-
5
-
-
0036110853
-
Finding motifs using random projections
-
Buhler, J., & Tompa, M. (2002). Finding motifs using random projections. Journal of Computational Biology, 9(2), 225-242.
-
(2002)
Journal of Computational Biology
, vol.9
, Issue.2
, pp. 225-242
-
-
Buhler, J.1
Tompa, M.2
-
6
-
-
52949149390
-
Analysis of time series data with predictive clustering trees
-
Berlin, Germany
-
Dzeroski, S., Slavkov, I., Gjorgjioski, V., & Struyf, J. (2006). Analysis of time series data with predictive clustering trees. In 5th International Workshop on Knowledge Discovery in Inductive Databases (pp. 47-58). Berlin, Germany.
-
(2006)
5th International Workshop on Knowledge Discovery in Inductive Databases
, pp. 47-58
-
-
Dzeroski, S.1
Slavkov, I.2
Gjorgjioski, V.3
Struyf, J.4
-
7
-
-
44449144279
-
Protein sequence classification through relevant sequence mining and Bayes classifiers
-
Ferreira, P. G., & Azevedo, P. J. (2005). Protein sequence classification through relevant sequence mining and Bayes classifiers. In 12th Portuguese Conference on AI.
-
(2005)
12th Portuguese Conference on AI
-
-
Ferreira, P.G.1
Azevedo, P.J.2
-
8
-
-
33750736111
-
Mining approximate motifs in time series
-
Barcelona
-
Ferreira, P. G., Azevedo, P. J., Silva, C. G., & Brito, R. M. M. (2006). Mining approximate motifs in time series. In 9th International Conference on Discovery Science. Barcelona.
-
(2006)
9th International Conference on Discovery Science
-
-
Ferreira, P.G.1
Azevedo, P.J.2
Silva, C.G.3
Brito, R.M.M.4
-
10
-
-
78149294679
-
Mining generalized association rules for sequential and path data
-
San Jose
-
Gaul, W., & Schmidt-Thieme, L. (2001). Mining generalized association rules for sequential and path data. In IEEE ICMD (pp. 593-596). San Jose.
-
(2001)
IEEE ICMD
, pp. 593-596
-
-
Gaul, W.1
Schmidt-Thieme, L.2
-
12
-
-
33749395907
-
A new algorithm for faster mining of generalized association rules
-
Nantes, France
-
Hipp, J., Myka, A., Wirth, R., & Gntzer, U. (1998). A new algorithm for faster mining of generalized association rules. In PKDD (pp. 74-82). Nantes, France.
-
(1998)
PKDD
, pp. 74-82
-
-
Hipp, J.1
Myka, A.2
Wirth, R.3
Gntzer, U.4
-
13
-
-
30344460682
-
A generic motif discovery algorithm for sequential data
-
Jensen, K. L., Styczynski, M. P., Rigoutsos, I., & Stephanopoulos, G. N. (2006). A generic motif discovery algorithm for sequential data. Bioinformatics, 22, 21-28.
-
(2006)
Bioinformatics
, vol.22
, pp. 21-28
-
-
Jensen, K.L.1
Styczynski, M.P.2
Rigoutsos, I.3
Stephanopoulos, G.N.4
-
14
-
-
0034592912
-
Scaling up dynamic time warping for datamining applications
-
Boston, MA, USA
-
Keogh, E. J., & Pazzani, M. J. (2000). Scaling up dynamic time warping for datamining applications. In KDD (pp. 285-289). Boston, MA, USA.
-
(2000)
KDD
, pp. 285-289
-
-
Keogh, E.J.1
Pazzani, M.J.2
-
15
-
-
77955161917
-
Identifying patients at risk: Mining dialysis treatment data
-
Berlin
-
Knorr, T. (2006a). Identifying patients at risk: Mining dialysis treatment data. In 2nd German Japanese Symposium on Classification. Berlin.
-
(2006)
2nd German Japanese Symposium on Classification
-
-
Knorr, T.1
-
17
-
-
33745495992
-
Motif extraction and protein classification
-
Kunik, V., Solan, Z., Edelman, S., Ruppin, E., & Horn, D. (2005). Motif extraction and protein classification. In IEEE Computational Systems Bioinformatics Conference.
-
(2005)
IEEE Computational Systems Bioinformatics Conference
-
-
Kunik, V.1
Solan, Z.2
Edelman, S.3
Ruppin, E.4
Horn, D.5
-
18
-
-
33745781710
-
A symbolic representation of time series, with implications for streaming algorithms
-
Lin, J., Keogh, E., Lonardi, S., & Chiu, B. (2003). A symbolic representation of time series, with implications for streaming algorithms. In 8th ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery.
-
(2003)
8th ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery
-
-
Lin, J.1
Keogh, E.2
Lonardi, S.3
Chiu, B.4
-
21
-
-
2442567436
-
Mining motifs in massive time series databases
-
Patel, P., Keogh, E., Lin, J., & Lonardi, S. (2002). Mining motifs in massive time series databases. In IEEE ICDM.
-
(2002)
IEEE ICDM
-
-
Patel, P.1
Keogh, E.2
Lin, J.3
Lonardi, S.4
-
22
-
-
13844256245
-
Mining sequential patterns by pattern-growth: The prefixspan approach
-
Pei, J., Han, J., Wang, J., Pinto, H., Chen, Q., Dayal, U., et al. (2004). Mining sequential patterns by pattern-growth: The prefixspan approach. IEEE Transactions on Knowledge and Data Engineering, 16, 1424-1440.
-
(2004)
IEEE Transactions on Knowledge and Data Engineering
, vol.16
, pp. 1424-1440
-
-
Pei, J.1
Han, J.2
Wang, J.3
Pinto, H.4
Chen, Q.5
Dayal, U.6
-
26
-
-
0042440996
-
Word image matching using dynamic time wrapping
-
Rath, T. M., & Manmatha, R. (2003). Word image matching using dynamic time wrapping. CVPR, II, 521-527.
-
(2003)
CVPR
, vol.2
, pp. 521-527
-
-
Rath, T.M.1
Manmatha, R.2
-
27
-
-
0017930815
-
Dynamic programming algorithm optimization for spoken word recognition
-
Sakoe, H., & Chiba, S. (1978). Dynamic programming algorithm optimization for spoken word recognition. IEEE Transactions on Acoustics, Speech, and Signal Processing, ASSP-26, 43-49.
-
(1978)
IEEE Transactions on Acoustics, Speech, and Signal Processing, ASSP-26
, pp. 43-49
-
-
Sakoe, H.1
Chiba, S.2
-
28
-
-
0002623130
-
Mining sequential patterns: Generalizations and performance improvements
-
Avignon, France
-
Srikant, R., & Agrawal, R. (1996). Mining sequential patterns: Generalizations and performance improvements. In EDBT. Avignon, France.
-
(1996)
EDBT
-
-
Srikant, R.1
Agrawal, R.2
-
29
-
-
33749413116
-
A new method for finding generalized frequent itemsets in generalizes association rule mining
-
Taormina, Italy
-
Sriphaew, K., & Theeramunkong, T. (2002). A new method for finding generalized frequent itemsets in generalizes association rule mining. In ISCC (pp. 1040-1045). Taormina, Italy.
-
(2002)
ISCC
, pp. 1040-1045
-
-
Sriphaew, K.1
Theeramunkong, T.2
-
30
-
-
1642409826
-
Fast algorithms for mining generalized frequent patterns of generalized association rules
-
Sriphaew, K., & Theeramunkong, T. (2004). Fast algorithms for mining generalized frequent patterns of generalized association rules. IEICE Transactions on Information and Systems, E87-D(3), 761-770.
-
(2004)
IEICE Transactions on Information and Systems
, vol.E87-D
, Issue.3
, pp. 761-770
-
-
Sriphaew, K.1
Theeramunkong, T.2
-
31
-
-
36849013559
-
Detecting time series motifs under uniform scaling
-
San Jose, CA, USA
-
Yankov, D., Keogh, E., Medina, J., Chiu, B., & Zordan, V. (2007). Detecting time series motifs under uniform scaling. In KDD (pp. 844-853). San Jose, CA, USA.
-
(2007)
KDD
, pp. 844-853
-
-
Yankov, D.1
Keogh, E.2
Medina, J.3
Chiu, B.4
Zordan, V.5
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