-
1
-
-
84864030546
-
Big data: The next frontier for innovation, competition, and productivity
-
J. Manyika, M. Chui, B. Brown, J. Bughin, R. Dobbs, C. Roxburgh, and A. H. Byers, "Big data: The next frontier for innovation, competition, and productivity," McKinsey Global Inst., pp. 1-137, 2011.
-
(2011)
McKinsey Global Inst.
, pp. 1-137
-
-
Manyika, J.1
Chui, M.2
Brown, B.3
Bughin, J.4
Dobbs, R.5
Roxburgh, C.6
Byers, A.H.7
-
3
-
-
77950369345
-
Data clustering: 50 years beyond k-means
-
A. Jain, "Data clustering: 50 years beyond k-means," Pattern Recognit. Lett., vol. 31, no. 8, pp. 651-666, 2010.
-
(2010)
Pattern Recognit. Lett.
, vol.31
, Issue.8
, pp. 651-666
-
-
Jain, A.1
-
4
-
-
34548025132
-
A survey of kernel and spectral methods for clustering
-
M. Filippone, F. Camastra, F. Masulli, and S. Rovetta, "A survey of kernel and spectral methods for clustering," Pattern Recognit., vol. 41, no. 1, pp. 176-190, 2008.
-
(2008)
Pattern Recognit.
, vol.41
, Issue.1
, pp. 176-190
-
-
Filippone, M.1
Camastra, F.2
Masulli, F.3
Rovetta, S.4
-
5
-
-
16444383160
-
Survey of clustering algorithms
-
May
-
R. Xu and D. Wunsch, "Survey of clustering algorithms," IEEE Trans. Neural Netw., vol. 16, no. 3, pp. 645-678, May 2005.
-
(2005)
IEEE Trans. Neural Netw.
, vol.16
, Issue.3
, pp. 645-678
-
-
Xu, R.1
Wunsch, D.2
-
6
-
-
0003430544
-
-
New York, NY, USA: Wiley-Interscience
-
L.Kaufman and P. J. Rousseeuw, Finding Groups in Data: An Introduction to Cluster Analysis, vol. 344. New York, NY, USA: Wiley-Interscience, 2009.
-
(2009)
Finding Groups in Data: An Introduction to Cluster Analysis
, vol.344
-
-
Kaufman, L.1
Rousseeuw, P.J.2
-
7
-
-
0003136237
-
Efficient and effective clusteringmethods for spatial data mining
-
(ser. VLDB'94). San Francisco, CA, USA: Morgan Kaufmann. [Online]. Available:
-
R. T.Ng and J. Han. (1994). "Efficient and effective clusteringmethods for spatial data mining," in Proc. 20th Int. Conf. Very Large Data Bases (ser. VLDB'94). San Francisco, CA, USA: Morgan Kaufmann, pp. 144-155. [Online]. Available: http://dl.acm.org/citation.cfm?id=645920.672827
-
(1994)
Proc. 20th Int. Conf. Very Large Data Bases
, pp. 144-155
-
-
Ng, R.T.1
Han, J.2
-
8
-
-
0030157145
-
Birch: An efficient data clustering method for very large databases
-
T. Livny, "Birch: An efficient data clustering method for very large databases," in Proc. ACM Int. Conf. Special Interest Group Manag. Data, 1996, vol. 1, pp. 103-114.
-
(1996)
Proc. ACM Int. Conf. Special Interest Group Manag. Data
, vol.1
, pp. 103-114
-
-
Livny, T.1
-
9
-
-
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 Special Interest Group Manag. Data Record, vol. 27, no. 2, 1998, pp. 73-84.
-
(1998)
ACM Special Interest Group Manag. Data Record
, vol.27
, Issue.2
, pp. 73-84
-
-
Guha, S.1
Rastogi, R.2
Shim, K.3
-
10
-
-
0038633423
-
Clustering data streams: Theory and practice
-
May/Jun
-
S. Guha, A. Meyerson, N. Mishra, R. Motwani, and L. O'Callaghan, "Clustering data streams: Theory and practice," IEEE Trans. Knowl. Data Eng., vol. 15, no. 3, pp. 515-528, May/Jun. 2003.
-
(2003)
IEEE Trans. Knowl. Data Eng.
, vol.15
, Issue.3
, pp. 515-528
-
-
Guha, S.1
Meyerson, A.2
Mishra, N.3
Motwani, R.4
O'callaghan, L.5
-
11
-
-
68949146876
-
Incremental spectral clustering by efficiently updating the eigen-system
-
H. Ning, W. Xu, Y. Chi, Y. Gong, and T. Huang, "Incremental spectral clustering by efficiently updating the eigen-system," Pattern Recognit., vol. 43, no. 1, pp. 113-127, 2010.
-
(2010)
Pattern Recognit.
, vol.43
, Issue.1
, pp. 113-127
-
-
Ning, H.1
Xu, W.2
Chi, Y.3
Gong, Y.4
Huang, T.5
-
12
-
-
80052679753
-
Approximate kernel k-means: Solution to large scale kernel clustering
-
R. Chitta, R. Jin, T. Havens, and A. Jain, "Approximate kernel k-means: Solution to large scale kernel clustering," in Proc. ACM Special Interest Group Knowl. Discovery Data Mining, 2011, pp. 551-556.
-
(2011)
Proc. ACM Special Interest Group Knowl. Discovery Data Mining
, pp. 551-556
-
-
Chitta, R.1
Jin, R.2
Havens, T.3
Jain, A.4
-
13
-
-
84874095062
-
Efficient kernel clustering using random fourier features
-
R. Chitta, R. Jin, and A. K. Jain, "Efficient kernel clustering using random fourier features," in Proc. IEEE 12th Int. Conf. Data Mining, 2012, pp. 161-170.
-
(2012)
Proc. IEEE 12th Int. Conf. Data Mining
, pp. 161-170
-
-
Chitta, R.1
Jin, R.2
Jain, A.K.3
-
14
-
-
80053643343
-
FRBC: A fuzzy rule-based clustering algorithm
-
Oct
-
E. G. Mansoori, "FRBC: A fuzzy rule-based clustering algorithm," IEEE Trans. Fuzzy Syst., vol. 19, no. 5, pp. 960-971, Oct. 2011.
-
(2011)
IEEE Trans. Fuzzy Syst.
, vol.19
, Issue.5
, pp. 960-971
-
-
Mansoori, E.G.1
-
15
-
-
82455221063
-
Supervised hierarchical clustering in fuzzy model identification
-
Dec
-
B. Hartmann, O. Banfer, O. Nelles, A. Sodja, L. Teslic, and I. Skrjanc, "Supervised hierarchical clustering in fuzzy model identification," IEEE Trans. Fuzzy Syst., vol. 19, no. 6, pp. 1163-1176, Dec. 2011.
-
(2011)
IEEE Trans. Fuzzy Syst.
, vol.19
, Issue.6
, pp. 1163-1176
-
-
Hartmann, B.1
Banfer, O.2
Nelles, O.3
Sodja, A.4
Teslic, L.5
Skrjanc, I.6
-
16
-
-
84863157412
-
Multiple kernel fuzzy clustering
-
Apr
-
H.-C. Huang, Y.-Y. Chuang, and C.-S. Chen, "Multiple kernel fuzzy clustering," IEEE Trans. Fuzzy Syst., vol. 20, no. 1, pp. 120-134, Apr. 2012.
-
(2012)
IEEE Trans. Fuzzy Syst.
, vol.20
, Issue.1
, pp. 120-134
-
-
Huang, H.-C.1
Chuang, Y.-Y.2
Chen, C.-S.3
-
17
-
-
84859698282
-
A fuzzy approach for multitype relational data clustering
-
Jun
-
J.-P. Mei and L. Chen, "A fuzzy approach for multitype relational data clustering," IEEE Trans. Fuzzy Syst., vol. 20, no. 2, pp. 358-371, Jun. 2012.
-
(2012)
IEEE Trans. Fuzzy Syst.
, vol.20
, Issue.2
, pp. 358-371
-
-
Mei, J.-P.1
Chen, L.2
-
18
-
-
84873293546
-
Collaborative fuzzy clustering algorithms: Some refinements and design guidelines
-
L. F. Coletta, L. Vendramin, E. R. Hruschka, R. J. Campello, and W. Pedrycz, "Collaborative fuzzy clustering algorithms: Some refinements and design guidelines," IEEE Trans. Fuzzy Syst., vol. 20, no. 3, pp. 444-462, 2012.
-
(2012)
IEEE Trans. Fuzzy Syst.
, vol.20
, Issue.3
, pp. 444-462
-
-
Coletta, L.F.1
Vendramin, L.2
Hruschka, E.R.3
Campello, R.J.4
Pedrycz, W.5
-
19
-
-
54349092861
-
A fuzzy clustering approach toward hidden Markov random field models for enhanced spatially constrained image segmentation
-
Oct
-
S. P. Chatzis and T. A. Varvarigou, "A fuzzy clustering approach toward hidden Markov random field models for enhanced spatially constrained image segmentation," IEEE Trans. Fuzzy Syst., vol. 16, no. 5, pp. 1351-1361, Oct. 2008.
-
(2008)
IEEE Trans. Fuzzy Syst.
, vol.16
, Issue.5
, pp. 1351-1361
-
-
Chatzis, S.P.1
Varvarigou, T.A.2
-
20
-
-
67149143365
-
Factor analysis latent subspace modeling and robust fuzzy clustering using formula formulatype
-
Jun
-
S. Chatzis and T. Varvarigou, "Factor analysis latent subspace modeling and robust fuzzy clustering using formula formulatype," IEEE Trans. Fuzzy Syst., vol. 17, no. 3, pp. 505-517, Jun. 2009.
-
(2009)
IEEE Trans. Fuzzy Syst.
, vol.17
, Issue.3
, pp. 505-517
-
-
Chatzis, S.1
Varvarigou, T.2
-
21
-
-
77951276538
-
Arobust fuzzy local information c-means clustering algorithm
-
May
-
S. Krinidis andV.Chatzis, "Arobust fuzzy local information c-means clustering algorithm," IEEE Trans. Image Process., vol. 19, no. 5, pp. 1328-1337, May 2010.
-
(2010)
IEEE Trans. Image Process.
, vol.19
, Issue.5
, pp. 1328-1337
-
-
Krinidis, S.1
Chatzis, V.2
-
22
-
-
84878732762
-
A mutually recurrent interval type-2 fuzzy neural network (MRIT2NFS) with self-evolving structure and parameters
-
Jun
-
Y.-Y. Lin, J.-Y. Chang, N. R. Pal, and C.-T. Lin, "A mutually recurrent interval type-2 fuzzy neural network (MRIT2NFS) with self-evolving structure and parameters," IEEE Trans. Fuzzy Syst., vol. 21, no. 3, pp. 492-509, Jun. 2013.
-
(2013)
IEEE Trans. Fuzzy Syst.
, vol.21
, Issue.3
, pp. 492-509
-
-
Lin, Y.-Y.1
Chang, J.-Y.2
Pal, N.R.3
Lin, C.-T.4
-
23
-
-
84881340565
-
Comparing fuzzy, probabilistic and possibilistic partitions using the earth mover's distance
-
Aug
-
D. Anderson, A. Zare, and S. Price, "Comparing fuzzy, probabilistic and possibilistic partitions using the earth mover's distance," IEEE Trans. Fuzzy Syst., vol. 21, no. 4, pp. 766-775, Aug. 2013.
-
(2013)
IEEE Trans. Fuzzy Syst.
, vol.21
, Issue.4
, pp. 766-775
-
-
Anderson, D.1
Zare, A.2
Price, S.3
-
24
-
-
84857336717
-
Efficient document clustering via online nonnegative matrix factorizations
-
presented at Mesa, AZ, USA
-
F. Wang, C. Tan, A. C. König, and P. Li, "Efficient document clustering via online nonnegative matrix factorizations," presented at the 11th SIAM Int. Conf. Data Min. Soc. Ind. Appl. Math., Mesa, AZ, USA, 2011.
-
(2011)
The 11th SIAM Int. Conf. Data Min. Soc. Ind. Appl. Math.
-
-
Wang, F.1
Tan, C.2
König, A.C.3
Li, P.4
-
26
-
-
50249122095
-
Single pass fuzzy c means
-
P. Hore, L. Hall, and D. Goldgof, "Single pass fuzzy c means," in Proc. IEEE Int. Fuzzy Syst. Conf., 2007, pp. 1-7.
-
(2007)
Proc. IEEE Int. Fuzzy Syst. Conf.
, pp. 1-7
-
-
Hore, P.1
Hall, L.2
Goldgof, D.3
-
27
-
-
51149106562
-
Online fuzzy c means
-
P. Hore, L. Hall, D. Goldgof, and W. Cheng, "Online fuzzy c means," in Proc. IEEE Annu. Meet. North Amer. Fuzzy Inf. Process. Soc., 2008, pp. 1-5.
-
(2008)
Proc. IEEE Annu. Meet. North Amer. Fuzzy Inf. Process. Soc.
, pp. 1-5
-
-
Hore, P.1
Hall, L.2
Goldgof, D.3
Cheng, W.4
-
28
-
-
58149263279
-
A scalable framework for segmenting magnetic resonance images
-
P. Hore, L. Hall, D. Goldgof, Y. Gu, A. Maudsley, and A. Darkazanli, "A scalable framework for segmenting magnetic resonance images," J. Signal Process. Syst., vol. 54, no. 1, pp. 183-203, 2009.
-
(2009)
J. Signal Process. Syst.
, vol.54
, Issue.1
, pp. 183-203
-
-
Hore, P.1
Hall, L.2
Goldgof, D.3
Gu, Y.4
Maudsley, A.5
Darkazanli, A.6
-
29
-
-
84867612677
-
Fuzzy c-means algorithms for very large data
-
Dec
-
T. Havens, J. Bezdek, C. Leckie, L. Hall, and M. Palaniswami, "Fuzzy c-means algorithms for very large data," IEEE Trans. Fuzzy Syst., vol. 20, no. 6, pp. 1130-1146, Dec. 2012.
-
(2012)
IEEE Trans. Fuzzy Syst.
, vol.20
, Issue.6
, pp. 1130-1146
-
-
Havens, T.1
Bezdek, J.2
Leckie, C.3
Hall, L.4
Palaniswami, M.5
-
31
-
-
0035416012
-
Low-complexity fuzzy relational clustering algorithms forweb mining
-
Aug
-
R. Krishnapuram, A. Joshi, O. Nasraoui, and L. Yi, "Low-complexity fuzzy relational clustering algorithms forweb mining," IEEE Trans. Fuzzy Syst., vol. 9, no. 4, pp. 595-607, Aug. 2001.
-
(2001)
IEEE Trans. Fuzzy Syst.
, vol.9
, Issue.4
, pp. 595-607
-
-
Krishnapuram, R.1
Joshi, A.2
Nasraoui, O.3
Yi, L.4
-
32
-
-
75749127352
-
Fuzzy clusteringwith weighted medoids for relational data
-
J. Mei and L. Chen, "Fuzzy clusteringwith weighted medoids for relational data," Pattern Recognit., vol. 43, no. 5, pp. 1964-1974, 2010.
-
(2010)
Pattern Recognit.
, vol.43
, Issue.5
, pp. 1964-1974
-
-
Mei, J.1
Chen, L.2
-
33
-
-
33746922014
-
Approximate clustering in very large relational data
-
J. Bezdek, R. Hathaway, J. Huband, C. Leckie, and R. Kotagiri, "Approximate clustering in very large relational data," Int. J. Intell. Syst., vol. 21, no. 8, pp. 817-841, 2006.
-
(2006)
Int. J. Intell. Syst.
, vol.21
, Issue.8
, pp. 817-841
-
-
Bezdek, J.1
Hathaway, R.2
Huband, J.3
Leckie, C.4
Kotagiri, R.5
-
34
-
-
79958743806
-
Automatic analysis of malware behavior using machine learning
-
K. Rieck, P. Trinius, C. Willems, and T. Holz, "Automatic analysis of malware behavior using machine learning," J. Comput. Security, vol. 19, no. 4, pp. 639-668, 2011.
-
(2011)
J. Comput. Security
, vol.19
, Issue.4
, pp. 639-668
-
-
Rieck, K.1
Trinius, P.2
Willems, C.3
Holz, T.4
-
36
-
-
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., vol. 3, pp. 583-617, 2003.
-
(2003)
J. Mach. Learn. Res.
, vol.3
, pp. 583-617
-
-
Strehl, A.1
Ghosh, J.2
|