-
1
-
-
0347172110
-
OPTICS: Ordering Points to Identify the Clustering Structure
-
Ankerst, M., Breunig, M., Kriegel, H. P., and Sander, J. (1999). OPTICS: Ordering Points To Identify the Clustering Structure. Proc. 1999 ACM-SIGMOD Conf. on Management of Data (SIGMOD'99), pp. 49-60.
-
(1999)
Proc. 1999 ACM-SIGMOD Conf. on Management of Data (SIGMOD'99)
, pp. 49-60
-
-
Ankerst, M.1
Breunig, M.2
Kriegel, H.P.3
Sander, J.4
-
2
-
-
84958956637
-
Partitioning approaches to clustering in graphs
-
LNCS
-
Batagelj, V., Mrvar, A., and Zaversnik, M. (2000). Partitioning approaches to clustering in graphs, Proc. Graph Drawing'1999, LNCS, pp. 90-97.
-
(2000)
Proc. Graph Drawing'1999
, pp. 90-97
-
-
Batagelj, V.1
Mrvar, A.2
Zaversnik, M.3
-
3
-
-
26944461753
-
Finding clusters of different sizes, shapes, and densities in noisy, high dimensional data
-
Ertoz, L., Steinbach, M., and Kumar, V. (2003), Finding clusters of different sizes, shapes, and densities in noisy, high dimensional data, In Proc. of SIAM DM'03.
-
(2003)
Proc. of SIAM DM'03
-
-
Ertoz, L.1
Steinbach, M.2
Kumar, V.3
-
4
-
-
85170282443
-
A density-based algorithm for discovering clusters in large spatial databases with noise
-
AAAI Press
-
Ester, M., Kriegel, H. P., Sander, J., and Xu, X. (1996). A density-based algorithm for discovering clusters in large spatial databases with noise, Proc. 2nd Int. Conf. on Knowledge Discovery and Data Mining (KDD-96), AAAI Press, pp. 226-231.
-
(1996)
Proc. 2nd Int. Conf. on Knowledge Discovery and Data Mining (KDD-96)
, pp. 226-231
-
-
Ester, M.1
Kriegel, H.P.2
Sander, J.3
Xu, X.4
-
5
-
-
0010415411
-
Spatial clustering methods in data mining: A survey
-
H. Miller and J. Han (eds.), Taylor and Francis
-
Han, J., Kamber, M., and Tung, A. K. H. (2001). Spatial clustering methods in data mining: A survey, H. Miller and J. Han (eds.), Geographic Data Mining and Knowledge Discovery, Taylor and Francis.
-
(2001)
Geographic Data Mining and Knowledge Discovery
-
-
Han, J.1
Kamber, M.2
Tung, A.K.H.3
-
7
-
-
0004161991
-
-
Prentice-Hall advanced reference series. Prentice-Hall, Inc., Upper Saddle River, NJ
-
Jain, A. K., and Dubes, R. C. (1988). Algorithms for Clustering Data, Prentice-Hall advanced reference series. Prentice-Hall, Inc., Upper Saddle River, NJ.
-
(1988)
Algorithms for Clustering Data
-
-
Jain, A.K.1
Dubes, R.C.2
-
8
-
-
0032686723
-
CHAMELEON, a hierarchical clustering algorithm using dynamic modeling
-
Karypis, G., Han, E., and Kumar, V. (1999). CHAMELEON, A hierarchical clustering algorithm using dynamic modeling, IEEE Computer, Vol.32, pp. 68-75.
-
(1999)
IEEE Computer
, vol.32
, pp. 68-75
-
-
Karypis, G.1
Han, E.2
Kumar, V.3
-
10
-
-
3142740971
-
FACADE: A Fast and Effective Approach to the Discovery of Dense Clusters in Noisy Spatial Data
-
ACM Press. (Demo Abstract)
-
Qian, Y., Zhang, G., and Zhang, K. (2004) FACADE: A Fast and Effective Approach to the Discovery of Dense Clusters in Noisy Spatial Data, In Proc. ACM SIGMOD 2004 Conference, Paris, France, 13-18 June 2004, ACM Press. (Demo Abstract)
-
(2004)
Proc. ACM SIGMOD 2004 Conference, Paris, France, 13-18 June 2004
-
-
Qian, Y.1
Zhang, G.2
Zhang, K.3
-
12
-
-
0000488788
-
Network structure and minimum degree
-
Seidman, S. B. (1983). Network structure and minimum degree. Social Networks, 5, pp. 269-287.
-
(1983)
Social Networks
, vol.5
, pp. 269-287
-
-
Seidman, S.B.1
-
13
-
-
77953995997
-
-
http://www.cs.umn.edu/~ertoz/snn/
-
-
-
|