TopicPanorama: A full picture of relevant topics

2014 IEEE Conference on Visual Analytics Science and Technology, VAST 2014 - Proceedings

Volumn , Issue , 2015, Pages 183-192

  Liu, Shixia ^a   Wang, Xiting ^a,b   Chen, Jianfei ^b   Zhu, Jim ^b   Guo, Baining ^a  

^a MICROSOFT RESEARCH ASIA   (China)

^b TSINGHUA UNIVERSITY   (China)

Author keywords

graph matching; graph visualization; level of detail; Topic graph; user interactions

Indexed keywords

BLOGS; GRAPHICAL USER INTERFACES; PATTERN MATCHING; VISUALIZATION;

GRAPH MATCHINGS; GRAPH VISUALIZATION; LEVEL OF DETAIL; TOPIC GRAPH; USER INTERACTION;

TREES (MATHEMATICS);

EID: 84929470844     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/VAST.2014.7042494     Document Type: Conference Paper

References (61)

1. Boardreader. http://www.boardreader.com, Mar. 2014.
2. B. Alper, B. Bach, N. H. Riche, T. Isenberg, and J.-D. Fekete. Weighted graph comparison techniques for brain connectivity analysis. In CHI, pages 483-492, 2013.
3. K. Andrews, M. Wohlfahrt, and G. Wurzinger. Visual graph comparison. In IV, pages 62-67, 2009.
4. D. Blei and J. Lafferty. Correlated topic models. In NIPS, pages 147-154. 2006.
5. D. M. Blei, A. Y. Ng, and M. I. Jordan. Latent dirichlet allocation. the Journal of machine Learning research, 3:993-1022, 2003.
6. C. Blundell, Y. W. Teh, and K. A. Heller. Bayesian rose trees. In UAI, pages 65-72, 2010.
7. J. Branke. Dynamic graph drawing. In Drawing Graphs, pages 228-246, 1999.
8. S. Bremm, T. von Landesberger, M. Hess, T. Schreck, P. Weil, and K. Hamacher. Interactive visual comparison of multiple trees. In IEEE VAST, pages 31-40, 2011.
9. N. Cao, J. Sun, Y.-R. Lin, D. Gotz, S. Liu, and H. Qu. Facetatlas: Multifaceted visualization for rich text corpora. IEEE TVCG, 16(6):1172-1181, 2010.
10. A. J.-B. Chaney and D. M. Blei. Visualizing topic models. In ICWSM, 2012.
11. J. Chen, J. Zhu, Z. Wang, X. Zheng, and B. Zhang. Scalable inference for logistic-normal topic models. In NIPS, pages 2445-2453. 2013.
12. J. Choo, C. Lee, C. K. Reddy, and H. Park. Utopian: User-driven topic modeling based on interactive nonnegative matrix factorization. IEEE TVCG, 19(12):1992-2001, 2013.
13. C. Collins and M. S. T. Carpendale. Vislink: Revealing relationships amongst visualizations. IEEE TVCG, 13(6):1192-1199, 2007.
14. D. Conte, P. Foggia, C. Sansone, and M. Vento. Thirty years of graph matching in pattern recognition. International journal of pattern recognition and artificial intelligence, 18(03):265-298, 2004.
15. W. Cui, S. Liu, L. Tan, C. Shi, Y. Song, Z. Gao, H. Qu, and X. Tong. Textflow: Towards better understanding of evolving topics in text. IEEE TVCG, 17(12):2412-2421, 2011.
16. W. Cui, S. Liu, Z. Wu, and H. Wei. How hierarchical topics evolve in large text corpora. To appear in IEEE TVCG, 2014.
17. W. Cui, X. Wang, S. Liu, N. H. Riche, T. M. Madhyastha, K. L. Ma, and B. Guo. Let it flow: a static method for exploring dynamic graphs. In IEEE PacificVis, pages 121-128, 2014.
18. M. Dork, D. M. Gruen, C. Williamson, and M. S. T. Carpendale. A visual backchannel for large-scale events. IEEE TVCG, 16(6):1129-1138, 2010.
19. W. Dou, X. Wang, R. Chang, and W. Ribarsky. Paralleltopics: A probabilistic approach to exploring document collections. In IEEE VAST, pages 231-240. IEEE, 2011.
20. W. Dou, L. Yu, X. Wang, Z. Ma, and W. Ribarsky. Hierarchicaltopics: Visually exploring large text collections using topic hierarchies. IEEE TVCG, 19(12):2002-2011, 2013.
21. X. Gao, B. Xiao, D. Tao, and X. Li. A survey of graph edit distance. Pattern Analysis and applications, 13(1):113-129, 2010.
22. M. Gleicher, D. Albers, R. Walker, I. Jusufi, C. D. Hansen, and J. C. Roberts. Visual comparison for information visualization. Information Visualization, 10(4):289-309, 2011.
23. M. Hascoet and P. Dragicevic. Interactive graph matching and visual comparison of graphs and clustered graphs. In AVI, pages 522-529, 2012.
24. S. Havre, E. G. Hetzler, P. Whitney, and L. T. Nowell. Themeriver: visualizing thematic changes in large document collections. IEEE TVCG, 8(1):9-20, 2002.
25. N. Henry, J. Fekete, and M. J. McGuffin. Nodetrix: a hybrid visualization of social networks. IEEE TVCG, 13(6):1302-1309, 2007.
26. J. Intriligator and P. Cavanagh. The spatial resolution of visual attention. Cognitive psychology, 43(3):171-216, 2001.
27. T. Kamada and S. Kawai. An algorithm for drawing general undirected graphs. Information processing letters, 31(1):7-15, 1989.
28. G. A. Korsah, A. T. Stentz, and M. B. Dias. The dynamic hungarian algorithm for the assignment problem with changing costs. Technical Report CMU-RI-TR-07-27, July 2007.
29. G. Kumar and M. Garland. Visual exploration of complex time-varying graphs. IEEE TVCG, 12(5):805-812, 2006.
30. O. D. Lampe and H. Hauser. Interactive visualization of streaming data with kernel density estimation. In PacificVis, pages 171-178, 2011.
31. S. Liu, W. Cui, Y. Wu, and M. Liu. A survey on information visualization: recent advances and challenges. The Visual Computer, pages 1-21, 2014.
32. S. Liu, M. X. Zhou, S. Pan, Y. Song, W. Qian, W. Cai, and X. Lian. Tiara: Interactive, topic-based visual text summarization and analysis. ACM TIST, 3(2):25, 2012.
33. X. Liu, Y. Song, S. Liu, and H. Wang. Automatic taxonomy construction from keywords. In KDD, pages 1433-1441, 2012.
34. A. M. MacEachren, R. E. Roth, J. O'Brien, B. Li, D. Swingley, and M. Gahegan. Visual semiotics &uncertainty visualization: An empirical study. IEEE TVCG, 18(12):2496-2505, 2012.
35. P. McLachlan, T. Munzner, E. Koutsofios, and S. North. Liverac: interactive visual exploration of system management time-series data. In CHI, pages 1483-1492, 2008.
36. J. Munkres. Algorithms for the assignment and transportation problems. Journal of the Society for Industrial &Applied Mathematics, 5(1):32-38, 1957.
37. T. Munzner. A nested process model for visualization design and validation. IEEE TVCG, 15(6):921-928, 2009.
38. T. Munzner, F. Guimbretiere, S. Tasiran, L. Zhang, and Y. Zhou. Treejuxtaposer: scalable tree comparison using focus+ context with guaranteed visibility. In ACM TOG, volume 22, pages 453-462, 2003.
39. R. Myers, R. Wison, and E. R. Hancock. Bayesian graph edit distance. IEEE PAMI, 22(6):628-635, 2000.
40. M. Neuhaus and H. Bunke. A convolution edit kernel for error-tolerant graph matching. In ICPR, volume 4, pages 220-223, 2006.
41. A. Ribalta and F. Serratosa. On the computation of the common labelling of a set of attributed graphs. In CIARP, pages 137-144, 2009.
42. A. Ribalta and F. Serratosa. Models and algorithms for computing the common labelling of a set of attributed graphs. Computer Vision and Image Understanding, 115(7):929-945, 2011.
43. K. Riesen and H. Bunke. Approximate graph edit distance computation by means of bipartite graph matching. Image Vision Comput., 27(7):950-959, 2009.
44. K. Riesen, X. Jiang, and H. Bunke. Exact and inexact graph matching: Methodology and applications. In Managing and Mining Graph Data, pages 217-247. 2010.
45. K. Salomatin, Y. Yang, and A. Lad. Multi-field correlated topic modeling. In SDM, pages 628-637, 2009.
46. R. R. Sambasivan, I. Shafer, M. L. Mazurek, and G. R. Ganger. Visualizing request-flow comparison to aid performance diagnosis in distributed systems. IEEE TVCG, 19(12):2466-2475, 2013.
47. P. N. Suganthan, E. K. Teoh, and D. P. Mital. Pattern recognition by graph matching using the potts mft neural networks. Pattern Recognition, 28(7):997-1009, 1995.
48. G. Sun, Y. Wu, R. Liang, and S. Liu. A survey of visual analytics techniques and applications: State-of-The-art research and future challenges. Journal of Computer Science and Technology, 28(5):852-867, 2013.
49. G. Sun, Y. Wu, S. Liu, T.-Q. Peng, J. J. H. Zhu, and R. Liang. EvoRiver: Visual analysis of topic coopetition on social media. To appear in IEEE TVCG, 2014.
50. C. Vehlow, T. Reinhardt, and D. Weiskopf. Visualizing fuzzy overlapping communities in networks. IEEE TVCG, 19(12):2486-2495, 2013.
51. T. Von Landesberger, A. Kuijper, T. Schreck, J. Kohlhammer, J. J. van Wijk, J.-D. Fekete, and D. W. Fellner. Visual analysis of large graphs: State-of-The-art and future research challenges. Computer graphics forum, 30(6):1719-1749, 2011.
52. X. Wang, S. Liu, Y. Song, and B. Guo. Mining evolutionary multi-branch trees from text streams. In KDD, pages 722-730, 2013.
53. M. L.Williams, R. C.Wilson, and E. R. Hancock. Multiple graph matching with bayesian inference. Pattern Recognition Letters, 18(11-13):1275-128, 1997.
54. R. C. Wilson and E. R. Hancock. Structural matching by discrete relaxation. IEEE PAMI, 19(6):634-648, 1997.
55. R. C. Wilson, E. R. Hancock, and B. Luo. Pattern vectors from algebraic graph theory. IEEE PAMI, 27(7):1112-1124, 2005.
56. Y. Wu, F. Wei, S. Liu, N. Au, W. Cui, H. Zhou, and H. Qu. Opinionseer: Interactive visualization of hotel customer feedback. IEEE TVCG, 16(6):1109-1118, 2010.
57. Y. Wu, G.-X. Yuan, and K.-L. Ma. Visualizing flow of uncertainty through analytical processes. IEEE TVCG, 18(12):2526-2535, 2012.
58. P. Xu, Y. Wu, E. Wei, T.-Q. Peng, S. Liu, J. J. H. Zhu, and H. Qu. Visual analysis of topic competition on social media. IEEE TVCG, 19(12):2012-2021, 2013.
59. J. Yan, Y. Tian, H. Zha, X. Yang, Y. Zhang, and S. M. Chu. Joint optimization for consistent multiple graph matching. In ICCV, pages 1649-1656, 2013.
60. S. Yantis. Multielement visual tracking: Attention and perceptual organization. Cognitive psychology, 24(3):295-340, 1992.
61. J. Zhang, Y. Song, C. Zhang, and S. Liu. Evolutionary hierarchical dirichlet processes for multiple correlated time-varying corpora. In KDD, pages 1079-1088, 2010.