-
1
-
-
0347718066
-
Fast algorithms for projected clustering
-
In: Delis A, Faloutsos C, Ghandeharizadeh S (eds) Philadelphia
-
Aggarwal C, Procopiuc C, Wolf J, Yu P, and Park J (1999) Fast algorithms for projected clustering. In: Delis A, Faloutsos C, Ghandeharizadeh S (eds) Proceedings of the ACM SIGMOD international conference on management of data, Philadelphia, pp 61-72
-
(1999)
Proceedings of the ACM SIGMOD International Conference on Management of Data
, pp. 61-72
-
-
Aggarwal, C.1
Procopiuc, C.2
Wolf, J.3
Yu, P.4
Park, J.5
-
2
-
-
0039253822
-
Finding generalized projected clusters in high dimensional spaces
-
In: Chen W, Naughton J, Bernstein P (eds) Dallas
-
Aggarwal C, Yu P (2000) Finding generalized projected clusters in high dimensional spaces. In: Chen W, Naughton J, Bernstein P (eds) Proceedings of the ACM SIGMOD international conference on management of data, Dallas, pp 70-81
-
(2000)
Proceedings of the ACM SIGMOD International Conference on Management of Data
, pp. 70-81
-
-
Aggarwal, C.1
Yu, P.2
-
3
-
-
0032090765
-
Automatic subspace clustering of high dimensional data for data mining applications
-
In: Haas L, Tiwary A (eds) Seattle
-
Agrawal R, Gehrke J, Gunopulos D, Raghavan P (1998) Automatic subspace clustering of high dimensional data for data mining applications. In: Haas L, Tiwary A (eds) Proceedings of the ACM SIGMOD international conference on management of data, Seattle, pp 94-105
-
(1998)
Proceedings of the ACM SIGMOD International Conference on Management of Data
, pp. 94-105
-
-
Agrawal, R.1
Gehrke, J.2
Gunopulos, D.3
Raghavan, P.4
-
4
-
-
0001882616
-
Fast algorithms for mining association rules
-
In: Bocca J, Jarke M, Zaniolo C (eds) Santiago de Chile, Chile
-
Agrawal R, Srikan R (1994) Fast algorithms for mining association rules. In: Bocca J, Jarke M, Zaniolo C (eds) Proceedings of the international conference on very large data bases VLDB, Santiago de Chile, Chile, pp 487-499
-
(1994)
Proceedings of the International Conference on Very Large Data Bases VLDB
, pp. 487-499
-
-
Agrawal, R.1
Srikan, R.2
-
5
-
-
0033536012
-
Broad patterns of gene expression revealed by clustering of tumor and normal colon tissues probed by oligonucleotide arrays
-
Alon U, Barkai N, Notterman D, Gish K, Ybarra S, Mack D and Levine A (1999). Broad patterns of gene expression revealed by clustering of tumor and normal colon tissues probed by oligonucleotide arrays. Proc Natl Acad Sci USA 96(12):6745-6750
-
(1999)
Proc Natl Acad Sci USA
, vol.96
, Issue.12
, pp. 6745-6750
-
-
Alon, U.1
Barkai, N.2
Notterman, D.3
Gish, K.4
Ybarra, S.5
Mack, D.6
Levine, A.7
-
6
-
-
35048857464
-
LIMBO: Scalable clustering of categorical data
-
In: Heraklion, Greece
-
Andritsos P, Tsaparas P, Miller J, Sevcik K (2004) LIMBO: Scalable clustering of categorical data. In Proceedings of international conference on extending database technology EDBT, Heraklion, Greece, pp 123-146
-
(2004)
Proceedings of International Conference on Extending Database Technology EDBT
, pp. 123-146
-
-
Andritsos, P.1
Tsaparas, P.2
Miller, J.3
Sevcik, K.4
-
7
-
-
84947205653
-
When is nearest neighbor meaningful?
-
Springer, Berlin
-
Beyer K, Goldstein J, Ramakrishnan R, Shaft U (1999) When is nearest neighbor meaningful? Lecture Notes in Computer Science, vol. 1540. Springer, Berlin, pp 217-235
-
(1999)
Lecture Notes in Computer Science
, vol.1540
, pp. 217-235
-
-
Beyer, K.1
Goldstein, J.2
Ramakrishnan, R.3
Shaft, U.4
-
8
-
-
0002629270
-
Maximum likelihood for incomplete data via the EM algorithm
-
Dempster A, Laird N and Rubin D (1977). Maximum likelihood for incomplete data via the EM algorithm. J Roy Stat Soc 39:1-38
-
(1977)
J Roy Stat Soc
, vol.39
, pp. 1-38
-
-
Dempster, A.1
Laird, N.2
Rubin, D.3
-
9
-
-
26844445118
-
Subspace clustering for high dimensional categorical data
-
Gan G and Wu J (2004). Subspace clustering for high dimensional categorical data. ACM SIGKDD Explor Newslett 6(2):87-94
-
(2004)
ACM SIGKDD Explor Newslett
, vol.6
, Issue.2
, pp. 87-94
-
-
Gan, G.1
Wu, J.2
-
11
-
-
85132256511
-
A general approach to clustering in large databases with noise
-
Hinneburg A and Keim D (2003). A general approach to clustering in large databases with noise. Knowl Inf Syst 5(4):387-415
-
(2003)
Knowl Inf Syst
, vol.5
, Issue.4
, pp. 387-415
-
-
Hinneburg, A.1
Keim, D.2
-
12
-
-
2942588997
-
Density-connected subspace clustering for high-dimensional data
-
In: Berry M, Dayal U, Kamath C, Skilicorn D (eds) Lake Buena Vista, April 2004
-
Kailing K, Kriegel H, Kröger P (2004) Density-connected subspace clustering for high-dimensional data. In: Berry M, Dayal U, Kamath C, Skilicorn D (eds) Proceedings of the SIAM international conference on data mining, Lake Buena Vista, April 2004, pp 1-11
-
(2004)
Proceedings of the SIAM International Conference on Data Mining
, pp. 1-11
-
-
Kailing, K.1
Kriegel, H.2
Kröger, P.3
-
13
-
-
34547251368
-
A generic framework for efficient subspace clustering of high-dimensional data
-
In: Houston
-
Kriegel H, Kröger P, Renz M, Wurst S (2005) A generic framework for efficient subspace clustering of high-dimensional data. In: Proceedings of the IEEE ICDM international conference on data mining, Houston, pp 250-257
-
(2005)
Proceedings of the IEEE ICDM International Conference on Data Mining
, pp. 250-257
-
-
Kriegel, H.1
Kröger, P.2
Renz, M.3
Wurst, S.4
-
16
-
-
14644424597
-
Projective clustering by histograms
-
Ng K, Fu A and Wong C (2005). Projective clustering by histograms. IEEE Trans Knowl Data Eng 17(3):369-383
-
(2005)
IEEE Trans Knowl Data Eng
, vol.17
, Issue.3
, pp. 369-383
-
-
Ng, K.1
Fu, A.2
Wong, C.3
-
17
-
-
17044376078
-
Subspace clustering for high dimensional data: A review
-
Parsons L, Haque E and Liu H (2004). Subspace clustering for high dimensional data: A review. ACM SIGKDD Explor Newslett 6(1):90-105
-
(2004)
ACM SIGKDD Explor Newslett
, vol.6
, Issue.1
, pp. 90-105
-
-
Parsons, L.1
Haque, E.2
Liu, H.3
-
18
-
-
0036361164
-
A Monte Carlo algorithm for fast projective clustering
-
In: Franklin M, Moon B, Ailamaki A (eds) Madison
-
Procopiuc C, Jones M, Agarwal P, Murali T (2002) A Monte Carlo algorithm for fast projective clustering. In: Franklin M, Moon B, Ailamaki A (eds) Proceedings of the ACM SIGMOD international conference on management of data, Madison, pp 418-427
-
(2002)
Proceedings of the ACM SIGMOD International Conference on Management of Data
, pp. 418-427
-
-
Procopiuc, C.1
Jones, M.2
Agarwal, P.3
Murali, T.4
-
19
-
-
84950439147
-
Unmasking multivariate outliers and leverage points
-
Rousseeuw P and Van Zomeren B (1990). Unmasking multivariate outliers and leverage points. J Am Stat Assoc 85(411):633-651
-
(1990)
J Am Stat Assoc
, vol.85
, Issue.411
, pp. 633-651
-
-
Rousseeuw, P.1
Van Zomeren, B.2
-
21
-
-
33845240405
-
Capabilities of outlier detection schemes in large datasets, framework and methodologies
-
Tang J, Chen J, Fu A and Cheung W (2007). Capabilities of outlier detection schemes in large datasets, framework and methodologies. Knowl Inf Syst 11(1):45-84
-
(2007)
Knowl Inf Syst
, vol.11
, Issue.1
, pp. 45-84
-
-
Tang, J.1
Chen, J.2
Fu, A.3
Cheung, W.4
-
22
-
-
32544438259
-
On efficiently summarizing categorical databases
-
Wang J and Karypis G (2006). On efficiently summarizing categorical databases. Knowl Inf Syst 9(1):19-37
-
(2006)
Knowl Inf Syst
, vol.9
, Issue.1
, pp. 19-37
-
-
Wang, J.1
Karypis, G.2
-
23
-
-
13844297591
-
HARP: A practical projected clustering algorithm
-
Yip K, Cheung D and Ng M (2004). HARP: A practical projected clustering algorithm. IEEE Trans Knowl Data Eng 16(11):1387-1397
-
(2004)
IEEE Trans Knowl Data Eng
, vol.16
, Issue.11
, pp. 1387-1397
-
-
Yip, K.1
Cheung, D.2
Ng, M.3
-
25
-
-
14644404956
-
Frequent-pattern based iterative projected clustering
-
Yiu M and Mamoulis N (2005). Frequent-pattern based iterative projected clustering. IEEE Trans Knowl Data Eng 17(2):176-189
-
(2005)
IEEE Trans Knowl Data Eng
, vol.17
, Issue.2
, pp. 176-189
-
-
Yiu, M.1
Mamoulis, N.2
-
26
-
-
32344441016
-
CLICKS: An effective algorithm for mining subspace clusters in categorical datasets
-
In: Grossman R, Bayardo R, Bennett K (eds) Chicago
-
Zaki M, Peters M, Assent I, Seidl T (2005) CLICKS: An effective algorithm for mining subspace clusters in categorical datasets. In: Grossman R, Bayardo R, Bennett K (eds) Proceedings of ACM SIGKDD international conference on knowledge discovery and data mining, Chicago, pp 733-742
-
(2005)
Proceedings of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
, pp. 733-742
-
-
Zaki, M.1
Peters, M.2
Assent, I.3
Seidl, T.4
|