An adaptive parameter space-filling algorithm for highly interactive cluster exploration

IEEE Conference on Visual Analytics Science and Technology 2012, VAST 2012 - Proceedings

Volumn , Issue , 2012, Pages 13-22

  Ahmed, Zafar ^a   Weaver, Chris ^a  

^a University of Oklahoma   (United States)

Author keywords

D.2.2 Software Engineering : Design Tools and Techniques User Interfaces ; H.2.3 Information Systems : Database Management Languages ; H.5.2 Information Systems : Information Interfaces and Presentation User Interfaces

Indexed keywords

ADAPTIVE PARAMETERS; BEST-EFFORT; CLUSTER STRUCTURE; CLUSTERING RESULTS; DATABASE MANAGEMENT; DESIGN TOOLS AND TECHNIQUES; DYNAMIC QUERY; EXACT RESULTS; INFORMATION INTERFACES; INTERACTION POINTS; K-MEANS CLUSTERING; METEOROLOGICAL DATA; MOTION PARALLAX; MULTIDIMENSIONAL CLUSTERING; MULTIDIMENSIONAL DATA; NEAREST NEIGHBORS; OVERLAPPING DATA; PARAMETER SPACES; PERFORMANCE STUDY; PREFETCHING TECHNIQUES; QUERY RESULTS; RULE OF THUMB; SPACE-FILLING; TIME RANGE; TIME-SERIES DATA; USER INTERACTION; VISUALIZATION SYSTEM; VISUALIZATION TOOLS;

CLUSTERING ALGORITHMS; GEOMETRICAL OPTICS; GRAPHICAL USER INTERFACES; INFORMATION SYSTEMS; METEOROLOGY; SOFTWARE ENGINEERING;

VISUALIZATION;

EID: 84872982572     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/VAST.2012.6400493     Document Type: Conference Paper

References (31)

1. C. Ahlberg, C.Williamson, and B. Shneiderman. Dynamic queries for information exploration: An implementation and evaluation. In Proceedings of the Conference on Human Factors in Computing Systems (CHI), pages 619-626, Monterey, CA, May 1992. ACM.
2. Z. Ahmed, P. Yost, A. McGovern, and C.Weaver. Steerable clustering for visual analysis of ecosystems. In S. Miksch and G. Santucci, editors, Proceedings of the International Workshop on Visual Analytics (EuroVA), pages 49-52, Bergen, Norway, June 2011. The Eurographics Association.
3. G. Andrienko and N. Andrienko. Interactive cluster analysis of diverse types of spatiotemporal data. SIGKDD Explorations Newsletter, 11(2):19-28, 2009.
4. M. Ankerst, S. Berchtold, and D. A. Keim. Similarity clustering of dimensions for an enhanced visualization of multidimensional data. In Proceedings of the IEEE Symposium on Information Visualization (InfoVis), page 52, Research Triangle Park, NC, 1998. IEEE Computer Society.
5. D. Baldocchi, E. Falge, L. Gu, R. Olson, D. Hollinger, S. Running, P. Anthoni, C. Bernhofer, K. Davis, R. Evans, J. Fuentes, A. Goldstein, G. Katul, B. Law, X. Lee, Y. Malhi, T. Meyers, W. Munger, W. Oechel, K. T. Paw, K. Pilegaard, H. P. Schmid, R. Valentini, S. Verma, T. Vesala, K. Wilson, and S. Wofsy. FLUXNET: A new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide, water vapor, and energy flux densities. Bulletin of the American Meteorological Society, 82(11):2415-2434, 2001.
6. N. Cao, D. Gotz, J. Sun, and H. Qu. DICON: Interactive visual analysis of multidimensional clusters. IEEE Transactions on Visualization and Computer Graphics, 17(12):2581-2590, December 2011.
7. S.-M. Chan, L. Xiao, J. Gerth, and P. Hanrahan. Maintaining interactivity while exploring massive time series. In Proceedings of the IEEE Symposium on Visual Analytics Science and Technology (VAST), pages 59-66, Columbus, OH, October 2008. IEEE.
8. K. Chen and L. Liu. iVIBRATE: Interactive visualization-based framework for clustering large datasets. ACM Transactions on Information Systems, 24(2):245-294, April 2006.
9. J. Choo, S. Bohn, and H. Park. Two-stage framework for visualization of clustered high dimensional data. In Proceedings of the IEEE Symposium on Visual Analytics Science and Technology (VAST), pages 67-74, Atlantic City, NJ, October 2009. IEEE.
10. W. T. Correa, J. T. Klosowski, and C. T. Silva. Visibility-based prefetching for interactive out-of-core rendering. In Proceedings of the IEEE Symposium on Parallel and Large-Data Visualization and Graphics, Seattle, WA, October 2003. IEEE Computer Society.
11. K. C. Crawford, F. V. Brock, R. L. Elliott, G.W. Cuperus, S. J. Stadler, H. L. Johnson, and C. A. Doswell. The Oklahoma mesonetwork - a 21st century project. In Proceedings of the 8th International Conference on Interactive Information and Processing Systems for Meteorology, Oceanography, and Hydrology, pages 27-33, Atlanta, GA, January 1992. American Meteorological Society.
12. P. R. Doshi, E. A. Rundensteiner, and M. O. Ward. Prefetching for visual data exploration. In Proceedings of the Eighth International Conference on Database Systems for Advanced Applications (DASFAA), Washington, DC, USA, 2003. IEEE Computer Society.
13. A. Gerndt, B. Hentschel, M. Wolter, T. Kuhlen, and C. Bischof. VIRACOCHA: An efficient parallelization framework for large-scale CFD post-processing in virtual environments. In Proceedings of the 2004 ACM/IEEE Conference on Supercomputing, Pittsburgh, PA, 2004. IEEE Computer Society.
14. D. Guo, J. Chen, A. M. MacEachren, and K. Liao. A visualization system for space-time and multivariate patterns (VIS-STAMP). IEEE Transactions on Visualization and Computer Graphics, 12(6):1461-1474, November/December 2006.
15. P. Jaccard. Distribution de la florine alpine dans la bassin de dranses et dans quelques regiones voisines. Bulletin de la Societe Vaudoise des Sciences Naturelles, 37:241-272, 1901.
16. B. Jeong, P. A. Navrátil, K. P. Gaither, G. Abram, and G. P. Johnson. Configurable data prefetching scheme for interactive visualization of large-scale volume data. In Proceedings of SPIE (Visualization and Data Analysis), volume 8294, January 2012.
17. D. H. Jeong, A. Darvish, K. Najarian, J. Yang, and W. Ribarsky. Interactive visual analysis of time-series microarray data. The Visual Computer, 24(12):1053-1066, October 2008.
18. D. Joseph and D. Grunwald. Prefetching using Markov predictors. In Proceedings of the 24th Annual International Symposium on Computer Architecture (ISCA), pages 252-263, Denver, Colorado, 1997. ACM.
19. D. A. Keim. Information visualization and visual data mining. IEEE Transactions on Visualization and Computer Graphics, 8(1):100-107, 2002.
20. P. Krishnan and J. S. Vitter. Optimal prediction for prefetching in the worst case. SIAM Journal on Computing, 27(6):1617-1636, 1998.
21. D. R. Lipsa, R. D. Bergeron, T. M. Sparr, and R. S. Laramee. Dynamic chunking for out-of-core volume visualization applications. In Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II (ISVC), pages 117-128, Las Vegas, Nevada, 2009. Springer-Verlag.
22. X. Ma, M. Winslett, J. Norris, X. Jiao, and R. Fiedler. Godiva: Lightweight data management for scientific visualization. In Proceedings of the 20th International Conference on Data Engineering (ICDE), pages 434-447. IEEE Computer Society, 2004.
23. E. J. Nam, Y. Han, K. Mueller, A. Zelenyuk, and D. Imre. Clustersculptor: A visual analytics tool for high-dimensional data. In Proceedings of the IEEE Symposium on Visual Analytics Science and Technology (VAST), pages 75-82, Sacramento, CA, October 30-November 1 2007. IEEE.
24. R. H. Patterson, G. A. Gibson, E. Ginting, D. Stodolsky, and J. Zelenka. Informed prefetching and caching. In Proceedings of the Fifteenth ACM Symposium on Operating Systems Principles (SIGOPS), pages 79-95, Copper Mountain, Colorado, 1995. ACM.
25. G. Peano. Sur une courbe, qui remplit toute une aire plane. Mathamatische Annalen, 36(1):157-160, 1890.
26. 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, Boulder, CO, September 1996. IEEE.
27. J. J. Thomas and K. A. Cook, editors. Illuminating the Path: The Research and Development Agenda for Visual Analytics. IEEE Computer Society, August 2005.
28. M. O. Ward. XmdvTool: Integrating multiple methods for visualizing multivariate data. In Proceedings of the IEEE Conference on Visualization (VIS), pages 326-333. IEEE Computer Society Press, 1994.
29. C. Weaver. Building highly-coordinated visualizations in Improvise. In Proceedings of the IEEE Symposium on Information Visualization (InfoVis), pages 159-166, Austin, TX, October 2004. IEEE Computer Society.
30. K.Wu,W. Koegler, J. Chen, and A. Shoshani. Using bitmap index for interactive exploration of large datasets. In Proceedings of the 15th International Conference on Scientific and Statistical Database Management (SSDBM), pages 65-74, Cambridge, MA, July 2003. IEEE Computer Society.
31. J. S. Yi, Y. ah Kang, J. T. Stasko, and J. A. Jacko. Toward a deeper understanding of the role of interaction in information visualization. IEEE Transactions on Visualization and Computer Graphics, 13(6):1224-1231, November/December 2007.