ApproxCCA: An approximate correlation analysis algorithm for multidimensional data streams

Knowledge-Based Systems

Volumn 24, Issue 7, 2011, Pages 952-962

  Wang, Yongli ^a   Zhang, Gongxuan ^a   Qian, Jiang Bo ^b  

^a NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^b NINGBO UNIVERSITY   (China)

Author keywords

Approximation; Canonical correlation analysis; Multidimensional data streams; Probability and statistics; Unequal probability sampling

Indexed keywords

APPROXIMATION; CANONICAL CORRELATION ANALYSIS; MULTIDIMENSIONAL DATA; PROBABILITY AND STATISTICS; UNEQUAL PROBABILITY SAMPLING;

ALGORITHMS; COMPUTATIONAL EFFICIENCY; COVARIANCE MATRIX; DATA COMMUNICATION SYSTEMS; PROBABILITY; SPEECH RECOGNITION;

CORRELATION METHODS;

EID: 79959713469     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.knosys.2011.04.003     Document Type: Article

References (27)

1. B. Ahmet, K.S. Ambuj, STARDUST: fast stream indexing using incremental wavelet approximations, in: Proceedings of the 29th VLDB Conference, Berlin, Germany, 2003.
2. S. Mehmet. Detecting Time Correlations in Time-Series Data Streams, Tech Report, Intelligent Enterprise Technologies Laboratory. < www.hpl.hp.com/techreports/2004/HPL-2004-103.html >.
3. Kamalika Chaudhuri, Sham M. Kakade, Karen Livescu, Karthik Sridharan, Multi-view clustering via canonical correlation analysis, in: Proceedings of the 26th International Conference on Machine Learning, Montreal, Canada, 2009.
4. Jiansheng Huang, Jeffrey F. Naughton, k-Relevance: a spectrum of relevance for data sources impacting a query, in: SIGMOD'07, Beijing, China, 2007.
5. S. Guha, D. Gunopulos, N. Koudas, Correlating synchronous and asynchronous data streams, in: The ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD 2003), Washington, DC, USA, August 24-27, 2003, pp. 529-534.
6. D. Achlioptas, F. McSherry, Fast computation of low rank approximations, in: Proceedings of the 33rd Annual Symposium on Theory of Computing (STOC2001), July 6-8, ACM Press, Heraklion, Crete, Greece, 2001, pp. 611-618. (Pubitemid 32865778)
7. W.B. Johnson, and J. Lindenstrauss Extension of Lipshitz mapping into Hilbert space Contemporary Mathematics 26 1984 189 206
8. S. Muthukrishnan, Data streams: algorithms and applications, in: Proceedings of the Fourteenth Annual ACM-SIAM Symposium on Discrete Algorithms, Baltimore, Maryland, USA, January 12-14, 2003.
9. Zhong Xu, Kaiyuan Zhang, and Quan Lu The Concise Tutorial of Matrix Theory 2002 Science Press Beijing pp. 24-27 (in Chinese)
10. R.A. Johnson, and D.W. Wichern Applied Multivariate Statistical Analysis 3rd ed. 1992 Prentice Hall, Inc. (Chapter 4)
11. A. Frieze, K. Ravi, V. Santosh, Fast Monte-Carlo Algorithms for finding low-rank approximations, in: Proceedings of the 39th Annual Symposium on Foundations of Computer Science, November, August 11, 1998, p. 370.
12. M. Borga, Learning "Multidimensional Signal Processing", PhD Thesis, Dissertation No 531, LinkÖping University, LinkÖping, Sweden, 1998, ISBN 91-7219-202-X.
13. NASDAQ historical stock exchange data. < http://www.eoddata.com/ download.asp >.
14. S&P500 historical stock exchange data. http://kumo.swcp.com/stocks.
15. R.Y. Chou, N. Liu, C.C. Wu, Forecasting correlation and covariance with a range-based dynamic conditional correlation model, Financial Engineering and Risk Management Workshop, Shanghai, 2005.
16. Y. Sakurai, S. Panadimitriou, J. Sun, C. Faloutsos, Braid: stream mining through group lag correlations, in: Proceedings of ACM SIGMOD, Baltimore, Maryland, 2005.
17. S. Papadimitriou, J. Sun, C. Faloutsos, Stream pattern discovery in multiple time series, in: Proceedings of VLDB, Trondheim, Norway, 2005.
18. Tiancheng Zhang, Dejun Yue, Yu Gu, Yi Wang, and Ge Yu Adaptive correlation analysis in stream time series with sliding windows Computers and Mathematics with Applications 57 6 2009 937 948
19. Akisato Kimura, Hirokazu Kameoka, Masashi Sugiyama, Takuho Nakano, Eisaku Maeda, Hitoshi Sakano, Katsuhiko Ishiguro, SemiCCA: efficient semi-supervised learning of canonical correlations, in: Proceedings of the 20th International Conference on Pattern Recognition, ICPR'2010, 2010, pp. 2933-2936.
20. Nicolle M. Correa, Tülay Adali, Yi-Ou Li, and Vince D. Calhoun Canonical correlation analysis for data fusion and group inferences IEEE Signal Processing Magazine 27 4 2010 30 50
21. Qinghua Hu, Jinfu Liu, and Daren Yu Mixed feature selection based on granulation and approximation Knowledge-Based Systems 21 4 2008 294 304 (Pubitemid 351608558)
22. Xiaoqing Weng, and Junyi Shen Detecting outlier samples in multivariate time series dataset Knowledge-Based Systems 21 8 2008 807 812
23. P. Drineas, R. Kannan, and M.W. Mahoney Fast Monte Carlo algorithms for matrices II: computing a low-rank approximation to a matrix SIAM Journal on Computing 36 2006 158 183 2004 (Pubitemid 46374022)
24. A. Deshpande, L. Rademacher, S. Vempala, G. Wang, Matrix approximation and projective clustering via volume sampling, in: Proceedings of the 17th ACM-SIAM Symposium on Discrete Algorithms (SODA), 2006.
25. Ju-Sheng Mi, Yee Leung, and Wei-Zhi Wu Approaches to attribute reduction in concept lattices induced by axialities Knowledge-Based Systems 23 6 2010 504 511
26. Izwan Nizal Mohd. Shaharanee, Fedja Hadzic, and Tharam S. Dillon Interestingness measures for association rules based on statistical validity Knowledge-Based Systems 24 3 2011 386 392
27. Charu C. Aggarwal, and Philip S. Yu A survey of uncertain data algorithms and applications IEEE Transactions on Knowledge and Data Engineering 21 5 2009 602 609