-
1
-
-
84858710111
-
A survey of clustering techniques
-
P. Rai, and S. Singh A survey of clustering techniques Int. J. Comput. Appl. 7 12 2010 1 5
-
(2010)
Int. J. Comput. Appl.
, vol.7
, Issue.12
, pp. 1-5
-
-
Rai, P.1
Singh, S.2
-
2
-
-
37349117256
-
On clustering multimedia time series data using k-means and dynamic time warping
-
V. Niennattrakul, C. Ratanamahatana, On clustering multimedia time series data using k-means and dynamic time warping, in: Proceedings of the International Conference on Multimedia and Ubiquitous Engineering, 2007, MUE '07, 2007, pp. 733-738.
-
(2007)
Proceedings of the International Conference on Multimedia and Ubiquitous Engineering, 2007, MUE '07
, pp. 733-738
-
-
Niennattrakul, V.1
Ratanamahatana, C.2
-
4
-
-
34247252483
-
Clustering multimedia data using time series
-
C. Ratanamahatana, V. Niennattrakul, Clustering multimedia data using time series, in: Proceedings of the International Conference on Hybrid Information Technology, 2006, ICHIT '06, 2006, pp. 372-379.
-
(2006)
Proceedings of the International Conference on Hybrid Information Technology, 2006, ICHIT '06
, pp. 372-379
-
-
Ratanamahatana, C.1
Niennattrakul, V.2
-
5
-
-
12244277019
-
Visually mining and monitoring massive time series
-
J. Lin, E. Keogh, S. Lonardi, J. Lankford, D. Nystrom, Visually mining and monitoring massive time series, in: Proceedings of 2004 ACM SIGKDD International Conference on Knowledge Discovery and data Mining - KDD '04, 2004, p. 460.
-
(2004)
Proceedings of 2004 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining - KDD '04
, pp. 460
-
-
Lin, J.1
Keogh, E.2
Lonardi, S.3
Lankford, J.4
Nystrom, D.5
-
6
-
-
0042711018
-
On the need for time series data mining benchmarks: A survey and empirical demonstration
-
E. Keogh, and S. Kasetty On the need for time series data mining benchmarks: a survey and empirical demonstration Data Min. Knowl. Discov. 7 4 2003 349 371
-
(2003)
Data Min. Knowl. Discov.
, vol.7
, Issue.4
, pp. 349-371
-
-
Keogh, E.1
Kasetty, S.2
-
7
-
-
84864270145
-
Visual query language: Finding patterns in and relationships among time series data
-
K. Haigh, W. Foslien, and V. Guralnik, Visual query language: finding patterns in and relationships among time series data, Seventh Workshop on Mining Scientific And Engineering Datasets, 2004, pp. 324-332.
-
(2004)
Seventh Workshop on Mining Scientific and Engineering Datasets
, pp. 324-332
-
-
Haigh, K.1
Foslien, W.2
Guralnik, V.3
-
8
-
-
26944478356
-
Segmenting time series: A survey and novel approach
-
E. Keogh, S. Chu, and D. Hart Segmenting time series: a survey and novel approach Data Min. Time Ser. Databases 57 1 2004 1 21
-
(2004)
Data Min. Time Ser. Databases
, vol.57
, Issue.1
, pp. 1-21
-
-
Keogh, E.1
Chu, S.2
Hart, D.3
-
9
-
-
33745781710
-
A symbolic representation of time series, with implications for streaming algorithms
-
J. Lin, E. Keogh, S. Lonardi, and B. Chiu, A symbolic representation of time series, with implications for streaming algorithms, in: Proceedings of 8th ACM SIGMOD Workshop on Research Issues Data Mining and Knowledge Discovery - DMKD '03, 2003, p. 2.
-
(2003)
Proceedings of 8th ACM SIGMOD Workshop on Research Issues Data Mining and Knowledge Discovery - DMKD '03
, pp. 2
-
-
Lin, J.1
Keogh, E.2
Lonardi, S.3
Chiu, B.4
-
10
-
-
84930651768
-
Mining massive archives of mice sounds with symbolized representations
-
J. Zakaria, S. Rotschafer, A. Mueen, K. Razak, E. Keogh, Mining massive archives of mice sounds with symbolized representations, in: SIGKDD, 2012, pp. 1-10.
-
(2012)
SIGKDD
, pp. 1-10
-
-
Zakaria, J.1
Rotschafer, S.2
Mueen, A.3
Razak, K.4
Keogh, E.5
-
11
-
-
84866037385
-
Searching and mining trillions of time series subsequences under dynamic time warping
-
T. Rakthanmanon, A.B. Campana, G. Batista, J. Zakaria, E. Keogh, Searching and mining trillions of time series subsequences under dynamic time warping, in: proceedings of the Conference on Knowledge Discovery and Data Mining, 2012, pp. 262-270.
-
(2012)
Proceedings of the Conference on Knowledge Discovery and Data Mining
, pp. 262-270
-
-
Rakthanmanon, T.1
Campana, A.B.2
Batista, G.3
Zakaria, J.4
Keogh, E.5
-
13
-
-
33646807766
-
A survey of temporal data mining
-
S. Laxman, and P.S. Sastry A survey of temporal data mining Sadhana 31 2 2006 173 198
-
(2006)
Sadhana
, vol.31
, Issue.2
, pp. 173-198
-
-
Laxman, S.1
Sastry, P.S.2
-
16
-
-
24044470614
-
Clustering of time series data - A survey
-
T. Warrenliao Clustering of time series data - a survey Pattern Recognit. 38 11 2005 1857 1874
-
(2005)
Pattern Recognit.
, vol.38
, Issue.11
, pp. 1857-1874
-
-
Warrenliao, T.1
-
17
-
-
84897906299
-
Recent techniques of clustering of time series data: A survey
-
S. Rani, and G. Sikka Recent techniques of clustering of time series data: a survey Int. J. Comput. Appl 52 15 2012 1 9
-
(2012)
Int. J. Comput. Appl
, vol.52
, Issue.15
, pp. 1-9
-
-
Rani, S.1
Sikka, G.2
-
19
-
-
84930616935
-
Time series as a point - A novel approach for time series cluster visualization
-
R. Kumar, P. Nagabhushan, Time series as a point - a novel approach for time series cluster visualization in: Proceedings of the Conference on Data Mining, 2006, pp. 24-29.
-
(2006)
Proceedings of the Conference on Data Mining
, pp. 24-29
-
-
Kumar, R.1
Nagabhushan, P.2
-
21
-
-
33749012790
-
Characteristic-based clustering for time series data
-
X. Wang, K. Smith, and R. Hyndman Characteristic-based clustering for time series data Data Min. Knowl. Discov. 13 3 2006 335 364
-
(2006)
Data Min. Knowl. Discov.
, vol.13
, Issue.3
, pp. 335-364
-
-
Wang, X.1
Smith, K.2
Hyndman, R.3
-
22
-
-
65549160361
-
Clustering time series data: An evolutionary approach
-
M. Chiş, S. Banerjee, and A.E. Hassanien Clustering time series data: an evolutionary approach Found. Comput. Intell. 6 1 2009 193 207
-
(2009)
Found. Comput. Intell.
, vol.6
, Issue.1
, pp. 193-207
-
-
Chiş, M.1
Banerjee, S.2
Hassanien, A.E.3
-
23
-
-
26444586342
-
Clustering of streaming time series is meaningless
-
J. Lin, E. Keogh, W. Truppel, Clustering of streaming time series is meaningless, in: Proceedings of 8th ACM SIGMOD Workshop on Research Issues Data Mining and Knowlegde Discovery DMKD 03, 2003, p. 56.
-
(2003)
Proceedings of 8th ACM SIGMOD Workshop on Research Issues Data Mining and Knowlegde Discovery DMKD 03
, pp. 56
-
-
Lin, J.1
Keogh, E.2
Truppel, W.3
-
24
-
-
84942742938
-
A simple dimensionality reduction technique for fast similarity search in large time series databases
-
E. Keogh, M. Pazzani, K. Chakrabarti, and S. Mehrotra A simple dimensionality reduction technique for fast similarity search in large time series databases Knowl. Inf. Syst. 1805 1 2000 122 133
-
(2000)
Knowl. Inf. Syst.
, vol.1805
, Issue.1
, pp. 122-133
-
-
Keogh, E.1
Pazzani, M.2
Chakrabarti, K.3
Mehrotra, S.4
-
26
-
-
33845236924
-
Unsupervised feature extraction for time series clustering using orthogonal wavelet transform
-
H. Zhang, T.B. Ho, Y. Zhang, and M.S. Lin Unsupervised feature extraction for time series clustering using orthogonal wavelet transform Informatica 30 3 2006 305 319
-
(2006)
Informatica
, vol.30
, Issue.3
, pp. 305-319
-
-
Zhang, H.1
Ho, T.B.2
Zhang, Y.3
Lin, M.S.4
-
27
-
-
0036372484
-
Clustering by pattern similarity in large data sets
-
H. Wang, W. Wang, J. Yang, P.P.S. Yu, Clustering by pattern similarity in large data sets, in: Proceedings of 2002 ACM SIGMOD International Conference Management data - SIGMOD '02, vol. 2, 2002, p. 394.
-
(2002)
Proceedings of 2002 ACM SIGMOD International Conference Management Data - SIGMOD '02
, vol.2
, pp. 394
-
-
Wang, H.1
Wang, W.2
Yang, J.3
Yu, P.P.S.4
-
28
-
-
77957873516
-
Rule discovery from time series
-
G. Das, K.I. Lin, H. Mannila, G. Renganathan, and P. Smyth Rule discovery from time series, Knowl. Discov. Data Min 98 1998 16 22
-
(1998)
Knowl. Discov. Data Min
, vol.98
, pp. 16-22
-
-
Das, G.1
Lin, K.I.2
Mannila, H.3
Renganathan, G.4
Smyth, P.5
-
29
-
-
1642281827
-
Pattern discovery from stock time series using self-organizing maps
-
T.C. Fu, F.L. Chung, V. Ng, R. Luk, Pattern discovery from stock time series using self-organizing maps, in: Workshop Notes of KDD2001 Workshop on Temporal Data Mining, 2001, pp. 26-29.
-
(2001)
Workshop Notes of KDD2001 Workshop on Temporal Data Mining
, pp. 26-29
-
-
Fu, T.C.1
Chung, F.L.2
Ng, V.3
Luk, R.4
-
30
-
-
52649179212
-
Probabilistic discovery of time series motifs
-
B. Chiu, E. Keogh, S. Lonardi, Probabilistic discovery of time series motifs, in: Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2003, pp. 493-498.
-
(2003)
Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
, pp. 493-498
-
-
Chiu, B.1
Keogh, E.2
Lonardi, S.3
-
31
-
-
0141463039
-
Finding surprising patterns in a time series database in linear time and space
-
E. Keogh, S. Lonardi, B.Y. Chiu, Finding surprising patterns in a time series database in linear time and space, in: Proceedings of the Eighth ACM SIGKDD, 2002, pp. 550-556.
-
(2002)
Proceedings of the Eighth ACM SIGKDD
, pp. 550-556
-
-
Keogh, E.1
Lonardi, S.2
Chiu, B.Y.3
-
33
-
-
84876028837
-
Assumption-free anomaly detection in time series
-
L. Wei, N. Kumar, V. Lolla, E. Keogh, Assumption-free anomaly detection in time series, in: Proceedings of the 17th International Conference on Scientific and Statistical Database Management, 2005, pp. 237-240.
-
(2005)
Proceedings of the 17th International Conference on Scientific and Statistical Database Management
, pp. 237-240
-
-
Wei, L.1
Kumar, N.2
Lolla, V.3
Keogh, E.4
-
34
-
-
70449093874
-
Time series representation for anomaly detection
-
M. Leng, X. Lai, G. Tan, X. Xu, Time series representation for anomaly detection, in: Proceedings of 2nd IEEE International Conference on Computer Science and Information Technology, 2009, ICCSIT 2009, 2009, pp. 628-632.
-
(2009)
Proceedings of 2nd IEEE International Conference on Computer Science and Information Technology, 2009, ICCSIT 2009
, pp. 628-632
-
-
Leng, M.1
Lai, X.2
Tan, G.3
Xu, X.4
-
35
-
-
84930648367
-
-
Technical Report, Österreichisches Forschungsinstitut für Artificial Intelligence, Wien, TR-2003-10, 2003
-
P.M. Polz, E. Hortnagl, E. Prem, Processing and Clustering Time Series of Mobile Robot Sensory Data. Technical Report, Österreichisches Forschungsinstitut für Artificial Intelligence, Wien, TR-2003-10, 2003, 2003.
-
(2003)
Processing and Clustering Time Series of Mobile Robot Sensory Data
-
-
Polz, P.M.1
Hortnagl, E.2
Prem, E.3
-
36
-
-
84860534755
-
A new method for abrupt dynamic change detection of correlated time series
-
W. He, G. Feng, Q. Wu, T. He, S. Wan, and J. Chou A new method for abrupt dynamic change detection of correlated time series, Int. J. Climatol. 32 10 2011 1604 1614
-
(2011)
Int. J. Climatol.
, vol.32
, Issue.10
, pp. 1604-1614
-
-
He, W.1
Feng, G.2
Wu, Q.3
He, T.4
Wan, S.5
Chou, J.6
-
37
-
-
2442474088
-
Time series forecasting with a hybrid clustering scheme and pattern recognition
-
A. Sfetsos, and C. Siriopoulos Time series forecasting with a hybrid clustering scheme and pattern recognition IEEE Trans. Syst. Man Cybern 34 3 2004 399 405
-
(2004)
IEEE Trans. Syst. Man Cybern
, vol.34
, Issue.3
, pp. 399-405
-
-
Sfetsos, A.1
Siriopoulos, C.2
-
38
-
-
70349334936
-
Financial forecasting through unsupervised clustering and neural networks
-
N. Pavlidis, V.P. Plagianakos, D.K. Tasoulis, and M.N. Vrahatis Financial forecasting through unsupervised clustering and neural networks Oper. Res. 6 2 2006 103 127
-
(2006)
Oper. Res.
, vol.6
, Issue.2
, pp. 103-127
-
-
Pavlidis, N.1
Plagianakos, V.P.2
Tasoulis, D.K.3
Vrahatis, M.N.4
-
39
-
-
71249094034
-
-
F. Ito, T. Hiroyasu, M. Miki, H. Yokouchi, Detection of Preference Shift Timing using Time-Series Clustering, 2009, pp. 1585-1590.
-
(2009)
Detection of Preference Shift Timing Using Time-Series Clustering
, pp. 1585-1590
-
-
Ito, F.1
Hiroyasu, T.2
Miki, M.3
Yokouchi, H.4
-
41
-
-
60349127820
-
Finding anomalous periodic time series
-
U. Rebbapragada, P. Protopapas, C.E. Brodley, and C. Alcock Finding anomalous periodic time series Mach. Learn. 74 3 2009 281 313
-
(2009)
Mach. Learn.
, vol.74
, Issue.3
, pp. 281-313
-
-
Rebbapragada, U.1
Protopapas, P.2
Brodley, C.E.3
Alcock, C.4
-
42
-
-
77956516272
-
Multiple gene expression profile alignment for microarray time-series data clustering
-
N. Subhani, L. Rueda, A. Ngom, and C.J. Burden Multiple gene expression profile alignment for microarray time-series data clustering Bioinformatics 26 18 2010 2281 2288
-
(2010)
Bioinformatics
, vol.26
, Issue.18
, pp. 2281-2288
-
-
Subhani, N.1
Rueda, L.2
Ngom, A.3
Burden, C.J.4
-
43
-
-
84867902634
-
Functional clustering of time series gene expression data by Granger causality
-
A. Fujita, P. Severino, K. Kojima, J.R. Sato, A.G. Patriota, and S. Miyano Functional clustering of time series gene expression data by Granger causality BMC Syst. Biol. 6 1 2012 137
-
(2012)
BMC Syst. Biol.
, vol.6
, Issue.1
, pp. 137
-
-
Fujita, A.1
Severino, P.2
Kojima, K.3
Sato, J.R.4
Patriota, A.G.5
Miyano, S.6
-
45
-
-
28644452470
-
Clustering short time series gene expression data
-
21
-
J. Ernst, G.J. Nau, and Z. Bar-Joseph Clustering short time series gene expression data Bioinforma. 21 Suppl. 1 2005 i159 i168 21
-
(2005)
Bioinforma.
, vol.21
, pp. i159-i168
-
-
Ernst, J.1
Nau, G.J.2
Bar-Joseph, Z.3
-
46
-
-
84897521088
-
Clustering gene expression regulators: New approach to disease subtyping
-
Mikhail Pyatnitskiy, I. Mazo, M. Shkrob, E. Schwartz, and E. Kotelnikova Clustering gene expression regulators: new approach to disease subtyping PLoS One 9 1 2014 e84955
-
(2014)
PLoS One
, vol.9
, Issue.1
, pp. e84955
-
-
Pyatnitskiy, M.1
Mazo, I.2
Shkrob, M.3
Schwartz, E.4
Kotelnikova, E.5
-
47
-
-
77952341882
-
Discovery of climate indices using clustering
-
M. Steinbach, P.N. Tan, V. Kumar, S. Klooster, and C. Potter, Discovery of climate indices using clustering, in: Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery And data Mining, 2003, pp. 446-455.
-
(2003)
Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
, pp. 446-455
-
-
Steinbach, M.1
Tan, P.N.2
Kumar, V.3
Klooster, S.4
Potter, C.5
-
48
-
-
84877276770
-
A dynamic fuzzy cluster algorithm for time series
-
M. Ji, F. Xie, and Y. Ping A dynamic fuzzy cluster algorithm for time series Abstr. Appl. Anal. 2013 2013 1 7
-
(2013)
Abstr. Appl. Anal.
, vol.2013
, pp. 1-7
-
-
Ji, M.1
Xie, F.2
Ping, Y.3
-
49
-
-
84901006073
-
Complex time series analysis of PM10 and PM2.5 for a coastal site using artificial neural network modelling and k-means clustering
-
M.A. Elangasinghe, N. Singhal, K.N. Dirks, J.A. Salmond, and S. Samarasinghe Complex time series analysis of PM10 and PM2.5 for a coastal site using artificial neural network modelling and k-means clustering Atmos. Environ. 94 2014 106 116
-
(2014)
Atmos. Environ.
, vol.94
, pp. 106-116
-
-
Elangasinghe, M.A.1
Singhal, N.2
Dirks, K.N.3
Salmond, J.A.4
Samarasinghe, S.5
-
50
-
-
0002182408
-
Cross-sectional approach for clustering time varying data
-
K. Košmelj, and V. Batagelj Cross-sectional approach for clustering time varying data J. Classif 7 1 1990
-
(1990)
J. Classif
, vol.7
, Issue.1
-
-
Košmelj, K.1
Batagelj, V.2
-
51
-
-
84874720586
-
Analysis of similarity measures in times series clustering for the discovery of building energy patterns
-
F. Iglesias, and W. Kastner Analysis of similarity measures in times series clustering for the discovery of building energy patterns Energies 6 2 2013 579 597
-
(2013)
Energies
, vol.6
, Issue.2
, pp. 579-597
-
-
Iglesias, F.1
Kastner, W.2
-
52
-
-
77954869144
-
Clustering time series of sea levels: Extreme value approach
-
M.G. Scotto, A.M. Alonso, and S.M. Barbosa Clustering time series of sea levels: extreme value approach J. Waterw. Port, Coastal, Ocean Eng. 136 4 2010 215 225
-
(2010)
J. Waterw. Port, Coastal, Ocean Eng.
, vol.136
, Issue.4
, pp. 215-225
-
-
Scotto, M.G.1
Alonso, A.M.2
Barbosa, S.M.3
-
53
-
-
0037905617
-
Time-frequency clustering and discriminant analysis
-
R.H.R. Shumway Time-frequency clustering and discriminant analysis Stat. Probab. Lett 63 3 2003 307 314
-
(2003)
Stat. Probab. Lett
, vol.63
, Issue.3
, pp. 307-314
-
-
Shumway, R.H.R.1
-
54
-
-
84888351444
-
Polarization of forecast densities: A new approach to time series classification
-
Shen Liu, E.A. Maharaj, and B. Inder Polarization of forecast densities: a new approach to time series classification Comput. Stat. Data Anal. 70 2014 345 361
-
(2014)
Comput. Stat. Data Anal.
, vol.70
, pp. 345-361
-
-
Liu, S.1
Maharaj, E.A.2
Inder, B.3
-
55
-
-
84895733474
-
Exploratory analysis of time series data: Detection of partial similarities, clustering, and visualization
-
Y. Sadahiro, and T. Kobayashi Exploratory analysis of time series data: detection of partial similarities, clustering, and visualization Comput. Environ. Urban Syst. 45 2014 24 33
-
(2014)
Comput. Environ. Urban Syst.
, vol.45
, pp. 24-33
-
-
Sadahiro, Y.1
Kobayashi, T.2
-
56
-
-
84901416218
-
Trend analysis using non-stationary time series clustering based on the finite element method
-
M. Gorji Sefidmazgi, M. Sayemuzzaman, A. Homaifar, M.K. Jha, and S. Liess Trend analysis using non-stationary time series clustering based on the finite element method Nonlinear Process. Geophys. 21 3 2014 605 615
-
(2014)
Nonlinear Process. Geophys.
, vol.21
, Issue.3
, pp. 605-615
-
-
Gorji Sefidmazgi, M.1
Sayemuzzaman, M.2
Homaifar, A.3
Jha, M.K.4
Liess, S.5
-
57
-
-
0242625246
-
Clustering seasonality patterns in the presence of errors
-
M. Kumar, N.R. Patel, Clustering seasonality patterns in the presence of errors, in: Proceedings of Eighth ACM SIGKDD, 2002, pp. 557-563.
-
(2002)
Proceedings of Eighth ACM SIGKDD
, pp. 557-563
-
-
Kumar, M.1
Patel, N.R.2
-
58
-
-
12244270853
-
Clustering time series from mixture polynomial models with discretised data
-
A.J. Bagnall, G. Janacek, B. De la Iglesia, M. Zhang, Clustering time series from mixture polynomial models with discretised data in: Proceedings of the Second Australasian Data Mining Workshop, 2003, pp. 105-120.
-
(2003)
Proceedings of the Second Australasian Data Mining Workshop
, pp. 105-120
-
-
Bagnall, A.J.1
Janacek, G.2
De La Iglesia, B.3
Zhang, M.4
-
60
-
-
58049087347
-
Time series clustering based on ICA for stock data analysis
-
C. Guo, H. Jia, N. Zhang, Time series clustering based on ICA for stock data analysis, in: Proceedings of 4th International Conference on Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08, 2008, pp. 1-4.
-
(2008)
Proceedings of 4th International Conference on Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08
, pp. 1-4
-
-
Guo, C.1
Jia, H.2
Zhang, N.3
-
61
-
-
84893592898
-
Fuzzy cluster analysis of financial time series and their volatility assessment
-
A. Stetco, X. Zeng, J. Keane, Fuzzy cluster analysis of financial time series and their volatility assessment, in: Proceedings of 2013 IEEE International Conference on Systems, Man, and Cybernetics, 2013, pp. 91-96.
-
(2013)
Proceedings of 2013 IEEE International Conference on Systems, Man, and Cybernetics
, pp. 91-96
-
-
Stetco, A.1
Zeng, X.2
Keane, J.3
-
62
-
-
84888335409
-
Stock market co-movement assessment using a three-phase clustering method
-
S. Aghabozorgi, and T. Ying Wah Stock market co-movement assessment using a three-phase clustering method Expert Syst. Appl. 41 4 2014 1301 1314
-
(2014)
Expert Syst. Appl.
, vol.41
, Issue.4
, pp. 1301-1314
-
-
Aghabozorgi, S.1
Wah, T.Y.2
-
63
-
-
84899716401
-
A clustering time series model for the optimal hedge ratio decision making
-
Y.-C. Hsu, and A.-P. Chen A clustering time series model for the optimal hedge ratio decision making Neurocomputing 138 2014 358 370
-
(2014)
Neurocomputing
, vol.138
, pp. 358-370
-
-
Hsu, Y.-C.1
Chen, A.-P.2
-
64
-
-
0036469327
-
Cluster analysis of biomedical image time-series
-
A. Wismüller, O. Lange, D.R. Dersch, G.L. Leinsinger, K. Hahn, B. Pütz, and D. Auer Cluster analysis of biomedical image time-series Int. J. Comput. Vis 46 2 2002 103 128
-
(2002)
Int. J. Comput. Vis
, vol.46
, Issue.2
, pp. 103-128
-
-
Wismüller, A.1
Lange, O.2
Dersch, D.R.3
Leinsinger, G.L.4
Hahn, K.5
Pütz, B.6
Auer, D.7
-
65
-
-
44349149239
-
Normalized cut group clustering of resting-state fMRI data
-
M. van den Heuvel, R. Mandl, Pol, and H. Hulshoff Normalized cut group clustering of resting-state fMRI data PLoS One 3 4 2008 e2001
-
(2008)
PLoS One
, vol.3
, Issue.4
, pp. e2001
-
-
Van Den Heuvel, M.1
Mandl, R.2
Pol3
Hulshoff, H.4
-
66
-
-
84860638565
-
A time series approach for clustering mass spectrometry data
-
2010
-
F. Gullo, G. Ponti, A. Tagarelli, G. Tradigo, and P. Veltri A time series approach for clustering mass spectrometry data J. Comput. Sci. 3 5 2011 344 355 2010
-
(2011)
J. Comput. Sci.
, vol.3
, Issue.5
, pp. 344-355
-
-
Gullo, F.1
Ponti, G.2
Tagarelli, A.3
Tradigo, G.4
Veltri, P.5
-
67
-
-
84867364690
-
Time-series mining in a psychological domain
-
V. Kurbalija, J. Nachtwei, C. Von Bernstorff, C. von Bernstorff, H.-D. Burkhard, M. Ivanović, L. Fodor, Time-series mining in a psychological domain, in: Proceedings of the Fifth Balkan Conference in Informatics, 2012, pp. 58-63.
-
(2012)
Proceedings of the Fifth Balkan Conference in Informatics
, pp. 58-63
-
-
Kurbalija, V.1
Nachtwei, J.2
Von Bernstorff, C.3
Von Bernstorff, C.4
Burkhard, H.-D.5
Ivanović, M.6
Fodor, L.7
-
68
-
-
85158153584
-
Multivariate clustering by dynamics
-
M. Ramoni, P. Sebastiani, P. Cohen, Multivariate clustering by dynamics, in:Proceedings of the national Conference on Artificial Intelligence, 2000, pp. 633-638.
-
(2000)
Proceedings of the National Conference on Artificial Intelligence
, pp. 633-638
-
-
Ramoni, M.1
Sebastiani, P.2
Cohen, P.3
-
70
-
-
79955625591
-
Fuzzy c-means clustering-based speaker verification
-
D. Tran, and M. Wagner Fuzzy c-means clustering-based speaker verification Adv. Soft Comput. 2002 2275 2002 363 369
-
(2002)
Adv. Soft Comput. 2002
, vol.2275
, pp. 363-369
-
-
Tran, D.1
Wagner, M.2
-
71
-
-
84861065520
-
Using hierarchical time series clustering algorithm and wavelet classifier for biometric voice classification
-
Fong, and Simon Using hierarchical time series clustering algorithm and wavelet classifier for biometric voice classification J. Biomed. Biotechnol. 2012 215019
-
(2012)
J. Biomed. Biotechnol.
, pp. 215019
-
-
Fong1
Simon2
-
72
-
-
84900840461
-
Social network users clustering based on multivariate time series of emotional behavior
-
J. Zhu, B. Wang, and B. Wu Social network users clustering based on multivariate time series of emotional behavior J. China Univ. Posts Telecommun 21 2 2014 21 31
-
(2014)
J. China Univ. Posts Telecommun
, vol.21
, Issue.2
, pp. 21-31
-
-
Zhu, J.1
Wang, B.2
Wu, B.3
-
73
-
-
21844471761
-
Clustering of time-series subsequences is meaningless: Implications for previous and future research
-
E. Keogh, and J. Lin Clustering of time-series subsequences is meaningless: implications for previous and future research Knowl. Inf. Syst. 8 2 2005 154 177
-
(2005)
Knowl. Inf. Syst.
, vol.8
, Issue.2
, pp. 154-177
-
-
Keogh, E.1
Lin, J.2
-
76
-
-
85013566475
-
Extracting interpretable muscle activation patterns with time series knowledge mining
-
F. Morchen, A. Ultsch, F. Mörchen, and O. Hoos Extracting interpretable muscle activation patterns with time series knowledge mining J. Knowl. BASED 9 3 2005 197 208
-
(2005)
J. Knowl. BASED
, vol.9
, Issue.3
, pp. 197-208
-
-
Morchen, F.1
Ultsch, A.2
Mörchen, F.3
Hoos, O.4
-
77
-
-
77957948202
-
Time-series clustering by approximate prototypes
-
V. Hautamaki, P. Nykanen, P. Franti, Time-series clustering by approximate prototypes, in: Proceedings of 19th International Conference on Pattern Recognition, 2008, ICPR 2008, 2008, no. D, pp. 1-4.
-
(2008)
Proceedings of 19th International Conference on Pattern Recognition, 2008, ICPR 2008
, vol.D
, pp. 1-4
-
-
Hautamaki, V.1
Nykanen, P.2
Franti, P.3
-
78
-
-
26944436839
-
Indexing time-series under conditions of noise
-
M. Last, A. Kandel, H. Bunke, World Scientific Singapore
-
M. Vlachos, D. Gunopulos, and G. Das "Indexing time-series under conditions of noise," M. Last, A. Kandel, H. Bunke, Data Mining in Time Series Databases 2004 World Scientific Singapore 67
-
(2004)
Data Mining in Time Series Databases
, pp. 67
-
-
Vlachos, M.1
Gunopulos, D.2
Das, G.3
-
79
-
-
79954516169
-
-
Chapman & Hall/CRC Taylor and Francis Group Boca Raton, FL
-
T. Mitsa Temporal Data Mining vol. 33 2009 Chapman & Hall/CRC Taylor and Francis Group Boca Raton, FL
-
(2009)
Temporal Data Mining
, vol.33
-
-
Mitsa, T.1
-
81
-
-
33644519378
-
Predicting volatility: Getting the most out of return data sampled at different frequencies
-
E. Ghysels, P. Santa-Clara, and R. Valkanov Predicting volatility: getting the most out of return data sampled at different frequencies J. Econom 131 1-2 2006 59 95
-
(2006)
J. Econom
, vol.131
, Issue.1-2
, pp. 59-95
-
-
Ghysels, E.1
Santa-Clara, P.2
Valkanov, R.3
-
82
-
-
84930639429
-
Grid representation of time series data for similarity search
-
G. Duan, Y. Suzuki, K. Kawagoe, Grid representation of time series data for similarity search, in: The institute of Electronic, Information, and Communication Engineer, 2006.
-
(2006)
The Institute of Electronic, Information, and Communication Engineer
-
-
Duan, G.1
Suzuki, Y.2
Kawagoe, K.3
-
83
-
-
26944466361
-
A novel bit level time series representation with implications for similarity search and clustering
-
C. Ratanamahatana, E. Keogh, A.J. Bagnall, S. Lonardi, A novel bit level time series representation with implications for similarity search and clustering, in: Proceedings of 9th Pacific-Asian International Conference on Knowledge Discovery and Data Mining (PAKDD'05), 2005, pp. 771-777.
-
(2005)
Proceedings of 9th Pacific-Asian International Conference on Knowledge Discovery and Data Mining (PAKDD'05)
, pp. 771-777
-
-
Ratanamahatana, C.1
Keogh, E.2
Bagnall, A.J.3
Lonardi, S.4
-
84
-
-
34548093287
-
Experiencing SAX: A novel symbolic representation of time series"
-
J. Lin, E. Keogh, L. Wei, and S. Lonardi Experiencing SAX: a novel symbolic representation of time series" Data Min. Knowl. Discov. 15 2 2007 107 144
-
(2007)
Data Min. Knowl. Discov.
, vol.15
, Issue.2
, pp. 107-144
-
-
Lin, J.1
Keogh, E.2
Wei, L.3
Lonardi, S.4
-
85
-
-
0032688141
-
Efficient time series matching by wavelets
-
K. Chan, A.W. Fu, Efficient time series matching by wavelets, in: Proceedings of 1999 15th International Conference on Data Engineering, vol. 15, no. 3, 1999, pp. 126-133.
-
(1999)
Proceedings of 1999 15th International Conference on Data Engineering
, vol.15
, Issue.3
, pp. 126-133
-
-
Chan, K.1
Fu, A.W.2
-
86
-
-
85150810448
-
An enhanced representation of time series which allows fast and accurate classification, clustering and relevance feedback
-
E. Keogh, M. Pazzani, An enhanced representation of time series which allows fast and accurate classification, clustering and relevance feedback, in: Proceedings of the 4th International Conference of Knowledge Discovery and Data Mining, 1998, pp. 239-241.
-
(1998)
Proceedings of the 4th International Conference of Knowledge Discovery and Data Mining
, pp. 239-241
-
-
Keogh, E.1
Pazzani, M.2
-
87
-
-
0034832364
-
Locally adaptive dimensionality reduction for indexing large time series databases
-
E. Keogh, K. Chakrabarti, M. Pazzani, and S. Mehrotra Locally adaptive dimensionality reduction for indexing large time series databases, ACM SIGMOD Rec 27 2 2001 151 162
-
(2001)
ACM SIGMOD Rec
, vol.27
, Issue.2
, pp. 151-162
-
-
Keogh, E.1
Chakrabarti, K.2
Pazzani, M.3
Mehrotra, S.4
-
89
-
-
84882410240
-
Comparison of DFT and DWT based similarity search in time-series databases
-
Y.L. Wu, D. Agrawal, A. El Abbadi, " comparison of DFT and DWT based similarity search in time-series databases, in: Proceedings of the Ninth International Conference on Information and Knowledge Management, 2000, pp. 488-495.
-
(2000)
Proceedings of the Ninth International Conference on Information and Knowledge Management
, pp. 488-495
-
-
Wu, Y.L.1
Agrawal, D.2
El Abbadi, A.3
-
91
-
-
84867136666
-
Querying and mining of time series data: Experimental comparison of representations and distance measures
-
H. Ding, G. Trajcevski, P. Scheuermann, X. Wang, and E. Keogh Querying and mining of time series data: experimental comparison of representations and distance measures, Proc. VLDB Endow 1 2 2008 1542 1552
-
(2008)
Proc. VLDB Endow
, vol.1
, Issue.2
, pp. 1542-1552
-
-
Ding, H.1
Trajcevski, G.2
Scheuermann, P.3
Wang, X.4
Keogh, E.5
-
92
-
-
33745108812
-
A bit level representation for time series data mining with shape based similarity
-
A.A.J. Bagnall, C. "Ann" Ratanamahatana, E. Keogh, S. Lonardi, and G. Janacek A bit level representation for time series data mining with shape based similarity Data Min. Knowl. Discov. 13 1 2006 11 40
-
(2006)
Data Min. Knowl. Discov.
, vol.13
, Issue.1
, pp. 11-40
-
-
Bagnall, A.A.J.1
Ann Ratanamahatana, C.2
Keogh, E.3
Lonardi, S.4
Janacek, G.5
-
93
-
-
67649557401
-
ISAX: Disk-aware mining and indexing of massive time series datasets
-
J. Shieh, and E. Keogh iSAX: disk-aware mining and indexing of massive time series datasets Data Min. Knowl. Discov. 19 1 2009 24 57
-
(2009)
Data Min. Knowl. Discov.
, vol.19
, Issue.1
, pp. 24-57
-
-
Shieh, J.1
Keogh, E.2
-
94
-
-
84872381144
-
Experimental comparison of representation methods and distance measures for time series data
-
p. Springer Netherlands
-
X. Wang, A. Mueen, H. Ding, G. Trajcevski, P. Scheuermann, and E. Keogh Experimental comparison of representation methods and distance measures for time series data Data Min. Knowl. Discov. 2012 p. Springer Netherlands
-
(2012)
Data Min. Knowl. Discov.
-
-
Wang, X.1
Mueen, A.2
Ding, H.3
Trajcevski, G.4
Scheuermann, P.5
Keogh, E.6
-
95
-
-
21844475708
-
The L-index: An indexing structure for efficient subsequence matching in time sequence databases
-
Y. Morinaka, M. Yoshikawa, T. Amagasa, S. Uemura, The L-index: an indexing structure for efficient subsequence matching in time sequence databases, in: Proceedings of 5th PacificAisa Conference on Knowledge Discovery and Data Mining, 2001, pp. 51-60.
-
(2001)
Proceedings of 5th PacificAisa Conference on Knowledge Discovery and Data Mining
, pp. 51-60
-
-
Morinaka, Y.1
Yoshikawa, M.2
Amagasa, T.3
Uemura, S.4
-
97
-
-
0031166708
-
Efficiently supporting ad hoc queries in large datasets of time sequences
-
F. Korn, H.V. Jagadish, and C. Faloutsos Efficiently supporting ad hoc queries in large datasets of time sequences ACM SIGMOD Record 26 1997 289 300
-
(1997)
ACM SIGMOD Record
, vol.26
, pp. 289-300
-
-
Korn, F.1
Jagadish, H.V.2
Faloutsos, C.3
-
98
-
-
62549107437
-
Automatic generation of textual summaries from neonatal intensive care data
-
F. Portet, E. Reiter, A. Gatt, J. Hunter, S. Sripada, Y. Freer, and C. Sykes Automatic generation of textual summaries from neonatal intensive care data Artif. Intell. 173 7 2009 789 816
-
(2009)
Artif. Intell.
, vol.173
, Issue.7
, pp. 789-816
-
-
Portet, F.1
Reiter, E.2
Gatt, A.3
Hunter, J.4
Sripada, S.5
Freer, Y.6
Sykes, C.7
-
99
-
-
3142777878
-
Indexing spatio-temporal trajectories with Chebyshev polynomials
-
Y. Cai and R. Ng, Indexing spatio-temporal trajectories with Chebyshev polynomials, in: Procedings of 2004 ACM SIGMOD International, 2004, p. 599.
-
(2004)
Procedings of 2004 ACM SIGMOD International
, pp. 599
-
-
Cai, Y.1
Ng, R.2
-
101
-
-
85011026173
-
Indexable PLA for efficient similarity search
-
Q. Chen, L. Chen, X. Lian, Y. Liu, Indexable PLA for efficient similarity search, in: Proceedings of the 33rd International Conference on Very large Data Bases, 2007, pp. 435-446.
-
(2007)
Proceedings of the 33rd International Conference on Very Large Data Bases
, pp. 435-446
-
-
Chen, Q.1
Chen, L.2
Lian, X.3
Liu, Y.4
-
102
-
-
43949136939
-
Discovering characteristic actions from on-body sensor data
-
D. Minnen, T. Starner, M. Essa, C. Isbell, Discovering characteristic actions from on-body sensor data, in: Proceedings of 10th IEEE International Symposium on Wearable Computers, 2006, pp. 11-18.
-
(2006)
Proceedings of 10th IEEE International Symposium on Wearable Computers
, pp. 11-18
-
-
Minnen, D.1
Starner, T.2
Essa, M.3
Isbell, C.4
-
103
-
-
36348977475
-
Discovering multivariate motifs using subsequence density estimation and greedy mixture learning
-
D. Minnen, C.L. Isbell, I. Essa, and T. Starner Discovering multivariate motifs using subsequence density estimation and greedy mixture learning Proc. Natl. Conf. Artif. Intell. 22 1 2007 615
-
(2007)
Proc. Natl. Conf. Artif. Intell.
, vol.22
, Issue.1
, pp. 615
-
-
Minnen, D.1
Isbell, C.L.2
Essa, I.3
Starner, T.4
-
104
-
-
23044532511
-
A Hidden Markov Model-based approach to sequential data clustering
-
T. Caelli, A. Amin, R. Duin, R. De, and M. Kamel, Eds.
-
A. Panuccio, M. Bicego, and V. Murino, A Hidden Markov Model-based approach to sequential data clustering, in Structural, Syntactic, and Statistical Pattern Recognition, T. Caelli, A. Amin, R. Duin, R. De, and M. Kamel, Eds. 2002.
-
(2002)
Structural, Syntactic, and Statistical Pattern Recognition
-
-
Panuccio, A.1
Bicego, M.2
Murino, V.3
-
105
-
-
84880090937
-
Time-series bitmaps: A practical visualization tool for working with large time series databases
-
N. Kumar, N. Lolla, E. Keogh, and S. Lonardi Time-series bitmaps: a practical visualization tool for working with large time series databases SIAM 2005 Data Min 2005 531 535
-
(2005)
SIAM 2005 Data Min
, pp. 531-535
-
-
Kumar, N.1
Lolla, N.2
Keogh, E.3
Lonardi, S.4
-
106
-
-
35748959377
-
Time series clustering and classification by the autoregressive metric
-
M. Corduas, and D. Piccolo Time series clustering and classification by the autoregressive metric Comput. Stat. Data Anal. 52 4 2008 1860 1872
-
(2008)
Comput. Stat. Data Anal.
, vol.52
, Issue.4
, pp. 1860-1872
-
-
Corduas, M.1
Piccolo, D.2
-
107
-
-
78149299418
-
Distance measures for effective clustering of ARIMA time-series
-
K. Kalpakis, D. Gada, V. Puttagunta, Distance measures for effective clustering of ARIMA time-series, in: Proceedings 2001 IEEE International Conference on Data Mining, 2001, pp. 273-280.
-
(2001)
Proceedings 2001 IEEE International Conference on Data Mining
, pp. 273-280
-
-
Kalpakis, K.1
Gada, D.2
Puttagunta, V.3
-
110
-
-
4844229413
-
Flexible time series pattern matching based on perceptually important points
-
F.L. Chung, T.C. Fu, R. Luk, Flexible time series pattern matching based on perceptually important points, in: Jt. Conference on Artificial Intelligence Workshop, 2001, pp. 1-7.
-
(2001)
Jt. Conference on Artificial Intelligence Workshop
, pp. 1-7
-
-
Chung, F.L.1
Fu, T.C.2
Luk, R.3
-
111
-
-
10644281769
-
Towards parameter-free data mining
-
E. Keogh, S. Lonardi, C. Ratanamahatana, Towards parameter-free data mining, in: Proceedings of Tenth ACM SIGKDD International Conference on Knowledge Discovery Data Mining, vol. 22, no. 25, 2004, pp. 206-215.
-
(2004)
Proceedings of Tenth ACM SIGKDD International Conference on Knowledge Discovery Data Mining
, vol.22
, Issue.25
, pp. 206-215
-
-
Keogh, E.1
Lonardi, S.2
Ratanamahatana, C.3
-
112
-
-
15544384126
-
Clustering time series with clipped data
-
A.J. Bagnall, and G. Janacek Clustering time series with clipped data Mach. Learn. 58 2 2005 151 178
-
(2005)
Mach. Learn.
, vol.58
, Issue.2
, pp. 151-178
-
-
Bagnall, A.J.1
Janacek, G.2
-
113
-
-
1842530903
-
Incremental, online, and merge mining of partial periodic patterns in time-series databases
-
W.G. Aref, M.G. Elfeky, and A.K. Elmagarmid Incremental, online, and merge mining of partial periodic patterns in time-series databases Trans. Knowl. Data Eng 16 3 2004 332 342
-
(2004)
Trans. Knowl. Data Eng
, vol.16
, Issue.3
, pp. 332-342
-
-
Aref, W.G.1
Elfeky, M.G.2
Elmagarmid, A.K.3
-
114
-
-
14844324775
-
Iterative deepening dynamic time warping for time series
-
S. Chu, E. Keogh, D. Hart, M. Pazzani, et al., Iterative deepening dynamic time warping for time series, in: Proceedings of the Second SIAM International Conference on Data Mining, 2002, pp. 195-212.
-
(2002)
Proceedings of the Second SIAM International Conference on Data Mining
, pp. 195-212
-
-
Chu, S.1
Keogh, E.2
Hart, D.3
Pazzani, M.4
-
116
-
-
84898995769
-
Clustering sequences with hidden Markov models
-
P. Smyth Clustering sequences with hidden Markov models, Adv. Neural Inf. Process. Syst 9 1997 648 654
-
(1997)
Adv. Neural Inf. Process. Syst
, vol.9
, pp. 648-654
-
-
Smyth, P.1
-
117
-
-
2642545237
-
Mixtures of ARMA models for model-based time series clustering
-
Y. Xiong, and D.Y. Yeung Mixtures of ARMA models for model-based time series clustering Data Min, 2002. ICDM 2003 2002 717 720
-
(2002)
Data Min, 2002. ICDM
, vol.2003
, pp. 717-720
-
-
Xiong, Y.1
Yeung, D.Y.2
-
119
-
-
0017930815
-
Dynamic programming algorithm optimization for spoken word recognition
-
H. Sakoe, and S. Chiba Dynamic programming algorithm optimization for spoken word recognition, IEEE Trans. Acoust. Speech Signal Process 26 1 1978 43 49
-
(1978)
IEEE Trans. Acoust. Speech Signal Process
, vol.26
, Issue.1
, pp. 43-49
-
-
Sakoe, H.1
Chiba, S.2
-
120
-
-
0036211177
-
Discovering similar multidimensional trajectories
-
M. Vlachos, G. Kollios, D. Gunopulos, Discovering similar multidimensional trajectories, in: Proceedingsof 18th International Conference on Data Engineering, 2002, pp. 673-684.
-
(2002)
Proceedingsof 18th International Conference on Data Engineering
, pp. 673-684
-
-
Vlachos, M.1
Kollios, G.2
Gunopulos, D.3
-
121
-
-
0037869046
-
Clickstream clustering using weighted longest common subsequences
-
A. Banerjee, J. Ghosh, Clickstream clustering using weighted longest common subsequences, in: Proceedings of the Workshop on Web Mining, SIAM Conference on Data Mining, 2001, pp. 33-40.
-
(2001)
Proceedings of the Workshop on Web Mining, SIAM Conference on Data Mining
, pp. 33-40
-
-
Banerjee, A.1
Ghosh, J.2
-
122
-
-
33646426628
-
Elastic partial matching of time series
-
L.J. Latecki, V. Megalooikonomou, Q. Wang, R. Lakaemper, C. Ratanamahatana, and E. Keogh Elastic partial matching of time series, Knowl. Discov. Databases PKDD 2005 2005 577 584
-
(2005)
Knowl. Discov. Databases PKDD 2005
, pp. 577-584
-
-
Latecki, L.J.1
Megalooikonomou, V.2
Wang, Q.3
Lakaemper, R.4
Ratanamahatana, C.5
Keogh, E.6
-
123
-
-
33847394102
-
Compression-based data mining of sequential data
-
E. Keogh, S. Lonardi, C. Ratanamahatana, L. Wei, S.H. Lee, and J. Handley Compression-based data mining of sequential data, Data Min. Knowl. Discov. 14 1 2007 99 129
-
(2007)
Data Min. Knowl. Discov.
, vol.14
, Issue.1
, pp. 99-129
-
-
Keogh, E.1
Lonardi, S.2
Ratanamahatana, C.3
Wei, L.4
Lee, S.H.5
Handley, J.6
-
124
-
-
84952503562
-
Thirteen ways to look at the correlation coefficient
-
J.L. Rodgers, and W.A. Nicewander Thirteen ways to look at the correlation coefficient, Am. Stat 42 1 1988 59 66
-
(1988)
Am. Stat
, vol.42
, Issue.1
, pp. 59-66
-
-
Rodgers, J.L.1
Nicewander, W.A.2
-
126
-
-
0032637272
-
Mining for similarities in aligned time series using wavelets
-
February 25
-
Yka Huhtala; Juha Karkkainen and Hannu T. Toivonen "Mining for similarities in aligned time series using wavelets", Proc. SPIE 3695, Data Mining and Knowledge Discovery: Theory, Tools, and Technology, 150 (February 25, 1999); doi:10.1117/12.339977; http://dx.doi.org/10.1117/12.339977.
-
(1999)
Proc. SPIE 3695, Data Mining and Knowledge Discovery: Theory, Tools, and Technology
, vol.150
-
-
Huhtala, Y.1
Karkkainen, J.2
Toivonen, H.T.3
-
127
-
-
80055004213
-
Data mining in time series databases
-
M. Last, and A. Kandel Data mining in time series databases World Sci. 2004
-
(2004)
World Sci.
-
-
Last, M.1
Kandel, A.2
-
128
-
-
34147174850
-
Comparison of similarity measures for trajectory clustering in outdoor surveillance scenes
-
Z. Zhang, K. Huang, T. Tan, Comparison of similarity measures for trajectory clustering in outdoor surveillance scenes, in: Proceedings of 18th International Conference on Pattern Recognition, ICPR 2006, vol. 3, pp. 1135-1138, 2006.
-
(2006)
Proceedings of 18th International Conference on Pattern Recognition, ICPR 2006
, vol.3
, pp. 1135-1138
-
-
Zhang, Z.1
Huang, K.2
Tan, T.3
-
129
-
-
0034954376
-
Aligning gene expression time series with time warping algorithms
-
J. Aach, and G.M. Church Aligning gene expression time series with time warping algorithms Bioinformatics 17 6 2001 495
-
(2001)
Bioinformatics
, vol.17
, Issue.6
, pp. 495
-
-
Aach, J.1
Church, G.M.2
-
130
-
-
0030095346
-
On the Kullback-Leibler information divergence of locally stationary processes
-
R. Dahlhaus On the Kullback-Leibler information divergence of locally stationary processes Stoch. Process. Appl 62 1 1996 139 168
-
(1996)
Stoch. Process. Appl
, vol.62
, Issue.1
, pp. 139-168
-
-
Dahlhaus, R.1
-
132
-
-
0031856564
-
A new correlation-based fuzzy logic clustering algorithm for FMRI
-
X. Golay, S. Kollias, G. Stoll, D. Meier, A. Valavanis, and P. Boesiger A new correlation-based fuzzy logic clustering algorithm for FMRI, Magn. Reson. Med. 40 2 1998 249 260
-
(1998)
Magn. Reson. Med.
, vol.40
, Issue.2
, pp. 249-260
-
-
Golay, X.1
Kollias, S.2
Stoll, G.3
Meier, D.4
Valavanis, A.5
Boesiger, P.6
-
133
-
-
53949085995
-
Supporting content-based searches on time series via approximation
-
C. Wang, and X. Sean Wang Supporting content-based searches on time series via approximation, Sci Stat Database 2000 69 81
-
(2000)
Sci Stat Database
, pp. 69-81
-
-
Wang, C.1
Wang, X.S.2
-
135
-
-
29844444110
-
Robust and fast similarity search for moving object trajectories
-
L. Chen, M.T. Özsu, V. Oria, Robust and fast similarity search for moving object trajectories, in: Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data, 2005, pp. 491-502.
-
(2005)
Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data
, pp. 491-502
-
-
Chen, L.1
Özsu, M.T.2
Oria, V.3
-
136
-
-
84883211513
-
Using multi-scale histograms to answer pattern existence and shape match queries
-
L. Chen, and M.T. Özsu Using multi-scale histograms to answer pattern existence and shape match queries, Time 2 1 2005 217 226
-
(2005)
Time
, vol.2
, Issue.1
, pp. 217-226
-
-
Chen, L.1
Özsu, M.T.2
-
137
-
-
33745617385
-
Similarity search on time series based on threshold queries
-
J. Aßfalg, H.P. Kriegel, P. Kröger, P. Kunath, A. Pryakhin, and M. Renz Similarity search on time series based on threshold queries Adv. Database Technol. 2006 2006 276 294
-
(2006)
Adv. Database Technol. 2006
, pp. 276-294
-
-
Aßfalg, J.1
Kriegel, H.P.2
Kröger, P.3
Kunath, P.4
Pryakhin, A.5
Renz, M.6
-
138
-
-
34548722068
-
Index-based most similar trajectory search
-
E. Frentzos, K. Gratsias, Y. Theodoridis, Index-based most similar trajectory search, in: Proceedings of 23rd International Conference on Data Engineering, 2007, ICDE 2007. IEEE, 2007, pp. 816-825.
-
(2007)
Proceedings of 23rd International Conference on Data Engineering, 2007, ICDE 2007. IEEE
, pp. 816-825
-
-
Frentzos, E.1
Gratsias, K.2
Theodoridis, Y.3
-
140
-
-
34548788470
-
Spade: On shape-based pattern detection in streaming time series
-
Y. Chen, M.A. Nascimento, B.C. Ooi,A.K.H. Tung, Spade: on shape-based pattern detection in streaming time series, in: Proceedings of IEEE 23rd International Conference on Data Engineering, 2007. ICDE 2007., 2007, pp. 786-795.
-
(2007)
Proceedings of IEEE 23rd International Conference on Data Engineering, 2007. ICDE 2007
, pp. 786-795
-
-
Chen, Y.1
Nascimento, M.A.2
Ooi, B.C.3
Tung, A.K.H.4
-
141
-
-
78649487981
-
A notime series classificationvel pattern extraction method for
-
X. Zhang, J. Wu, X. Yang, H. Ou, and T. Lv A notime series classificationvel pattern extraction method for Optim. Eng. 10 2 2009 253 271
-
(2009)
Optim. Eng.
, vol.10
, Issue.2
, pp. 253-271
-
-
Zhang, X.1
Wu, J.2
Yang, X.3
Ou, H.4
Lv, T.5
-
142
-
-
77956999479
-
Dictionary-based compression for long time-series similarity
-
W. Lang, M. Morse, and J.M. Patel Dictionary-based compression for long time-series similarity Knowl. Data Eng. IEEE Trans 22 11 2010 1609 1622
-
(2010)
Knowl. Data Eng. IEEE Trans
, vol.22
, Issue.11
, pp. 1609-1622
-
-
Lang, W.1
Morse, M.2
Patel, J.M.3
-
143
-
-
41749090269
-
Toward accurate dynamic time warping in linear time and space
-
S. Salvador, and P. Chan Toward accurate dynamic time warping in linear time and space Intell. Data Anal. 11 5 2007 561 580
-
(2007)
Intell. Data Anal.
, vol.11
, Issue.5
, pp. 561-580
-
-
Salvador, S.1
Chan, P.2
-
144
-
-
0016467604
-
Minimum prediction residual principle applied to speech recognition. Minimum prediction residual principle applied to speech recognition
-
F. Itakura Minimum prediction residual principle applied to speech recognition. Minimum prediction residual principle applied to speech recognition IEEE Trans. Acoust. Speech Signal Process 23 1 1975 67 72
-
(1975)
IEEE Trans. Acoust. Speech Signal Process
, vol.23
, Issue.1
, pp. 67-72
-
-
Itakura, F.1
-
145
-
-
84890514466
-
New time series data representation ESAX for financial applications
-
B. Lkhagva, Y.u. Suzuki, K. Kawagoe, New time series data representation ESAX for financial applications, in: Proceedings of 22nd International Conference on Data Engineering Workshops, 2006, pp. 17-22.
-
(2006)
Proceedings of 22nd International Conference on Data Engineering Workshops
, pp. 17-22
-
-
Lkhagva, B.1
Suzuki, Yu.2
Kawagoe, K.3
-
146
-
-
84931825565
-
Dynamic time warping for off-line recognition of a small gesture vocabulary
-
A. Corradini, Dynamic time warping for off-line recognition of a small gesture vocabulary, in: IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems, 2001, pp. 82-89.
-
(2001)
IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems
, pp. 82-89
-
-
Corradini, A.1
-
147
-
-
0018656519
-
Speaker-independent recognition of isolated words using clustering techniques
-
L. Rabiner, and S. Levinson Speaker-independent recognition of isolated words using clustering techniques, IEEE Trans. Acoust. Speech Signal Process 27 4 1979 336 349
-
(1979)
IEEE Trans. Acoust. Speech Signal Process
, vol.27
, Issue.4
, pp. 336-349
-
-
Rabiner, L.1
Levinson, S.2
-
149
-
-
37249046121
-
Inaccuracies of shape averaging method using dynamic time warping for time series data
-
V. Niennattrakul, and C. Ratanamahatana Inaccuracies of shape averaging method using dynamic time warping for time series data Comput. Sci. 2007 2007 513 520
-
(2007)
Comput. Sci. 2007
, pp. 513-520
-
-
Niennattrakul, V.1
Ratanamahatana, C.2
-
151
-
-
33751567248
-
A comparison of techniques for automatic clustering of handwritten characters
-
V. Vuori, and J. Laaksonen A comparison of techniques for automatic clustering of handwritten characters Pattern Recognit., 2002 3 2002 30168
-
(2002)
Pattern Recognit., 2002
, vol.3
, pp. 30168
-
-
Vuori, V.1
Laaksonen, J.2
-
152
-
-
24044538120
-
Understanding and projecting the battle state
-
Orlando, FL
-
T.W. Liao, B. Bolt, J. Forester, E. Hailman, C. Hansen, R. Kaste, J. O'May, Understanding and projecting the battle state, in: Proceedings of 23rd Army Science Conference, Orlando, FL, 2002, pp. 2-3.
-
(2002)
Proceedings of 23rd Army Science Conference
, pp. 2-3
-
-
Liao, T.W.1
Bolt, B.2
Forester, J.3
Hailman, E.4
Hansen, C.5
Kaste, R.6
O'May, J.7
-
153
-
-
33745000979
-
An adaptive genetic clustering method for exploratory mining of feature vector and time series data
-
T.W. Liao, and C.F. Ting An adaptive genetic clustering method for exploratory mining of feature vector and time series data, Int. J. Prod. Res. 44 14 2006 2731 2748
-
(2006)
Int. J. Prod. Res.
, vol.44
, Issue.14
, pp. 2731-2748
-
-
Liao, T.W.1
Ting, C.F.2
-
154
-
-
0030130811
-
Nonlinear alignment and averaging for estimating the evoked potential
-
L. Gupta, D.L. Molfese, R. Tammana, and P.G. Simos Nonlinear alignment and averaging for estimating the evoked potential IEEE Trans. Biomed. Eng. 43 4 1996 348 356
-
(1996)
IEEE Trans. Biomed. Eng.
, vol.43
, Issue.4
, pp. 348-356
-
-
Gupta, L.1
Molfese, D.L.2
Tammana, R.3
Simos, P.G.4
-
155
-
-
12844282508
-
Warped-average template technique to track on a cycle-by-cycle basis the cardiac filling phases on left ventricular volume
-
E. Caiani, A. Porta, G. Baselli, M. Turiel, S. Muzzupappa, F. Pieruzzi, C. Crema, A. Malliani, and S. Cerutti Warped-average template technique to track on a cycle-by-cycle basis the cardiac filling phases on left ventricular volume, Comput. Cardiol. 1998 1998 73 76
-
(1998)
Comput. Cardiol. 1998
, pp. 73-76
-
-
Caiani, E.1
Porta, A.2
Baselli, G.3
Turiel, M.4
Muzzupappa, S.5
Pieruzzi, F.6
Crema, C.7
Malliani, A.8
Cerutti, S.9
-
156
-
-
2642567171
-
Using dynamic time warping to bootstrap HMM-based clustering of time series
-
T. Oates, L. Firoiu, and P. Cohen Using dynamic time warping to bootstrap HMM-based clustering of time series Seq. Learn. Paradig. ALGORITHMS, Appl 1 1828 2001 35 52
-
(2001)
Seq. Learn. Paradig. ALGORITHMS, Appl
, vol.1
, Issue.1828
, pp. 35-52
-
-
Oates, T.1
Firoiu, L.2
Cohen, P.3
-
157
-
-
2342589272
-
Cross-words reference template for DTW-based speech recognition systems
-
W. Abdulla, D. Chow, Cross-words reference template for DTW-based speech recognition systems, in: TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region, vol. 4, 2003, pp. 1576-1579.
-
(2003)
TENCon 2003. Conference on Convergent Technologies for Asia-Pacific Region
, vol.4
, pp. 1576-1579
-
-
Abdulla, W.1
Chow, D.2
-
158
-
-
78649324794
-
A global averaging method for dynamic time warping, with applications to clustering
-
F. Petitjean, A. Ketterlin, and P. Gançarski A global averaging method for dynamic time warping, with applications to clustering Pattern Recognit 44 3 2011 678 693
-
(2011)
Pattern Recognit
, vol.44
, Issue.3
, pp. 678-693
-
-
Petitjean, F.1
Ketterlin, A.2
Gançarski, P.3
-
159
-
-
84964528874
-
A survey of longest common subsequence algorithms
-
L. Bergroth, H. Hakonen, A survey of longest common subsequence algorithms, in: Proceedings of the Seventh International Symposium on String Processing and Information Retrieval, 2000. SPIRE 2000, 2000, pp. 39-48.
-
(2000)
Proceedings of the Seventh International Symposium on String Processing and Information Retrieval, 2000. SPIRE 2000
, pp. 39-48
-
-
Bergroth, L.1
Hakonen, H.2
-
160
-
-
84888385203
-
A new approach to present prototypes in clustering of time series
-
S. Aghabozorgi, T.Y. Wah, A. Amini, M.R. Saybani, A new approach to present prototypes in clustering of time series, in: Proceedings of the 7th International Conference of Data Mining, vol. 28, no. 4, 2011, pp. 214-220.
-
(2011)
Proceedings of the 7th International Conference of Data Mining
, vol.28
, Issue.4
, pp. 214-220
-
-
Aghabozorgi, S.1
Wah, T.Y.2
Amini, A.3
Saybani, M.R.4
-
161
-
-
84862906604
-
Incremental clustering of time-series by fuzzy clustering
-
S. Aghabozorgi, M.R. Saybani, and T.Y. Wah Incremental clustering of time-series by fuzzy clustering J. Inf. Sci. Eng. 28 4 2012 671 688
-
(2012)
J. Inf. Sci. Eng.
, vol.28
, Issue.4
, pp. 671-688
-
-
Aghabozorgi, S.1
Saybani, M.R.2
Wah, T.Y.3
-
162
-
-
0032686723
-
Chameleon: Hierarchical clustering using dynamic modeling
-
G. Karypis, E.H. Han, and V. Kumar Chameleon: hierarchical clustering using dynamic modeling Comput. (Long. Beach. Calif). 32 8 1999 68 75
-
(1999)
Comput. (Long. Beach. Calif).
, vol.32
, Issue.8
, pp. 68-75
-
-
Karypis, G.1
Han, E.H.2
Kumar, V.3
-
163
-
-
0032091595
-
CURE: An efficient clustering algorithm for large databases
-
S. Guha, R. Rastogi, and K. Shim CURE: an efficient clustering algorithm for large databases, ACM SIGMOD Rec. 27 2 1998 73 84
-
(1998)
ACM SIGMOD Rec.
, vol.27
, Issue.2
, pp. 73-84
-
-
Guha, S.1
Rastogi, R.2
Shim, K.3
-
164
-
-
0030157145
-
BIRCH: An efficient data clustering method for very large databases
-
T. Zhang, R. Ramakrishnan, and M. Livny BIRCH: an efficient data clustering method for very large databases ACM SIGMOD Rec. 25 2 1996 103 114
-
(1996)
ACM SIGMOD Rec.
, vol.25
, Issue.2
, pp. 103-114
-
-
Zhang, T.1
Ramakrishnan, R.2
Livny, M.3
-
165
-
-
15344341533
-
A wavelet-based anytime algorithm for k-means clustering of time series
-
M. Vlachos, J. Lin, and E. Keogh A wavelet-based anytime algorithm for k-means clustering of time series Proc. Work. Clust 2003 23 30
-
(2003)
Proc. Work. Clust
, pp. 23-30
-
-
Vlachos, M.1
Lin, J.2
Keogh, E.3
-
167
-
-
84969135798
-
A method for clustering the experiences of a mobile robot that accords with human judgments
-
T. Oates, M.D. Schmill, P.R. Cohen, A method for clustering the experiences of a mobile robot that accords with human judgments, in: Proceedings of the National Conference on Artificial Intelligence, 2000, pp. 846-851.
-
(2000)
Proceedings of the National Conference on Artificial Intelligence
, pp. 846-851
-
-
Oates, T.1
Schmill, M.D.2
Cohen, P.R.3
-
168
-
-
26844542547
-
Empirical comparison of clustering methods for long time-series databases
-
S. Hirano, and S. Tsumoto Empirical comparison of clustering methods for long time-series databases Act. Min 3430 2005 268 286
-
(2005)
Act. Min
, vol.3430
, pp. 268-286
-
-
Hirano, S.1
Tsumoto, S.2
-
171
-
-
85043349209
-
Initialization of iterative refinement clustering algorithms
-
U. Fayyad, C. Reina, P.S. Bradley, Initialization of iterative refinement clustering algorithms, in: Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining, 1998, pp. 194-198.
-
(1998)
Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining
, pp. 194-198
-
-
Fayyad, U.1
Reina, C.2
Bradley, P.S.3
-
173
-
-
33646933601
-
Online clustering of parallel data streams
-
Aug
-
J. Beringer, and E. Hullermeier Online clustering of parallel data streams Data Knowl. Eng. 58 2 2006 180 204 Aug
-
(2006)
Data Knowl. Eng.
, vol.58
, Issue.2
, pp. 180-204
-
-
Beringer, J.1
Hullermeier, E.2
-
175
-
-
0015644825
-
A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters
-
J.C. Dunn A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters Cybern. Syst. 3 3 1973 32 57
-
(1973)
Cybern. Syst.
, vol.3
, Issue.3
, pp. 32-57
-
-
Dunn, J.C.1
-
176
-
-
0035416012
-
Low-complexity fuzzy relational clustering algorithms for web mining
-
R. Krishnapuram, A. Joshi, O. Nasraoui, and L. Yi "Low-complexity fuzzy relational clustering algorithms for web mining," Fuzzy Syst. IEEE Trans vol. 9 no. 4 2001 595 607
-
(2001)
Fuzzy Syst. IEEE Trans
, vol.9
, Issue.4
, pp. 595-607
-
-
Krishnapuram, R.1
Joshi, A.2
Nasraoui, O.3
Yi, L.4
-
177
-
-
17944394324
-
Fuzzy C-means method for clustering microarray data
-
D. Dembélé, and P. Kastner Fuzzy C-means method for clustering microarray data Bioinformatics 19 8 2003 973 980
-
(2003)
Bioinformatics
, vol.19
, Issue.8
, pp. 973-980
-
-
Dembélé, D.1
Kastner, P.2
-
180
-
-
0343442766
-
Knowledge acquisition via incremental conceptual clustering
-
D.H. Fisher Knowledge acquisition via incremental conceptual clustering Mach. Learn. 2 2 1987 139 172
-
(1987)
Mach. Learn.
, vol.2
, Issue.2
, pp. 139-172
-
-
Fisher, D.H.1
-
181
-
-
0021776661
-
A massively parallel architecture for a self-organizing neural pattern recognition machine
-
G.A. Carpenter, and S. Grossberg A massively parallel architecture for a self-organizing neural pattern recognition machine Comput. vision, Graph. image Process 37 1 1987 54 115
-
(1987)
Comput. Vision, Graph. Image Process
, vol.37
, Issue.1
, pp. 54-115
-
-
Carpenter, G.A.1
Grossberg, S.2
-
182
-
-
0025489075
-
The self-organizing map
-
T. Kohonen The self-organizing map Proc. IEEE 78 9 1990 1464 1480
-
(1990)
Proc. IEEE
, vol.78
, Issue.9
, pp. 1464-1480
-
-
Kohonen, T.1
-
183
-
-
0034228914
-
Assessing a mixture model for clustering with the integrated completed likelihood
-
C. Biernacki, G. Celeux, and G. Govaert Assessing a mixture model for clustering with the integrated completed likelihood IEEE Trans. Pattern Anal. Mach. Intell 22 7 2000 719 725
-
(2000)
IEEE Trans. Pattern Anal. Mach. Intell
, vol.22
, Issue.7
, pp. 719-725
-
-
Biernacki, C.1
Celeux, G.2
Govaert, G.3
-
185
-
-
34147169446
-
An interweaved hmm/dtw approach to robust time series clustering
-
J. Hu, B. Ray, L. Han, An interweaved hmm/dtw approach to robust time series clustering, in: Proceedings of 18th International Conference on Pattern Recognition, 2006. ICPR 2006, vol. 3, 2006, pp. 145-148.
-
(2006)
Proceedings of 18th International Conference on Pattern Recognition, 2006. ICPR 2006
, vol.3
, pp. 145-148
-
-
Hu, J.1
Ray, B.2
Han, L.3
-
186
-
-
65549104397
-
A roadmap of clustering algorithms: Finding a match for a biomedical application
-
B. Andreopoulos, A. An, and X. Wang, A roadmap of clustering algorithms: finding a match for a biomedical application Brief. Bioinform. 10 3 2009 297 314
-
(2009)
Brief. Bioinform.
, vol.10
, Issue.3
, pp. 297-314
-
-
Andreopoulos, B.1
An, A.2
Wang, X.3
-
187
-
-
45749146270
-
A density-based algorithm for discovering clusters in large spatial databases with noise
-
M. Ester, H.P. Kriegel, J. Sander, and X. Xu A density-based algorithm for discovering clusters in large spatial databases with noise In Kdd 96 34 1996, August 226 231
-
(1996)
Kdd
, vol.96
, Issue.34
, pp. 226-231
-
-
Ester, M.1
Kriegel, H.P.2
Sander, J.3
Xu, X.4
-
188
-
-
0347172110
-
OPTICS: Ordering points to identify the clustering structure
-
M. Ankerst, M. Breunig, and H. Kriegel OPTICS: Ordering points to identify the clustering structure ACM SIGMOD Rec 28 2 1999 40 60
-
(1999)
ACM SIGMOD Rec
, vol.28
, Issue.2
, pp. 40-60
-
-
Ankerst, M.1
Breunig, M.2
Kriegel, H.3
-
189
-
-
56349085660
-
A density based method for multivariate time series clustering in kernel feature space
-
S. Chandrakala, C. Chandra, A density based method for multivariate time series clustering in kernel feature space, in: Proceedings of IEEE International Joint Conference on Neural Networks IEEE World Congress on Computational Intelligence, vol. 2008, 2008, pp. 1885-1890.
-
(2008)
Proceedings of IEEE International Joint Conference on Neural Networks IEEE World Congress on Computational Intelligence
, vol.2008
, pp. 1885-1890
-
-
Chandrakala, S.1
Chandra, C.2
-
190
-
-
84994158589
-
STING: A statistical information grid approach to spatial data mining
-
W. Wang, J. Yang, R. Muntz, STING: a statistical information grid approach to spatial data mining, in: Proceedings of the International Conference on Very Large Data Bases, 1997, pp. 186-195.
-
(1997)
Proceedings of the International Conference on Very Large Data Bases
, pp. 186-195
-
-
Wang, W.1
Yang, J.2
Muntz, R.3
-
191
-
-
0003052357
-
Wavecluster: A multi-resolution clustering approach for very large spatial databases
-
G. Sheikholeslami, S. Chatterjee, A. Zhang, Wavecluster: A multi-resolution clustering approach for very large spatial databases, in: proceedings of the International conference on Very Large Data Bases, 1998, pp. 428-439.
-
(1998)
Proceedings of the International Conference on Very Large Data Bases
, pp. 428-439
-
-
Sheikholeslami, G.1
Chatterjee, S.2
Zhang, A.3
-
192
-
-
0032343819
-
Discrimination and clustering for multivariate time series
-
Y. Kakizawa, R.H. Shumway, and M. Taniguchi Discrimination and clustering for multivariate time series J. Am. Stat. Assoc 93 441 1998 328 340
-
(1998)
J. Am. Stat. Assoc
, vol.93
, Issue.441
, pp. 328-340
-
-
Kakizawa, Y.1
Shumway, R.H.2
Taniguchi, M.3
-
193
-
-
0033692592
-
Nonstationary time series analysis by temporal clustering
-
S. Policker, and A.B.B. Geva Nonstationary time series analysis by temporal clustering Syst. Man, Cybern. Part B 30 2 2000 339 343
-
(2000)
Syst. Man, Cybern. Part B
, vol.30
, Issue.2
, pp. 339-343
-
-
Policker, S.1
Geva, A.B.B.2
-
194
-
-
0035861975
-
Beyond synexpression relationships: Local clustering of time-shifted and inverted gene expression profiles identifies new, biologically relevant interactions1
-
J. Qian, M. Dolled-Filhart, J. Lin, H. Yu, and M. Gerstein Beyond synexpression relationships: local clustering of time-shifted and inverted gene expression profiles identifies new, biologically relevant interactions1 J. Mol. Biol. 314 5 2001 1053 1066
-
(2001)
J. Mol. Biol.
, vol.314
, Issue.5
, pp. 1053-1066
-
-
Qian, J.1
Dolled-Filhart, M.2
Lin, J.3
Yu, H.4
Gerstein, M.5
-
195
-
-
1842483334
-
Joint segmentation and classification of time series using class-specific features
-
Z.J. Wang, and P. Willett Joint segmentation and classification of time series using class-specific features Syst. Man, Cybern. Part B Cybern. IEEE Trans 34 2 2004 1056 1067
-
(2004)
Syst. Man, Cybern. Part B Cybern. IEEE Trans
, vol.34
, Issue.2
, pp. 1056-1067
-
-
Wang, Z.J.1
Willett, P.2
-
196
-
-
25144474901
-
Dimension reduction for clustering time series using global characteristics
-
X. Wang, K.A. Smith, and R.J. Hyndman Dimension reduction for clustering time series using global characteristics Comput. Sci. 2005 2005 792 795
-
(2005)
Comput. Sci. 2005
, pp. 792-795
-
-
Wang, X.1
Smith, K.A.2
Hyndman, R.J.3
-
198
-
-
33750563997
-
Principal component analysis based time series segmentation-application to hierarchical clustering for multivariate process data
-
J. Abonyi, B. Feil, S. Nemeth, P. Arva, Principal component analysis based time series segmentation-application to hierarchical clustering for multivariate process data, in: Proceedings of IEEE International Conference on Computational Cybernetics, 2005, pp. 29-31.
-
(2005)
Proceedings of IEEE International Conference on Computational Cybernetics
, pp. 29-31
-
-
Abonyi, J.1
Feil, B.2
Nemeth, S.3
Arva, P.4
-
199
-
-
30344477625
-
Efficiently mining gene expression data via a novel parameterless clustering method
-
V.S. Tseng, and C.P. Kao Efficiently mining gene expression data via a novel parameterless clustering method, IEEE/ACM Trans. Comput. Biol. Bioinforma 2 4 2005 355 365
-
(2005)
IEEE/ACM Trans. Comput. Biol. Bioinforma
, vol.2
, Issue.4
, pp. 355-365
-
-
Tseng, V.S.1
Kao, C.P.2
-
201
-
-
45849102089
-
A generalized model for financial time series representation and prediction
-
D. Bao A generalized model for financial time series representation and prediction, Appl. Intell. 29 1 2007 1 11
-
(2007)
Appl. Intell.
, vol.29
, Issue.1
, pp. 1-11
-
-
Bao, D.1
-
202
-
-
34248566914
-
Intelligent stock trading system by turning point confirming and probabilistic reasoning
-
D. Bao, and Z. Yang Intelligent stock trading system by turning point confirming and probabilistic reasoning Exp. Syst. Appl. 34 1 2008 620 627
-
(2008)
Exp. Syst. Appl.
, vol.34
, Issue.1
, pp. 620-627
-
-
Bao, D.1
Yang, Z.2
-
204
-
-
76349092798
-
Financial time series indexing based on low resolution clustering
-
T.C. Fu, F.L. Chung, R. Luk, C.M. Ng, Financial time series indexing based on low resolution clustering, in: Proceedings of the 4th IEEE International Conference on Data Mining (ICDM-2004), 2010, pp. 5-14.
-
(2010)
Proceedings of the 4th IEEE International Conference on Data Mining (ICDM-2004)
, pp. 5-14
-
-
Fu, T.C.1
Chung, F.L.2
Luk, R.3
Ng, C.M.4
-
205
-
-
80051606484
-
A novel two-level clustering method for time series data analysis
-
C.-P.P. Lai, P.-C.C. Chung, and V.S. Tseng A novel two-level clustering method for time series data analysis, Expert Syst. Appl. 37 9 2010 6319 6326
-
(2010)
Expert Syst. Appl.
, vol.37
, Issue.9
, pp. 6319-6326
-
-
Lai, C.-P.P.1
Chung, P.-C.C.2
Tseng, V.S.3
-
206
-
-
79955630000
-
A novel clustering method on time series data
-
X. Zhang, J. Liu, Y. Du, and T. Lv A novel clustering method on time series data Expert Syst. Appl. 38 9 2011 11891 11900
-
(2011)
Expert Syst. Appl.
, vol.38
, Issue.9
, pp. 11891-11900
-
-
Zhang, X.1
Liu, J.2
Du, Y.3
Lv, T.4
-
207
-
-
84874084961
-
Clustering time series using unsupervised-shapelets
-
J. Zakaria, A. Mueen, E. Keogh, Clustering time series using unsupervised-shapelets, in: Proceedings of 2012 IEEE 12th International Conference on Data Mining, 2012, pp. 785-794.
-
(2012)
Proceedings of 2012 IEEE 12th International Conference on Data Mining
, pp. 785-794
-
-
Zakaria, J.1
Mueen, A.2
Keogh, E.3
-
208
-
-
84875644445
-
Accelerating Bayesian hierarchical clustering of time series data with a randomised algorithm
-
R. Darkins, E.J. Cooke, Z. Ghahramani, P.D.W. Kirk, D.L. Wild, and R.S. Savage Accelerating Bayesian hierarchical clustering of time series data with a randomised algorithm PLoS One 8 4 2013 e59795
-
(2013)
PLoS One
, vol.8
, Issue.4
, pp. e59795
-
-
Darkins, R.1
Cooke, E.J.2
Ghahramani, Z.3
Kirk, P.D.W.4
Wild, D.L.5
Savage, R.S.6
-
209
-
-
84890504998
-
Mathematical programming formulations and algorithms for discrete k-median clustering of time-series data
-
O. Seref, Y.-J. Fan, and W.A. Chaovalitwongse Mathematical programming formulations and algorithms for discrete k-median clustering of time-series data INFORMS J. Comput. 26 1 2014 160 172
-
(2014)
INFORMS J. Comput.
, vol.26
, Issue.1
, pp. 160-172
-
-
Seref, O.1
Fan, Y.-J.2
Chaovalitwongse, W.A.3
-
211
-
-
84899535969
-
A hybrid algorithm for clustering of time series data based on affinity search technique
-
S. Aghabozorgi, T. Ying Wah, T. Herawan, H.A. Jalab, M.A. Shaygan, and A. Jalali A hybrid algorithm for clustering of time series data based on affinity search technique Sci.World J. 2014 2014 562194
-
(2014)
Sci.World J.
, vol.2014
, pp. 562194
-
-
Aghabozorgi, S.1
Ying Wah, T.2
Herawan, T.3
Jalab, H.A.4
Shaygan, M.A.5
Jalali, A.6
-
212
-
-
3142557753
-
E-CAST: A data mining algorithm for gene expression data
-
A. Bellaachia, D. Portnoy, Y. Chen, A.G. Elkahloun, E-CAST: a data mining algorithm for gene expression data, in: Workshop on Data Mining in Bioinformatics, 2002, pp. 49-54.
-
(2002)
Workshop on Data Mining in Bioinformatics
, pp. 49-54
-
-
Bellaachia, A.1
Portnoy, D.2
Chen, Y.3
Elkahloun, A.G.4
-
213
-
-
26944501204
-
A MPAA-based iterative clustering algorithm augmented by nearest neighbors search for time-series data streams
-
J. Lin, M. Vlachos, E. Keogh, D. Gunopulos, J. Liu, S. Yu, and J. Le A MPAA-based iterative clustering algorithm augmented by nearest neighbors search for time-series data streams Adv. Knowl. Discov. Data Min 2005 333 342
-
(2005)
Adv. Knowl. Discov. Data Min
, pp. 333-342
-
-
Lin, J.1
Vlachos, M.2
Keogh, E.3
Gunopulos, D.4
Liu, J.5
Yu, S.6
Le, J.7
-
214
-
-
0037410621
-
Visual cluster validity for prototype generator clustering models
-
R.J. Hathaway, and J.C. Bezdek Visual cluster validity for prototype generator clustering models Pattern Recognit. Lett 24 9-10 2003 1563 1569
-
(2003)
Pattern Recognit. Lett
, vol.24
, Issue.9-10
, pp. 1563-1569
-
-
Hathaway, R.J.1
Bezdek, J.C.2
-
217
-
-
67650932694
-
A comparison of extrinsic clustering evaluation metrics based on formal constraints
-
E. Amigó, J. Gonzalo, J. Artiles, and F. Verdejo A comparison of extrinsic clustering evaluation metrics based on formal constraints Inf. Retr. Boston 12 4 2009 461 486
-
(2009)
Inf. Retr. Boston
, vol.12
, Issue.4
, pp. 461-486
-
-
Amigó, E.1
Gonzalo, J.2
Artiles, J.3
Verdejo, F.4
-
221
-
-
80052676926
-
An effective evaluation measure for clustering on evolving data streams
-
H. Kremer, P. Kranen, T. Jansen, T. Seidl, A. Bifet, G. Holmes, B. Pfahringer, An effective evaluation measure for clustering on evolving data streams, in: Proceedings of the 17th ACM SIGKDD international conference on Knowledge Discovery and Data Mining, 2011, pp. 868-876.
-
(2011)
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
, pp. 868-876
-
-
Kremer, H.1
Kranen, P.2
Jansen, T.3
Seidl, T.4
Bifet, A.5
Holmes, G.6
Pfahringer, B.7
-
222
-
-
3543085722
-
Empirical and theoretical comparisons of selected criterion functions for document clustering
-
Y. Zhao, and G. Karypis Empirical and theoretical comparisons of selected criterion functions for document clustering, Mach. Learn. 55 3 2004 311 331
-
(2004)
Mach. Learn.
, vol.55
, Issue.3
, pp. 311-331
-
-
Zhao, Y.1
Karypis, G.2
-
223
-
-
2642570831
-
Time series clustering with ARMA mixtures
-
Y. Xiong, and D.Y. Yeung Time series clustering with ARMA mixtures, Pattern Recognit 37 8 2004 1675 1689
-
(2004)
Pattern Recognit
, vol.37
, Issue.8
, pp. 1675-1689
-
-
Xiong, Y.1
Yeung, D.Y.2
-
224
-
-
84945923591
-
A method for comparing two hierarchical clusterings
-
E. Fowlkes, and C.L. Mallows A method for comparing two hierarchical clusterings, J. Am. Stat. Assoc 78 383 1983 553 569
-
(1983)
J. Am. Stat. Assoc
, vol.78
, Issue.383
, pp. 553-569
-
-
Fowlkes, E.1
Mallows, C.L.2
-
225
-
-
70350647693
-
Adapting the right measures for k-means clustering
-
J. Wu, H. Xiong, J. Chen, Adapting the right measures for k-means clustering, in: Proceedings of the 15th ACM SIGKDD, 2009, pp. 877-886.
-
(2009)
Proceedings of the 15th ACM SIGKDD
, pp. 877-886
-
-
Wu, J.1
Xiong, H.2
Chen, J.3
-
226
-
-
84950632109
-
Objective criteria for the evaluation of clustering methods
-
W.M. Rand Objective criteria for the evaluation of clustering methods, J. Am. Stat. Assoc 66 336 1971 846 850
-
(1971)
J. Am. Stat. Assoc
, vol.66
, Issue.336
, pp. 846-850
-
-
Rand, W.M.1
-
227
-
-
0000008146
-
Comparing partitions
-
L. Hubert, and P. Arabie Comparing partitions, J. Classif. 2 1 1985 193 218
-
(1985)
J. Classif.
, vol.2
, Issue.1
, pp. 193-218
-
-
Hubert, L.1
Arabie, P.2
-
229
-
-
4344611435
-
Properties of the Hubert-Arable adjusted rand index
-
D. Steinley Properties of the Hubert-Arable adjusted rand index, Psychol. Methods 9 3 2004 386
-
(2004)
Psychol. Methods
, vol.9
, Issue.3
, pp. 386
-
-
Steinley, D.1
-
230
-
-
0035024021
-
Validating clustering for gene expression data
-
K.K. Yeung, D.D. Haynor, and W. Ruzzo Validating clustering for gene expression data, Bioinformatics 17 4 2001 309 318
-
(2001)
Bioinformatics
, vol.17
, Issue.4
, pp. 309-318
-
-
Yeung, K.K.1
Haynor, D.D.2
Ruzzo, W.3
-
231
-
-
0034782618
-
Model-based clustering and data transformations for gene expression data
-
K. Yeung, C. Fraley, A. Murua, A.E. Raftery, and W.L. Ruzzo Model-based clustering and data transformations for gene expression data Bioinformatics 17 10 2001 977 987
-
(2001)
Bioinformatics
, vol.17
, Issue.10
, pp. 977-987
-
-
Yeung, K.1
Fraley, C.2
Murua, A.3
Raftery, A.E.4
Ruzzo, W.L.5
-
234
-
-
0023014685
-
A non-classical logic for information retrieval
-
C.J. Van Rijsbergen A non-classical logic for information retrieval Comput. J. 29 6 1986 481 485
-
(1986)
Comput. J.
, vol.29
, Issue.6
, pp. 481-485
-
-
Van Rijsbergen, C.J.1
-
236
-
-
0032762144
-
An overlap invariant entropy measure of 3D medical image alignment
-
C. Studholme, D.L.G. Hill, and D.J. Hawkes An overlap invariant entropy measure of 3D medical image alignment, Pattern Recognit 32 1 1999 71 86
-
(1999)
Pattern Recognit
, vol.32
, Issue.1
, pp. 71-86
-
-
Studholme, C.1
Hill, D.L.G.2
Hawkes, D.J.3
-
237
-
-
0041965980
-
Cluster ensembles - A knowledge reuse framework for combining multiple partitions
-
A. Strehl, and J. Ghosh Cluster ensembles - a knowledge reuse framework for combining multiple partitions J. Mach. Learn. Res. 3 2003 583 617
-
(2003)
J. Mach. Learn. Res.
, vol.3
, pp. 583-617
-
-
Strehl, A.1
Ghosh, J.2
-
239
-
-
0001699630
-
Methods of comparing classifications
-
F. Rohlf Methods of comparing classifications Annu. Rev. Ecol. Syst. 1974 101 113
-
(1974)
Annu. Rev. Ecol. Syst.
, pp. 101-113
-
-
Rohlf, F.1
-
240
-
-
67049114699
-
Comparison of cluster representations from partial second-to full fourth-order cross moments for data stream clustering
-
S. Lin, M. Song, L. Zhang, Comparison of cluster representations from partial second-to full fourth-order cross moments for data stream clustering, in: Proceedings of the Eighth IEEE International Conference on Data Mining, 2008. ICDM '08, 2008, pp. 560-569.
-
(2008)
Proceedings of the Eighth IEEE International Conference on Data Mining, 2008. ICDM '08
, pp. 560-569
-
-
Lin, S.1
Song, M.2
Zhang, L.3
-
242
-
-
21844471761
-
Clustering of time-series subsequences is meaningless: Implications for previous and future research
-
E. Keogh, and J., Lin Clustering of time-series subsequences is meaningless: implications for previous and future research Knowledge and information systems 8 2 2005 154 177
-
(2005)
Knowledge and Information Systems
, vol.8
, Issue.2
, pp. 154-177
-
-
Keogh, E.1
Lin, J.2
|