Detection and visualization of subspace cluster hierarchies

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4443 LNCS, Issue , 2007, Pages 152-163

  Achtelt, Elke ^a   Böhm, Christian ^a   Kriegel, Hans Peter ^a   Kroger, Peer ^a   Müller Gorman, Ina ^a   Zimek, Arthur ^a  

^a UNIVERSITY OF MUNICH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CLUSTER ANALYSIS; EMBEDDED SYSTEMS; GRAPH THEORY; MATHEMATICAL MODELS;

SUBSPACE CLUSTERING; SUBSPACE CLUSTERS;

HIERARCHICAL SYSTEMS;

EID: 38049175016     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: None     Document Type: Conference Paper

References (15)

1. Agrawal, R., Gehrke, J., Gunopulos, D., Raghavan, P.: Automatic subspace clustering of high dimensional data for data mining applications. In: Proc. SIGMOD. (1998)
2. Cheng, C.H., Fu, A.W.C., Zhang, Y.: Entropy-based subspace clustering for mining numerical data. In: Proc. KDD. (1999) 84-93
3. Railing, K., Kriegel, H.P., Kroger, P.: Density-connected subspace clustering for high-dimensional data. In: Proc. SDM. (2004)
4. Kriegel, H.P., Kroger, P., Renz, M., Wurst, S.: A generic framework for efficient subspace clustering of high-dimensional data. In: Proc. ICDM. (2005)
5. Aggarwal, C.C., Procopiuc, C.M., Wolf, J.L., Yu, P.S., Park, J.S.: Fast algorithms for projected clustering. In: Proc. SIGMOD. (1999)
6. Procopiuc, C.M., Jones, M., Agarwal, PK., Murali, T.M.: A Monte Carlo algorithm for fast projective clustering. In: Proc. SIGMOD. (2002)
7. Böhm, C., Railing, K., Kriegel, H.P., Kroger, P.: Density connected clustering with local subspace preferences. In: Proc. ICDM. (2004)
8. Achtert, E., Böhm, C., Kriegel, H.P., Kroger, P., Midler-Gorman, I., Zimek, A.: Finding hierarchies of subspace clusters. In: Proc. PKDD. (2006) To appear.
9. Ankerst, M., Breunig, M.M., Kriegel, H.P., Sander, J.: OPTICS: Ordering points to identify the clustering structure. In: Proc. SIGMOD. (1999)
10. Yang, J., Wang, W., Wang, H., Yu, P.S.: Delta-Clusters: Capturing subspace correlation in a large data set. In: Proc. ICDE. (2002)
11. Wang, H., Wang, W., Yang, J., Yu, P.S.: Clustering by pattern similarity in large data sets. In: Proc. SIGMOD. (2002)
12. Böhm, C., Railing, K., Kroger, P., Zimek, A.: Computing clusters of correlation connected objects. In: Proc. SIGMOD. (2004)
13. Aggarwal, C.C., Yu, P.S.: Finding generalized projected clusters in high dimensional space. In: Proc. SIGMOD. (2000)
14. Agrawal, R., Srikant, R.: Fast algorithms for mining association rules. In: Proc. SIGMOD. (1994)
15. Spellman, P.T., Sherlock, C., Zhang, M.Q., Iyer, V.R., Anders, K., Eisen, M.B., Brown, P.O., Botstein, D., Futcher, B.: "Comprehensive Identification of Cell Cycle-Regulated Genes of the Yeast Saccharomyces Cerevisiae by Microarray Hybridization.". Molecular Biolology of the Cell 9 (1998) 3273-3297