-
1
-
-
34447330447
-
A k-mean clustering algorithm for mixed numeric and categorical data
-
A. Ahmed and D. Lipika. A k-mean clustering algorithm for mixed numeric and categorical data. Data and Knowledge Engineering, 63(2):503-527, 2007.
-
(2007)
Data and Knowledge Engineering
, vol.63
, Issue.2
, pp. 503-527
-
-
Ahmed, A.1
Lipika, D.2
-
2
-
-
34447501949
-
Hierarchical clustering of mixed data based on distance hierarchy
-
H. Chung-Chian, C. Chin-Long, and S. Yu-Wei. Hierarchical clustering of mixed data based on distance hierarchy. Information Sciences, 177(20):4474-4492, 2007.
-
(2007)
Information Sciences
, vol.177
, Issue.20
, pp. 4474-4492
-
-
Chung-Chian, H.1
Chin-Long, C.2
Yu-Wei, S.3
-
3
-
-
85170282443
-
A densitybased algorithm for discovering clusters in large spatial databases with noise
-
Portland, Oregon, August
-
M. Ester, H.-P. Kriegel, J. Sander, and X. Xu. A densitybased algorithm for discovering clusters in large spatial databases with noise. In Proc. of 2nd Int. Conf. on Knowledge Discovery and Data Mining (KDD), pages 226-231, Portland, Oregon, August 1996.
-
(1996)
Proc. of 2nd Int. Conf. on Knowledge Discovery and Data Mining (KDD)
, pp. 226-231
-
-
Ester, M.1
Kriegel, H.-P.2
Sander, J.3
Xu, X.4
-
4
-
-
0032091595
-
CURE: An efficient clustering algorithm for large databases
-
Seatle, USA, June
-
S. Guha, R. Rastogi, and K. Shim. CURE: An efficient clustering algorithm for large databases. In Proc. of ACM SIGMOD Int. Conf. on Management of Data, pages 73-84, Seatle, USA, June 1998.
-
(1998)
Proc. of ACM SIGMOD Int. Conf. on Management of Data
, pp. 73-84
-
-
Guha, S.1
Rastogi, R.2
Shim, K.3
-
5
-
-
0035676057
-
On clustering validation techniques
-
M. Halkidi, Y. Batistakis, and M. Vazirgiannis. On clustering validation techniques. Journal of Intelligent Information Systems, 17(2):107-145, 2001.
-
(2001)
Journal of Intelligent Information Systems
, vol.17
, Issue.2
, pp. 107-145
-
-
Halkidi, M.1
Batistakis, Y.2
Vazirgiannis, M.3
-
6
-
-
27844433509
-
Scalable algorithms for clustering mixed type attributes in large datasets
-
Z. He, X. Xu, and S. Deng. Scalable algorithms for clustering mixed type attributes in large datasets. International Journal of Intelligent Systems, 20(10):1077-1089, 2005.
-
(2005)
International Journal of Intelligent Systems
, vol.20
, Issue.10
, pp. 1077-1089
-
-
He, Z.1
Xu, X.2
Deng, S.3
-
8
-
-
27144536001
-
Extensions to the k-means algorithm for clustering large data sets with categorical values
-
Z. Huang. Extensions to the k-means algorithm for clustering large data sets with categorical values. Data Mining and Knowledge Discovery, 2(3):283-304, 1998.
-
(1998)
Data Mining and Knowledge Discovery
, vol.2
, Issue.3
, pp. 283-304
-
-
Huang, Z.1
-
9
-
-
84893405732
-
Data clustering: A review
-
A.-K. Jain, M. Murty, and P.-J. Flynn. Data clustering: A review. ACM Computing Surveys, 31(3):264-323, 1999.
-
(1999)
ACM Computing Surveys
, vol.31
, Issue.3
, pp. 264-323
-
-
Jain, A.-K.1
Murty, M.2
Flynn, P.-J.3
-
12
-
-
62449114337
-
-
J. Mcqueen. some methods for classification and analysis of multivariate observations. In 5th Berkeley Symp. on Math. Statistics and Probability, pages 281-298, Berkley, CA: University of California Press, 1967.
-
J. Mcqueen. some methods for classification and analysis of multivariate observations. In 5th Berkeley Symp. on Math. Statistics and Probability, pages 281-298, Berkley, CA: University of California Press, 1967.
-
-
-
-
13
-
-
0003136237
-
Efficient and effective clustering methods for spatial data mining
-
Santiago, Chile, September
-
R.-T. Ng and J. Han. Efficient and effective clustering methods for spatial data mining. In 20th Int. Conf. on Very Large Data Bases (VLDB), pages 144-155, Santiago, Chile, September 1994.
-
(1994)
20th Int. Conf. on Very Large Data Bases (VLDB)
, pp. 144-155
-
-
Ng, R.-T.1
Han, J.2
-
14
-
-
0029415780
-
A conceptual version of the k-means algorithm
-
H. Ralambondrainy. A conceptual version of the k-means algorithm. Pattern Recognition Letters, 16(11):1147-1157, 1995.
-
(1995)
Pattern Recognition Letters
, vol.16
, Issue.11
, pp. 1147-1157
-
-
Ralambondrainy, H.1
-
15
-
-
0030157145
-
BIRCH: An efficient data clustering method for very large databases
-
Montreal, Canada, June
-
T. Zhang, R. Ramakrishnan, and M. Livny. BIRCH: An efficient data clustering method for very large databases. In Proc. of ACM SIGMOD Int. Conf. on Management of data, Montreal, Canada, June 1996.
-
(1996)
Proc. of ACM SIGMOD Int. Conf. on Management of data
-
-
Zhang, T.1
Ramakrishnan, R.2
Livny, M.3
|