BIỂU DIỄN DỮ LIỆU NHIỀU CHIỀU TRONG KHÔNG GIAN BA CHIỀU
Abstract
Trong bài báo này, phương pháp động lực học phân tử (thường sử dụng tính toán trong nhiều hệ thống vật lý) phối hợp Multi-Dimensional Scaling(MDS) được sử dụng để giảm số chiều của dữ liệu nhằm mục tiêu thể hiện các phần tử dữ liệu trong không gian 3 chiều. Các thử nghiệm dựa trên phần mềm Matlab cho thấy kết quả trình bày trong bài báo đạt được khá tốt trong một số trường hợp. Tuy vậy cần có những tìm hiểu, nghiên cứu cũng như hoàn thiện hơn giải pháp do các tác giả đề nghịReferences
[1] D. Hand, H. Mannila and P. Smyth. “Principles of Data Mining”, The MIT Press, 2001, pp. 37-59.
[2] D. Jain and R.C. Dubes, ”Algorithms for Clustering Data”, Prentice-Hall, Advanced Reference Series, 1988, pp. 55-141.
[3] S. Theodoridis and K. Koutroumbas, ”Pattern Recognition”, 2nd Edition, Academic Press, San Diego-CA, 2003, pp. 506-556.
[4] M. Halkidi, Y. Batistakis, and M. Vazirgiannis, ”Cluster validity methods: part i”, ACM SIGMOD Record, 31(2), 2002, pp. 40-45.
[5] C. Urska, T. Marjan and J. Clifford, ”Neural-Network Enhanced Visualization of HighDimensional Data”, InTech, April 2010, pp. 145-165.
[6] W. Dzwinel, D.A. Yuen, K. Boryczko, Y. Ben-Zion, S. Yoshioka, and T. Ito, “Nonlinear multidimensional scaling and visualization of earthquake clusters over space, time and feature space”, Nonlinear Processes in Geophysics, 2005 (12), pp. 117-128.
[7] M. P. Allen, ”Introduction to Molecular Dynamics Simulation”, Computational Soft Matter: From Synthetic Polymers to Proteins,Lecture Notes, NIC Series, Vol. 23, ISBN 3- 00-012641-4, 2004, pp. 1-28.
[8] W. Dzwinel, “Virtual Particles and Search for Global Minimum”, Future Generation Computer Systems, 12, 1997, pp.371-389.
[9] M. Steyvers,”Multidimensional Scaling”, In: Encyclopedia of Cognitive Science. Nature Publishing Group, London, UK, 2002.
[10] J. B. Kruskal and M. Wish, “Multidimensional Scaling”, No. 07-011 in Sage University Paper,Series on Quantitative Applications in the Social Sciences, Sage Publications, Beverly Hills, 1978.
[11] J.B. Kruskal, “Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis”. Psychometrika 29, 1964, pp. 1–27 [Bell Telephone Laboratories, Murray Hill, NJ].
[12] R.Karbauskaitė and G.Dzemyda, “Multidimensional Data Projection Algorithms Saving Calculations of Distances”, Information Technology And Control, Kaunas, Technologija, Vol. 35, No. 1, 2006, pp. 57 - 64.
[13] H. Niemann and J. Weiss, “A fast converging algorithm for nonlinear mapping of highdimensional data to a plane”, IEEE Trans. Comput. C-28, 1979, pp. 142-147.
[14] M .A. Carreira-Perpinan, “A review of dimension reduction techniques”, Technical report CS-96-09, Department of Computer Science, University of Sheffield, UK, 1997.
[15] W. Dzwinel and J. Błasiak, “Method of particles in visual clustering of multi-dimensional and large data sets”, Future Generation Computer Systems 15, 1999, pp. 365–379.
[16] J. M. Haile, “Molecular Dynamics Simulation”, Wiley&Sons, New York, 1992, pp. 489.
[17] A. P. Dempster, N. M. Laird, and D. B. Rubin, “Maximum Likelihood from Incomplete Data via the EM Algorithm”, Annals of Statistics 39, 1977, pp. 1 – 38.
[18] David A. Yuen, et al., “Earthquake Clusters over Multi-dimensional Space, Visualization of”, 2009, pp. 2347-2371.
[2] D. Jain and R.C. Dubes, ”Algorithms for Clustering Data”, Prentice-Hall, Advanced Reference Series, 1988, pp. 55-141.
[3] S. Theodoridis and K. Koutroumbas, ”Pattern Recognition”, 2nd Edition, Academic Press, San Diego-CA, 2003, pp. 506-556.
[4] M. Halkidi, Y. Batistakis, and M. Vazirgiannis, ”Cluster validity methods: part i”, ACM SIGMOD Record, 31(2), 2002, pp. 40-45.
[5] C. Urska, T. Marjan and J. Clifford, ”Neural-Network Enhanced Visualization of HighDimensional Data”, InTech, April 2010, pp. 145-165.
[6] W. Dzwinel, D.A. Yuen, K. Boryczko, Y. Ben-Zion, S. Yoshioka, and T. Ito, “Nonlinear multidimensional scaling and visualization of earthquake clusters over space, time and feature space”, Nonlinear Processes in Geophysics, 2005 (12), pp. 117-128.
[7] M. P. Allen, ”Introduction to Molecular Dynamics Simulation”, Computational Soft Matter: From Synthetic Polymers to Proteins,Lecture Notes, NIC Series, Vol. 23, ISBN 3- 00-012641-4, 2004, pp. 1-28.
[8] W. Dzwinel, “Virtual Particles and Search for Global Minimum”, Future Generation Computer Systems, 12, 1997, pp.371-389.
[9] M. Steyvers,”Multidimensional Scaling”, In: Encyclopedia of Cognitive Science. Nature Publishing Group, London, UK, 2002.
[10] J. B. Kruskal and M. Wish, “Multidimensional Scaling”, No. 07-011 in Sage University Paper,Series on Quantitative Applications in the Social Sciences, Sage Publications, Beverly Hills, 1978.
[11] J.B. Kruskal, “Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis”. Psychometrika 29, 1964, pp. 1–27 [Bell Telephone Laboratories, Murray Hill, NJ].
[12] R.Karbauskaitė and G.Dzemyda, “Multidimensional Data Projection Algorithms Saving Calculations of Distances”, Information Technology And Control, Kaunas, Technologija, Vol. 35, No. 1, 2006, pp. 57 - 64.
[13] H. Niemann and J. Weiss, “A fast converging algorithm for nonlinear mapping of highdimensional data to a plane”, IEEE Trans. Comput. C-28, 1979, pp. 142-147.
[14] M .A. Carreira-Perpinan, “A review of dimension reduction techniques”, Technical report CS-96-09, Department of Computer Science, University of Sheffield, UK, 1997.
[15] W. Dzwinel and J. Błasiak, “Method of particles in visual clustering of multi-dimensional and large data sets”, Future Generation Computer Systems 15, 1999, pp. 365–379.
[16] J. M. Haile, “Molecular Dynamics Simulation”, Wiley&Sons, New York, 1992, pp. 489.
[17] A. P. Dempster, N. M. Laird, and D. B. Rubin, “Maximum Likelihood from Incomplete Data via the EM Algorithm”, Annals of Statistics 39, 1977, pp. 1 – 38.
[18] David A. Yuen, et al., “Earthquake Clusters over Multi-dimensional Space, Visualization of”, 2009, pp. 2347-2371.
Published
2015-12-18
How to Cite
LỆ, Đỗ Thị Bích et al.
BIỂU DIỄN DỮ LIỆU NHIỀU CHIỀU TRONG KHÔNG GIAN BA CHIỀU.
JBIS, [S.l.], dec. 2015.
Available at: <http://jbis.ueh.edu.vn/index.php/TSTHQL/article/view/78>. Date accessed: 27 apr. 2024.
Issue
Section
Bài viết
Keywords
Chia tỷ lệ đa chiều (Multi-Dimensional Scaling - MDS); Động lực học phân tử (molecular dynamics - MD)
