-
2
-
-
84947593543
-
Mining changes for reallife applications
-
London: Springer
-
Liu B, Hsu W, HanHS, Xia Y. Mining changes for reallife applications. Proceedings of the 2nd International Conference on Data Warehousing and KnowledgeDiscovery, London: Springer; 2000, 337-346.
-
(2000)
Proceedings of the 2nd International Conference on Data Warehousing and KnowledgeDiscovery
, pp. 337-346
-
-
Liu, B.1
Hsu, W.2
Han, H.S.3
Xia, Y.4
-
4
-
-
24344498330
-
Mining data streams: a review
-
Gaber MM, Zaslavsky A, Krishnaswamy S. Mining data streams: a review. SIGMOD Rec 2005, 34:18-26. doi:http://doi.acm.org/10.1145/1083784.1083789.
-
(2005)
SIGMOD Rec
, vol.34
, pp. 18-26
-
-
Gaber, M.M.1
Zaslavsky, A.2
Krishnaswamy, S.3
-
6
-
-
10644220350
-
A framework for measuring differences in data characteristics
-
Ganti V, Gehrke J, Ramakrishnan R, Loh WY. A framework for measuring differences in data characteristics. J Comput Syst Sci 2002, 64:542-578. doi:http://dx.doi.org/10.1006/jcss.2001.1808.
-
(2002)
J Comput Syst Sci
, vol.64
, pp. 542-578
-
-
Ganti, V.1
Gehrke, J.2
Ramakrishnan, R.3
Loh, W.Y.4
-
7
-
-
61749084093
-
Supervised descriptive rule discovery: a unifying survey of contrast set, emerging pattern and subgroup mining
-
Novak PK, Lavrač N, Webb GI. Supervised descriptive rule discovery: a unifying survey of contrast set, emerging pattern and subgroup mining. J Mach Learn Res 2009, 10:377-403.
-
(2009)
J Mach Learn Res
, vol.10
, pp. 377-403
-
-
Novak, P.K.1
Lavrač, N.2
Webb, G.I.3
-
8
-
-
0035476841
-
Mining the change of customer behavior in an internet shopping mall
-
Song HS, Kim JK, Kim SH. Mining the change of customer behavior in an internet shopping mall. Expert Syst Appl 2001, 21:157-168.
-
(2001)
Expert Syst Appl
, vol.21
, pp. 157-168
-
-
Song, H.S.1
Kim, J.K.2
Kim, S.H.3
-
9
-
-
17844377335
-
Mining changes in customer behavior in retail marketing
-
Chen MC, Chiu AL, Chang HH. Mining changes in customer behavior in retail marketing. Expert Syst Appl 2005, 28:773-781.
-
(2005)
Expert Syst Appl
, vol.28
, pp. 773-781
-
-
Chen, M.C.1
Chiu, A.L.2
Chang, H.H.3
-
10
-
-
33745187176
-
Detecting the change of customer behavior based on decision tree analysis
-
Kim JK, Song HS, Kim TS, Kim HK. Detecting the change of customer behavior based on decision tree analysis. Expert Syst 2005, 22:193-205.
-
(2005)
Expert Syst
, vol.22
, pp. 193-205
-
-
Kim, J.K.1
Song, H.S.2
Kim, T.S.3
Kim, H.K.4
-
11
-
-
57749111947
-
A change detection method for sequential patterns
-
Tsai CY, Shieh YC. A change detection method for sequential patterns. Decis Support Syst 2009, 46:501-511. doi:http://dx.doi.org/10.1016/j.dss.2008.09.003.
-
(2009)
Decis Support Syst
, vol.46
, pp. 501-511
-
-
Tsai, C.Y.1
Shieh, Y.C.2
-
12
-
-
29844455221
-
What's new: finding significant differences in network data streams
-
Cormode G, Muthukrishnan S. What's new: finding significant differences in network data streams. IEEE/ ACM Trans Netw 2005, 13:1219-1232. doi:http:// dx.doi.org/10.1109/TNET.2005.860096.
-
(2005)
IEEE/ ACM Trans Netw
, vol.13
, pp. 1219-1232
-
-
Cormode, G.1
Muthukrishnan, S.2
-
14
-
-
33745843245
-
A framework for discovering interesting business changes from data
-
Böttcher M, Nauck D, Borgelt C, Kruse R. A framework for discovering interesting business changes from data. BT Technol J 2006, 24:219-228. doi:http:// dx.doi.org/10.1007/s10550-006-0064-3.
-
(2006)
BT Technol J
, vol.24
, pp. 219-228
-
-
Böttcher, M.1
Nauck, D.2
Borgelt, C.3
Kruse, R.4
-
15
-
-
53849105788
-
Mining changing customer segments in dynamic markets
-
Böttcher M, Spott M, Nauck D, Kruse R. Mining changing customer segments in dynamic markets. Expert Syst Appl 2009; 36(1):155-164. doi:http:// dx.doi.org/10.1016/j.eswa.2007.09.006.
-
(2009)
Expert Syst Appl
, vol.36
, Issue.1
, pp. 155-164
-
-
Böttcher, M.1
Spott, M.2
Nauck, D.3
Kruse, R.4
-
18
-
-
0010012318
-
Incremental learning from noisy data
-
Schlimmer JC, Granger RH. Incremental learning from noisy data. Mach Learn 1986, 1:317-354.
-
(1986)
Mach Learn
, vol.1
, pp. 317-354
-
-
Schlimmer, J.C.1
Granger, R.H.2
-
19
-
-
0030126609
-
Learning in the presence of concept drift and hidden contexts
-
Widmer G, Kubat M. Learning in the presence of concept drift and hidden contexts. Mach Learn 1996, 23:69-101. doi:http://dx.doi.org/10.1023/A: 1018046501280.
-
(1996)
Mach Learn
, vol.23
, pp. 69-101
-
-
Widmer, G.1
Kubat, M.2
-
21
-
-
17744362879
-
On the complexity of finding emerging patterns
-
Wang L, Zhao H, Dong G, Li J. On the complexity of finding emerging patterns. Theor Compu Sci 2005, 335:15-27. doi:http://dx.doi.org/10.1016/ j.tcs.2004.12.014.
-
(2005)
Theor Compu Sci
, vol.335
, pp. 15-27
-
-
Wang, L.1
Zhao, H.2
Dong, G.3
Li, J.4
-
22
-
-
21844446593
-
Mining border descriptions of emerging patterns from dataset pairs
-
Dong G, Li J. Mining border descriptions of emerging patterns from dataset pairs. Knowl Inf Syst 2005, 8:178-202. doi:http://dx.doi.org/10.1007/s10115-004-0178-1.
-
(2005)
Knowl Inf Syst
, vol.8
, pp. 178-202
-
-
Dong, G.1
Li, J.2
-
23
-
-
53849141859
-
Efficient mining of temporal emerging itemsets from data streams
-
Chu CJ, Tseng VS, Liang T. Efficient mining of temporal emerging itemsets from data streams. Expert Syst Appl 2009, 36:885-893. doi:http://dx.doi.org/ 10.1016/j.eswa.2007.10.040.
-
(2009)
Expert Syst Appl
, vol.36
, pp. 885-893
-
-
Chu, C.J.1
Tseng, V.S.2
Liang, T.3
-
25
-
-
33749665453
-
Efficiently mining interesting emerging patterns
-
Berlin, Heidelberg, New York: Springer, doi:10.1007/b11939
-
Fan H, Ramamohanarao K. Efficiently mining interesting emerging patterns. Advances in Web-Age Information Management, Lecture Notes in Computer Science, vol. 2762, Berlin, Heidelberg, New York: Springer; 2003, 189-201. doi:10.1007/b11939.
-
(2003)
Advances in Web-Age Information Management, Lecture Notes in Computer Science
, vol.2762
, pp. 189-201
-
-
Fan, H.1
Ramamohanarao, K.2
-
26
-
-
7444263001
-
Condensed representation of emerging patterns
-
8th Pacific-Asia Conference, PAKDD 2004, Lecture Notes in Computer Science, Berlin, Heidelberg, New York: Springer
-
Soulet A, Crémilleux B, Rioult F. Condensed representation of emerging patterns. Advances in Knowledge Discovery and Data Mining, 8th Pacific-Asia Conference, PAKDD 2004, Lecture Notes in Computer Science, vol. 3056, Berlin, Heidelberg, New York: Springer; 2004, 127-132.
-
(2004)
Advances in Knowledge Discovery and Data Mining
, vol.3056
, pp. 127-132
-
-
Soulet, A.1
Crémilleux, B.2
Rioult, F.3
-
28
-
-
85053374465
-
Making use of the most expressive jumping emerging patterns for classification
-
Li J, Dong G, Ramamohanarao K. Making use of the most expressive jumping emerging patterns for classification. Knowl Inf Syst 2001, 3:1-29.
-
(2001)
Knowl Inf Syst
, vol.3
, pp. 1-29
-
-
Li, J.1
Dong, G.2
Ramamohanarao, K.3
-
29
-
-
0002479811
-
Exploration of the power of attributeoriented induction in data mining
-
Fayyad UM, Piatetsky-Shapiro G, Smyth P, Uthurusamy R eds. Menlo Park, CA: AAAI/MIT Press
-
Han J, Fu Y. Exploration of the power of attributeoriented induction in data mining. In: Fayyad UM, Piatetsky-Shapiro G, Smyth P, Uthurusamy R eds. Advances in Knowledge Discovery and Data Mining. Menlo Park, CA: AAAI/MIT Press; 1996, 83-115.
-
(1996)
Advances in Knowledge Discovery and Data Mining
, pp. 83-115
-
-
Han, J.1
Fu, Y.2
-
30
-
-
33749652718
-
On the relation between rough set reducts and jumping emerging patterns
-
Terlecki P, Walczak K. On the relation between rough set reducts and jumping emerging patterns. Inf Sci 2007, 177:74-83. doi:DOI:10.1016/j.ins. 2006.04.002.
-
(2007)
Inf Sci
, vol.177
, pp. 74-83
-
-
Terlecki, P.1
Walczak, K.2
-
32
-
-
23044527560
-
Detecting group differences: Mining contrast sets
-
Bay SD, Pazzani MJ. Detecting group differences: Mining contrast sets. Data Min Knowl Discovery 2001, 5:213-246. doi:http://dx.doi.org/10.1023/A: 1011429418057.
-
(2001)
Data Min Knowl Discovery
, vol.5
, pp. 213-246
-
-
Bay, S.D.1
Pazzani, M.J.2
-
34
-
-
22144470180
-
Mining negative contrast sets from data with discrete attributes
-
Wong TT, Tseng KL. Mining negative contrast sets from data with discrete attributes. Expert Syst Appl 2005, 29:401-407.
-
(2005)
Expert Syst Appl
, vol.29
, pp. 401-407
-
-
Wong, T.T.1
Tseng, K.L.2
-
36
-
-
44649190568
-
Unsupervised change analysis using supervised learning
-
Berlin, Heidelberg, New York: Springer
-
Hido S, Idé T, Kashima H, Kubo H, Matsuzawa H. Unsupervised change analysis using supervised learning. Proceedings of the 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2008), Lecture Notes in Computer Science, vol. 5012, Berlin, Heidelberg, New York: Springer; 2008, 148-159.
-
(2008)
Proceedings of the 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2008), Lecture Notes in Computer Science
, vol.5012
, pp. 148-159
-
-
Hido, S.1
Idé, T.2
Kashima, H.3
Kubo, H.4
Matsuzawa, H.5
-
39
-
-
33744584654
-
Induction of decision trees
-
Quinlan JR. Induction of decision trees. Mach Learn 1986, 1:81-106.
-
(1986)
Mach Learn
, vol.1
, pp. 81-106
-
-
Quinlan, J.R.1
-
40
-
-
18444373554
-
A survey on tree edit distance and related problems
-
Bille P. A survey on tree edit distance and related problems. Theor Comput Sci 2005, 337:217-239. doi:http://dx.doi.org/10.1016/j.tcs.2004.12.030.
-
(2005)
Theor Comput Sci
, vol.337
, pp. 217-239
-
-
Bille, P.1
-
41
-
-
0029309548
-
Alignment of trees-an alternative to tree edit
-
Jiang T, Wang L, Zhang K. Alignment of trees-an alternative to tree edit. Theor Comput Sci 1995, 143:137-148.
-
(1995)
Theor Comput Sci
, vol.143
, pp. 137-148
-
-
Jiang, T.1
Wang, L.2
Zhang, K.3
-
42
-
-
0030344230
-
The heuristics of instability in model selection
-
Breiman L. The heuristics of instability in model selection. Ann Stat 1996, 24:2350-2383.
-
(1996)
Ann Stat
, vol.24
, pp. 2350-2383
-
-
Breiman, L.1
-
44
-
-
37949048565
-
Mining changes of classification by correspondence tracing
-
Philadelphia, PA: SIAM
-
Wang K, Zhou S, Fu AWC, Yu JX. Mining changes of classification by correspondence tracing. Proceedings of the 3rd SIAM International Conference on Data Mining (SDM-03). Philadelphia, PA: SIAM; 2003, 95-106.
-
(2003)
Proceedings of the 3rd SIAM International Conference on Data Mining (SDM-03)
, pp. 95-106
-
-
Wang, K.1
Zhou, S.2
Fu, A.W.C.3
Yu, J.X.4
-
46
-
-
36849089105
-
Efficient and effective explanation of change in hierarchical summaries
-
New York: ACM
-
Agarwal D, Barman D, Gunopulos D, Young NE, Korn F, Srivastava D. Efficient and effective explanation of change in hierarchical summaries. KDD '07: Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York: ACM; 2007, 6-15. doi:http://doi.acm.org/ 10.1145/1281192.1281197.
-
(2007)
KDD '07: Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
, pp. 6-15
-
-
Agarwal, D.1
Barman, D.2
Gunopulos, D.3
Young, N.E.4
Korn, F.5
Srivastava, D.6
-
47
-
-
0004161991
-
Algorithms for clustering data
-
NJ: Prentice-Hall, Inc.
-
Jain AK, Dubes RC. Algorithms for clustering data. Upper Saddle River, NJ: Prentice-Hall, Inc.; 1988.
-
(1988)
Upper Saddle River
-
-
Jain, A.K.1
Dubes, R.C.2
-
48
-
-
33646723902
-
Data clustering: a user's dilemma
-
Springer
-
Jain AK, LawMHC. Data clustering: a user's dilemma. In: Pal SK, Bandyopadhyay S, Biswas S, eds. First International Conference on Pattern Recognition and Machine Intelligence (PReMI 2005), Lecture Notes in Computer Science, vol. 3776, Springer; 2005, 1-10. doi:http://dx.doi.org/10.1007/115903161.
-
(2005)
First International Conference on Pattern Recognition and Machine Pal SK, Bandyopadhyay S, Biswas S, eds. Intelligence (PReMI 2005), Lecture Notes in Computer Science
, vol.3776
-
-
Jain, A.K.1
Law, M.H.C.2
-
50
-
-
26944480755
-
Visualization of cluster changes by comparing self-organizing maps
-
Berlin, Heidelberg: Springer-Verlag
-
Denny, Squire DM. Visualization of cluster changes by comparing self-organizing maps. Proceedings of the 9th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Lecture Notes in Computer Science, vol. 3518, Berlin, Heidelberg: Springer-Verlag; 2005, 410-419.
-
(2005)
Proceedings of the 9th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Lecture Notes in Computer Science
, vol.3518
, pp. 410-419
-
-
Denny, S.D.M.1
-
52
-
-
67049100143
-
Redsom: relative density visualization of temporal changes in cluster structures using self-organizing maps
-
Washington, DC: IEEE Computer Society
-
Denny, Williams GJ, Christen P. Redsom: relative density visualization of temporal changes in cluster structures using self-organizing maps. ICDM '08: Proceedings of the 8th IEEE International Conference on Data Mining. Washington, DC: IEEE Computer Society; 2008, 173-182. doi:http://dx.doi.org/10.1109/ICDM.2008.34.
-
(2008)
ICDM '08: Proceedings of the 8th IEEE International Conference on Data Mining
, pp. 173-182
-
-
Denny, W.G.J.1
Christen, P.2
-
53
-
-
78049429522
-
Visualizing temporal cluster changes using relative density selforganizing maps
-
doi: 10.1007/s10115-009-0264-5
-
Denny, Williams GJ, Christen P. Visualizing temporal cluster changes using relative density selforganizing maps. Knowl Inf Syst 2009, 25:281-302. doi: 10.1007/s10115-009-0264-5.
-
(2009)
Knowl Inf Syst
, vol.25
, pp. 281-302
-
-
Denny, W.G.J.1
Christen, P.2
-
54
-
-
85012236181
-
A framework for clustering evolving data streams
-
Aggarwal CC, Han J, Wang J, Yu PS. A framework for clustering evolving data streams. VLDB '2003: Proceedings of the 29th International Conference on Very Large Data Bases, VLDB Endowment, 2003, 81-92.
-
(2003)
VLDB '2003: Proceedings of the 29th International Conference on Very Large Data Bases, VLDB Endowment
, pp. 81-92
-
-
Aggarwal, C.C.1
Han, J.2
Wang, J.3
Yu, P.S.4
-
55
-
-
71349088018
-
HE-tree: a framework for detecting changes in clustering structure for categorical data streams
-
Chen K, Liu L. HE-tree: a framework for detecting changes in clustering structure for categorical data streams. VLDB J 2009, 18:1241-1260.
-
(2009)
VLDB J
, vol.18
, pp. 1241-1260
-
-
Chen, K.1
Liu, L.2
-
56
-
-
34247618448
-
A unified and flexible framework for comparing simple and complex patterns
-
New York: Springer-Verlag, Inc.
-
Bartolini I, Ciaccia P, Ntoutsi I, Patella M, Theodoridis Y. A unified and flexible framework for comparing simple and complex patterns. PKDD '04: Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases, Lecture Notes In Computer Science, vol. 3202, New York: Springer-Verlag, Inc.; 2004, 496-499.
-
(2004)
PKDD '04: Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases, Lecture Notes In Computer Science
, vol.3202
, pp. 496-499
-
-
Bartolini, I.1
Ciaccia, P.2
Ntoutsi, I.3
Patella, M.4
Theodoridis, Y.5
-
57
-
-
57649195435
-
The PANDA framework for comparing patterns
-
Bartolini I, Ciaccia P, Ntoutsi I, Patella M, Theodoridis Y. The PANDA framework for comparing patterns. Data Knowl Eng 2009, 68:244-260. doi:http:// dx.doi.org/10.1016/j.datak.2008.10.004.
-
(2009)
Data Knowl Eng
, vol.68
, pp. 244-260
-
-
Bartolini, I.1
Ciaccia, P.2
Ntoutsi, I.3
Patella, M.4
Theodoridis, Y.5
-
58
-
-
58549112709
-
Higher order mining
-
Roddick JF, Spiliopoulou M, Lister D, Ceglar A. Higher order mining. SIGKDD Explor Newsl 2008, 10:5-17. doi:http://doi.acm.org/10.1145/1412734. 1412736.
-
(2008)
SIGKDD Explor Newsl
, vol.10
, pp. 5-17
-
-
Roddick, J.F.1
Spiliopoulou, M.2
Lister, D.3
Ceglar, A.4
-
59
-
-
38849098533
-
Managing large collections of data mining models
-
Liu B, Tuzhilin A. Managing large collections of data mining models. Commun ACM 2008, 51:85-89. doi:http://doi.acm.org/10.1145/1314215.1314230.
-
(2008)
Commun ACM
, vol.51
, pp. 85-89
-
-
Liu, B.1
Tuzhilin, A.2
-
60
-
-
33749319347
-
Interestingness measures for data mining: a survey
-
Geng L, Hamilton HJ. Interestingness measures for data mining: a survey. ACM Comput Surv 2006, 38:9. doi:http://doi.acm.org/10.1145/1132960.1132963.
-
(2006)
ACM Comput Surv
, vol.38
, pp. 9
-
-
Geng, L.1
Hamilton, H.J.2
-
62
-
-
0004135895
-
-
Boca Raton, London, New York: Chapman and Hall/CRC
-
Chatfield C. Time-Series Forecasting. Boca Raton, London, New York: Chapman and Hall/CRC; 2001.
-
(2001)
Time-Series Forecasting
-
-
Chatfield, C.1
-
63
-
-
84954134641
-
Active data mining
-
Fayyad UM, Uthurusamy R, eds. Menlo Park, CA: AAAI Press
-
Agrawal R, Psaila G. Active data mining. In: Fayyad UM, Uthurusamy R, eds. Proceedings of the 1st ACM SIGKDD International Conference on KnowledgeDiscovery and Data Mining. Menlo Park, CA: AAAI Press; 1995, 3-8.
-
(1995)
Proceedings of the 1st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
, pp. 3-8
-
-
Agrawal, R.1
Psaila, G.2
-
64
-
-
9644300959
-
Mining changes in association rules: a fuzzy approach
-
Au WH, Chan K. Mining changes in association rules: a fuzzy approach. Fuzzy Sets Syst 2005, 149:87-104.
-
(2005)
Fuzzy Sets Syst
, vol.149
, pp. 87-104
-
-
Au, W.H.1
Chan, K.2
-
66
-
-
84958044742
-
On similarity queries for time-series data: constraint specification and implementation
-
Berlin, Heidelberg, New York: Springer
-
Goldin DQ, Kanellakis PC. On similarity queries for time-series data: constraint specification and implementation. Proceedings of the 1st International Conference on Principles and Practice of Constraint Programming, Lecture Notes in Computer Science, vol. 976, Berlin, Heidelberg, New York: Springer; 1995, 137-153.
-
(1995)
Proceedings of the 1st International Conference on Principles and Practice of Constraint Programming, Lecture Notes in Computer Science
, vol.976
, pp. 137-153
-
-
Goldin, D.Q.1
Kanellakis, P.C.2
-
68
-
-
78149338936
-
Analyzing the interestingness of association rules from the temporal dimension
-
Berlin, Heidelberg, New York: IEEE Computer Society
-
Liu B, Ma Y, Lee R. Analyzing the interestingness of association rules from the temporal dimension. Proceedings of the IEEE International Conference on Data Mining. Berlin, Heidelberg, New York: IEEE Computer Society; 2001, 377-384.
-
(2001)
Proceedings of the IEEE International Conference on Data Mining
, pp. 377-384
-
-
Liu, B.1
Ma, Y.2
Lee, R.3
-
69
-
-
84873281579
-
Towards a framework for change detection in datasets
-
Bramer M, Coenen F, Tuson A, eds. London: BCS SGAI, Springer
-
Böttcher M, Nauck D, Ruta D, Spott M. Towards a framework for change detection in datasets. In: Bramer M, Coenen F, Tuson A, eds. Research and Development in Intelligent Systems XXIII, Proceedings of AI-2006, the 26th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, London: BCS SGAI, Springer; 2006, 115-128.
-
(2006)
Research and Development in Intelligent Systems XXIII, Proceedings of AI-2006, the 26th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence
, pp. 115-128
-
-
Böttcher, M.1
Nauck, D.2
Ruta, D.3
Spott, M.4
-
70
-
-
84873138721
-
Relevance feedback for association rules by leveraging concepts from information retrieval
-
Bramer M, Coenen F, Petridis M, eds. London: BCS SGAI, Springer
-
Russ G, Böttcher M, Nauck D, Kruse R. Relevance feedback for association rules by leveraging concepts from information retrieval. In: Bramer M, Coenen F, Petridis M, eds. Research and Development in Intelligent Systems XXIV, Proceedings of AI-2007, the 27th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, London: BCS SGAI, Springer; 2007, 253-266. doi:http://dx.doi.org/10.1007/978-1-84800-094-0 19.
-
(2007)
Research and Development in Intelligent Systems XXIV, Proceedings of AI-2007, the 27th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence
, pp. 253-266
-
-
Russ, G.1
Böttcher, M.2
Nauck, D.3
Kruse, R.4
-
72
-
-
33745767871
-
Efficient monitoring of patterns in data mining environments
-
Berlin, Heidelberg, New York: Springer
-
Baron S, Spiliopoulou M, Günther O. Efficient monitoring of patterns in data mining environments. Proceedings of the 7th East-European Conference on Advances in Databases and Information Systems (ADBIS'03), Lecture Notes in Computer Science, vol. 2798, Berlin, Heidelberg, New York: Springer; 2003, 253-265.
-
(2003)
Proceedings of the 7th East-European Conference on Advances in Databases and Information Systems (ADBIS'03), Lecture Notes in Computer Science
, vol.2798
, pp. 253-265
-
-
Baron, S.1
Spiliopoulou, M.2
Günther, O.3
-
75
-
-
0018015137
-
Modeling by shortest data description
-
Rissanen J. Modeling by shortest data description. Automatica 1978, 14:465-471.
-
(1978)
Automatica
, vol.14
, pp. 465-471
-
-
Rissanen, J.1
-
76
-
-
43249088014
-
Tracking clusters in evolving data streams over sliding windows
-
Zhou A, Cao F, Qian W, Jin C. Tracking clusters in evolving data streams over sliding windows. Knowl Inf Syst 2008, 15:181-214. doi:http://dx.doi.org/ 10.1007/s10115-007-0070-x.
-
(2008)
Knowl Inf Syst
, vol.15
, pp. 181-214
-
-
Zhou, A.1
Cao, F.2
Qian, W.3
Jin, C.4
-
77
-
-
57949108012
-
Movstream: an efficient algorithm for monitoring clusters evolving in data streams
-
Tang L, Tang CJ, Duan L, Li C, Jiang YX, Zeng CQ, Zhu J. Movstream: an efficient algorithm for monitoring clusters evolving in data streams. IEEE International Conference on Granular Computing (GrC 2008), IEEE Computer Society; 2008, 582-587. doi:10.1109/GRC.2008.4664715.
-
(2008)
IEEE International Conference on Granular Computing (GrC 2008), IEEE Computer Society
, pp. 582-587
-
-
Tang, L.1
Tang, C.J.2
Duan, L.3
Li, C.4
Jiang, Y.X.5
Zeng, C.Q.6
Zhu, J.7
-
78
-
-
33749564726
-
MONIC: modeling and monitoring cluster transitions
-
New York: ACM
-
Spiliopoulou M, Ntoutsi I, Theodoridis Y, Schult R. MONIC: modeling and monitoring cluster transitions. Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York: ACM; 2006, 706-711. doi:http://doi.acm.org/10.1145/1150402.1150491.
-
(2006)
Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
, pp. 706-711
-
-
Spiliopoulou, M.1
Ntoutsi, I.2
Theodoridis, Y.3
Schult, R.4
-
79
-
-
77953738183
-
Bipartite graphs for monitoring clusters transitions
-
Berlin/Heidelberg: Springer, doi:10.1007/978-3-642-13062-5 12
-
Oliveira M, Gama J. Bipartite graphs for monitoring clusters transitions. Advances in Intelligent Data Analysis IX, Lecture Notes in Computer Science, vol. 6065, Berlin/Heidelberg: Springer; 2010, 114-124. doi:10.1007/978-3-642-13062-5 12.
-
(2010)
Advances in Intelligent Data Analysis IX, Lecture Notes in Computer Science
, vol.6065
, pp. 114-124
-
-
Oliveira, M.1
Gama, J.2
-
80
-
-
30244462467
-
Algorithmic complexity: three NP-hard problems in computational statistics
-
Welch WJ. Algorithmic complexity: three NP-hard problems in computational statistics. J Stat Comput Simul 1982, 15:17-25.
-
(1982)
J Stat Comput Simul
, vol.15
, pp. 17-25
-
-
Welch, W.J.1
-
82
-
-
0024896089
-
Floating approximation in time-varying knowledge bases
-
Kubat M. Floating approximation in time-varying knowledge bases. Pattern Recognit Lett 1989, 10:223-227.
-
(1989)
Pattern Recognit Lett
, vol.10
, pp. 223-227
-
-
Kubat, M.1
-
83
-
-
0002896413
-
Tracking drifting concepts by minimizing disagreements
-
Helmbold DP, Long PM. Tracking drifting concepts by minimizing disagreements. Mach Learn 1994, 14:27-45.
-
(1994)
Mach Learn
, vol.14
, pp. 27-45
-
-
Helmbold, D.P.1
Long, P.M.2
-
84
-
-
0141741870
-
-
San Francisco, CA: Morgan Kaufmann Publishers Inc.
-
Kuh A, Petsche T, Rivest RL. Learning time-varying concepts. NIPS-3: Proceedings of the 1990 Conference on Advances in Neural Information Processing Systems 3, San Francisco, CA: Morgan Kaufmann Publishers Inc.; 1990, 183-189.
-
(1990)
Learning time-varying concepts. NIPS-3: Proceedings of the 1990 Conference on Advances in Neural Information Processing Systems 3
, pp. 183-189
-
-
Kuh, A.1
Petsche, T.2
Rivest, R.L.3
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