Web Application for Large-Scale Multidimensional Data Visualization

References

• M . Baravykaitė , R . Č iegis and J . Žilinskas . Template realization of generalized branch and bound algorithm . Math. Model. Anal ., 10 3 217 – 236 , 2005 . doi: 10.1080/13926292.2005.9637283 .
   Google Scholar
• J . Bernatavičienė , G . Dzemyda , O . Kurasova , V . Marcinkevičius and V . Medvedev . The problem of visual analysis of multidimensional medical data . Optimization and Its Applications , 4 : 277 – 298 , 2007 . doi: 101007/978-0-387-36721-717
   Google Scholar
• Booth , D. , Haas , H. , McCabe , F. , Newcomer , E. , Champion , M. , Ferris , C. and Orchard , D. 2004 . Web service architecture , W3C Working Group Note .
   Google Scholar
• Borg , I. and Groenen , J.P. 2005 . Modern Multidimensional Scaling: Theory and Applications, second ed , Springer, New York .
   Google Scholar
• R . Čiegis , A . Jakušev , A . Krylovas and O . Suboč . Parallel algorithms for solution of nonlinear diffusion problems in image smoothing . Math. Model. Anal ., 10 2 155 – 172 , 2005 . doi: 10.1080/13926292.2005.9637279
   Google Scholar
• V . de Silva and J.B . Tenenbaum . Global versus local methods for nonlinear dimensionality reduction . Advances in Neural Information Processing Systems , 15 : 721 – 728 , 2003 .
   Google Scholar
• G . Dzemyda . Visualization of a set of parameters characterized by their correlation matrix . Computational Statistics and Data Analysis , 36 10 15 – 30 , 2001 . doi: 10.1016/S0167-9473(00)00030-X
   Google Scholar
• G . Dzemyda , O . Kurasova and V . Medvedev . Dimension reduction and data visualization using neural networks . In Emerging Artificial Intelligence Applications in Computer Engineering – Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies, volume 160 of Frontiers Artificial Intelligence Appl ., pp. 25 – 49 , 2007 .
   Google Scholar
• A . Frank and A . Asuncion . UCI Machine Learning Repository . University of California, School of Information and Computer Science, Irvine, CA, 2010. Available from Internet: http://archive.ics.uci.edu/ml.
   Google Scholar
• P.J.F . Groenen and M . van de Vaelden . Multidimensional scaling . Econometric InstituteReport EI2004-15 , 2004 .
   Google Scholar
• Hagel , J. 2002 . Edging into Web services . Quarterly , 4 : 29 – 38 .
   Google Scholar
• J . Handl and J . Knowles . Cluster generators for large high-dimensional data sets with large numbers of clusters, 2005 . Available from Internet: http://dbkgroup.org/handl/generators/.
   Google Scholar
• R . Karbauskaitė and G . Dzemyda . Topology preservation measures in the visualization of manifold-type multidimensional data . Informatica , 20 2 235 – 254 , 2009
   Google Scholar
• Khan , K.M. 2008 . Managing Web Service Quality: Measuring Outcomes and Effectiveness, Information Science Reference , Qatar University, Qatar .
   Google Scholar
• H . Klock and J. M . Buhmann . Data visualization by multidimensional scaling: A deterministic annealing approch . Pattern Recognition , 33 4 651 – 669 , 1999 . doi: 10.1016/S0031-3203(99)00078-3 .
   Google Scholar
• T . Kohonen . Self-Organizing Maps, third ed . Springer , 2001 .
   Google Scholar
• V . Marcinkevičius . Investigation and Functionality Improvement of Nonlinear Multidimensional Data Projection Methods . Kauno technologijos universiteto spaustuvė, Vilnius , 2010 . in Lithuanian, PhD thesis
   Google Scholar
• Mathar , R. and Žilinskas , A. 2001 . On global optimization in two-dimensional scaling Acta Appl. Math. , 33 : 57 – 64 .
   Google Scholar
• A . Morrison , G . Ross and M . Chalmers . Fast multidimensional scaling through sampling, springs and interpolation . Information Visualization , 2 1 68 – 77 , 2003 . doi: 10.1057/palgrave.ivs.9500040 .
   Google Scholar
• A . Naud and W . Duch . Interactive data exploration using MDS mapping . In Proceedingsof the Fifth Conference: Neural Networks and Soft Computing , pp. 255 – 260 , 2000 .
   Google Scholar
• W.M . Trosset and P.J . Groenen . Multidimensional scaling algorithms for large data sets interactive data exploration using MDS mapping . In Proccedings of the Computing Science and Statistics , 2005 .
   Google Scholar
• M . Williams and T . Munzner . Steerable, progressive multidimensional scaling . In Information Visualization, 2004 , INFOVIS 2004. IEEE Symposium , pp. 57 – 64 , 2004 .
   Google Scholar
• E.K . Zavadskas , A . Kaklauskas , Z . Turskis and J . Tamošaitienė . Multi-attribute decision-making model by applying grey numbers . Informatica , 20 2 305 – 320 , 2009 .
   Web of Science ®Google Scholar