network visualization by semantic substrates. IEEE Transactions on Visualization and Computer Graphics, 12(5):733-740, 2006.
24. G. Sindre, B. Gulla, and H. G. Jokstad. Onion graphs: aesthetics and layout. In Proceedings of the IEEE Workshop on Visual Languages, pages 287-291, 1993.
25. J. Tang, J. Zhang, L. Yao, J. Li, L. Zhang, and Z. Su. Arnetminer: Extraction and mining of academic social networks. In ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pages 990-998, 2008.
26. F. van Ham and A. Perer. "search, show context, expand on demand": Supporting large graph exploration with degree-of-interest. IEEE Transactions on Visualization and Computer Graphics, 15(6):953-960, 2009.
27. M. Wattenberg. Visual exploration of multivariate graphs. In SIGCHI conference on Human Factors in computing systems (CHI'06), 2006.
28. D. R. White and K. P. Reitz. Graph and semigroup homomorphisms on networks of relations. Social Networks, 5(2):193-234, 1983.