Automatic generation of co-embeddings from relational data with adaptive shaping

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 35, Issue 10, 2013, Pages 2340-2356

  Mu, Tingting ^a   Goulermas, John Yannis ^a  

^a UNIVERSITY OF LIVERPOOL   (United Kingdom)

Author keywords

data co embedding; data visualization; heterogeneous embedding; Relational data; structural matching

Indexed keywords

AUTOMATIC GENERATION; DATA CO-EMBEDDING; HETEROGENEOUS EMBEDDING; LOW-DIMENSIONAL SPACES; QUALITATIVE ANALYSIS; QUANTITATIVE ASSESSMENTS; RELATIONAL DATA; STRUCTURAL MATCHING;

ALGORITHMS; DATA VISUALIZATION;

IMAGE MATCHING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; PROCEDURES;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; IMAGE INTERPRETATION, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84883186360     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2013.66     Document Type: Article

References (37)

1. H. Zhong, J. Shi, and M. Visontai, "Detecting Unusual Activity in Video," Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. 2, pp. 819-826, 2004.
2. T. Iwata, K. Saito, N. Ueda, S. Stromsten, T.L. Griffiths, and J.B. Tenenbaum, "Parametric Embedding for Class Visualization," Neural Computation, vol. 19, no. 9, pp. 2536-2556, 2007.
3. A. Globerson, G. Chechik, F. Pereira, and N. Tishby, "Euclidean Embedding of Co-Occurrence Data," J. Machine Learning Research, vol. 8, pp. 2265-2295, 2007. (Pubitemid 350046197)
4. V. Sindhwani and P. Melville, "Document-Word Co-Regularization for Semi-Supervised Sentiment Analysis," Proc. Eighth IEEE Int'l Conf. Data Mining, pp. 1025-1030, 2008.
5. L.J.P. van der Maaten, E.O. Postma, and H.J. van den Herik, "Dimensionality Reduction: A Comparative Review," Technical Report TiCC-TR 2009-005, Tilburg Univ., 2009.
6. T.F. Cox and M.A.A. Cox, Multidimensional Scaling. Chapman and Hall, 2000.
7. I.S. Dhillon, "Co-Clustering Documents and Words Using Bipartite Spectral Graph Partitioning," Proc. Seventh ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining, pp. 269-274, 2001.
8. A. Globerson, G. Chechik, F. Pereira, and N. Tishby, "Embedding Heterogeneous Data Using Statistical Models," Proc. 21st Nat'l Conf. Artificial Intelligence, 2006.
9. T. Iwata, K. Saito, N. Ueda, S. Stromsten, T.L. Griffiths, and J.B. Tenenbaum, "Parametric Embedding for Class Visualization," Proc. Advances in Neural Information Processing Systems, 2005.
10. P. Sarkar, S.M. Siddiqi, and G.J. Gordon, "Approximate Kalman Filters for Embedding Author-Word Co-Occurrence Data over Time," Proc. 11th Int'l Conf. Statistical Network Analysis, pp. 126-139, 2006.
11. P. Sarkar, S.M. Siddiqi, and G.J. Gordon, "A Latent Space Approach to Dynamic Embedding of Co-Occurrence Data," Proc. 11th Int'l Conf. Artificial Intelligence and Statistics, 2007.
12. J.P. Benzecri, "L'Analyse des Donnees," L'Analyse des Correspondances, vol. 2, 1973.
13. M. Greenacre, Theory and Applications of Correspondence Analysis. Academic Press, 1983.
14. J.R. Bellegarda, "Latent Semantic Mapping," IEEE Signal Processing Magazine, vol. 22, no. 5, pp. 70-80, Sept. 2005. (Pubitemid 41488522)
15. M. Richardson and G.F. Kuder, "Making a Rating Scale That Measures," Personnel J., vol. 12, pp. 36-40, 1933.
16. H. Zha, X. He, C.H.Q. Ding, M. Gu, and H.D. Simon, "Bipartite Graph Partitioning and Data Clustering," Proc. 10th Int'l Conf. Information and Knowledge Management, pp. 25-32, 2001. (Pubitemid 34974610)
17. B. Gao, T. Liu, X. Zheng, Q. Cheng, and W. Ma, "Consistent Bipartite Graph Co-Partitioning for Star-Structured High-Order Heterogeneous Data Co-Clustering," Proc. 11th ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining, pp. 41-50, 2005. (Pubitemid 43218266)
18. B. Long, Z. Zhang, and P.S. Yu, "Co-Clustering by Block Value Decomposition," Proc. 11th ACM SIGKDD Int'l Conf. Knowledge Discovery in Data Mining, pp. 635-640, 2005. (Pubitemid 43218332)
19. B. Long, Z. Zhang, X. Wu, and P.S. Yu, "Spectral Clustering for Multi-Type Relational Data," Proc. 23rd Int'l Conf. Machine Learning, pp. 585-592, 2006.
20. M. Rege, M. Dong, and F. Fotouhi, "Bipartite Isoperimetric Graph Partitioning for Data Co-Clustering," Data Mining and Knowledge Discovery, vol. 16, no. 3, pp. 276-312, 2008.
21. C.E. Bichot, "Co-Clustering Documents and Words by Minimizing the Normalized Cut Objective Function," J. Math. Modelling and Algorithms, vol. 9, no. 2, pp. 131-147, 2010.
22. S. Deerwester, S.T. Dumais, G.W. Furnas, T.K. Landauer, and R. Harshman, "Indexing by Latent Semantic Analysis," J. Am. Soc. for Information Science, vol. 41, pp. 391-407, 1990.
23. A. Globerson, G. Chechik, F. Pereira, and N. Tishby, "Euclidean Embedding of Co-Occurrence Data," Proc. Advances in Neural Information Processing Systems, 2004.
24. F.W. Young, ViSta: The Visual Statistics System. Wiley, 1996.
25. P.M. Yelland, "An Introduction to Correspondence Analysis," Math. J., vol. 12, 2010.
26. M. Greenacre, "Power Transformations in Correspondence Analysis," Computational Statistics and Data Analysis, vol. 53, no. 8, pp. 3108-3116, 2009.
27. U. Luxburg, "A Tutorial on Spectral Clustering," Statistics and Computing, vol. 17, no. 4, pp. 395-416, 2007.
28. T. Mu, J.Y. Goulermas, J. Tsujii, and S. Ananiadou, "Proximity-Based Frameworks for Generating Embeddings from Multi-Output Data," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 34, no. 11, pp. 2216-2232, Nov. 2012.
29. W.S. Torgerson, "Multidimensional Scaling: I. Theory and Method," J. Psychometrika, vol. 17, no. 4, pp. 401-419, 1952.
30. C. Eckart and G. Young, "The Approximation of One Matrix by Another of Lower Rank," Psychometrika, vol. 1, no. 3, pp. 211-218, 1936.
31. B. Xie, M. Wang, and D. Tao, "Toward the Optimization of Normalized Graph Laplacian," IEEE Trans. Neural Networks, vol. 22, no. 4, pp. 660-666, Apr. 2011.
32. N. Cristianini, J. Kandola, A. Elisseeff, and J. Shawe-Taylor, "On Optimizing Kernel Alignment," Technical Report NC-TR-01-087, Royal Holloway Univ. of London, 2001.
33. UCI Machine Learning Repository, http://www.ics.uci.edu/ mlearn/MLRepository.html, 1992.
34. M. Hahsler, K. Hornik, and C. Buchta, "Getting Things in Order: An Introduction to the R Package Seriation," J. Statistical Software, vol. 25, no. 3, pp. 1-34, 2008.
35. H. Wu, Y. Tien, and C. Chen, "GAP: A Graphical Environment for Matrix Visualization and Cluster Analysis," Computational Statistics and Data Analysis, vol. 54, no. 3, pp. 767-778, 2010.
36. J.C. Bezdek, R.J. Hathaway, and J.M. Huband, "Visual Assessment of Clustering Tendency for Rectangular Dissimilarity Matrices," IEEE Trans. Fuzzy Systems, vol. 15, no. 5, pp. 890-903, Oct. 2007. (Pubitemid 47577996)
37. UCI, DELVE, and STATLOG Benchmark Repository, http:// ida.first.fhg.de/projects/bench/benchmarks.htm, 2013.