Characterizing pattern preserving clustering

Knowledge and Information Systems

Volumn 19, Issue 3, 2009, Pages 311-336

  Xiong, Hui ^a   Steinbach, Michael ^b   Ruslim, Arifin ^b   Kumar, Vipin ^b  

^a RUTGERS UNIVERSITY   (United States)

^b University of Minnesota   (United States)

Author keywords

Hierarchical clustering; Hyperclique pattern; K means clustering; Pattern preserving clustering

Indexed keywords

ENTROPY; HIERARCHICAL CLUSTERING;

CLUSTER CENTROIDS; CLUSTERING APPROACH; CLUSTERING EVALUATION; DIFFERENT SIZES; HYPERCLIQUE PATTERN; OVERLAPPING CLUSTERS; PATTERN PRESERVING CLUSTERING; USEFUL PATTERNS;

K-MEANS CLUSTERING;

EID: 67349254647     PISSN: 02191377     EISSN: 02193116     Source Type: Journal    
DOI: 10.1007/s10115-008-0148-0     Document Type: Article

References (36)

1. Agrawal R, Imielinski T, Swami A (1993) Mining association rules between sets of items in large databases. In: Proceedings of the 1993 ACM SIGMOD international conference on management of data, pp 207-216
2. Anderberg MR (1973) Cluster analysis for applications. Academic Press, New York
3. Beil F, Ester M, Xu X (2002) Frequent term-based text clustering. In: Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining. ACM Press, New York, pp. 436-442
4. Berkhin P (2002) Survey of clustering data mining techniques. Technical report, Accrue Software, CA
5. Brecheisen S, Kriegel H-P, Pfeifle M (2006) Multi-step density-based clustering. Knowl Inf Syst 9(3):284-308
6. Fung B, Wang K, Ester M (2003) Hierarchical document clustering using frequent itemsets. In: Proceedings of the third SIAM international conference on data mining, SIAM
7. Gondek D, Hofmann T (2007) Non-redundant data clustering. Knowl Inf Syst 12(1):1-24
8. Han E-H, Boley D, Gini M, Gross R, Hastings K, Karypis G, Kumar V, Mobasher B, Moore J (1998) Webace: A web agent for document categorization and exploration. In: Proceedings of the second international conference on autonomous agents
9. Han E-HS, Karypis G, Kumar V, Mobasher B (1998) Hypergraph based clustering in high-dimensional data sets: A summary of results. Bulletin of the Technical Committee on Data Engineering 21(1)
10. Hinneburg A, Keim DA (2003) A general approach to clustering in large databases with noise. Knowl Inf Syst 5(4):387-415
11. Jain AK, Dubes RC (1988) Algorithms for clustering data. Prentice Hall Advanced Reference Series. Prentice Hall, Englewood Cliffs
12. Jain AK, Murty MN, Flynn PJ (1999) Data clustering: A review. ACM Computing Surveys (3)
13. Karypis G (2006) Cluto: Software for clustering high-dimensional datasets. http://www.cs.umn.edu/~karypis
14. Kaufman L, Rousseeuw PJ (1990) Finding groups in data: An introduction to cluster analysis. Wiley Series in Probability and Statistics, John Wiley and Sons, New York
15. Koga H, Ishibashi T, Watanabe T (2007) Fast agglomerative hierarchical clustering algorithm using locality-sensitive hashing. Knowl Inf Syst 12(1):25-53
16. Lewis D (2004) Reuters-21578 text categorization text collection 1.0. http://www.daviddlewis.com/resources/testcollections/reuters21578/
17. MacQueen J (1967) Some methods for classification and analysis of multivariate observations. In: Cam LML, Neyman J (eds) Proceedings of the fifth berkeley symposium on mathematical statistics and probability, vol I, Statistics, University of California Press
18. Madeira SC, Oliveira AL (2004) Biclustering algorithms for biological data analysis: A survey. IEEE/ACM Trans Comput Biol Bioinform 1(1):24-45
19. Omiecinski E (2003) Alternative interest measures for mining associations in databases. IEEE Trans Knowl Data Eng 15(1):57-69
20. Ozdal MM, Aykanat C (2004) Hypergraph models and algorithms for data-pattern based clustering. Data Mining Knowl Discov 9(1):29-57
21. Porter MF (1980) An algorithm for suffix stripping. In: Program 14(3):130-137
22. Rijsbergen CJV (1979) Information retrieval, 2nd edn. Butterworths, London
23. Sander J, Ester M, Kriegel H-P, Xu X (1998) Density-based clustering in spatial databases: The algorithm gdbscan and its applications. Data Mining Knowl Discov 2(2):169-194
24. Steinbach M, Karypis G, Kumar V (2000) A comparison of document clustering techniques. In: KDD workshop on text mining
25. Steinbach M, Tan P-N, Xiong H, Kumar V (2004) Generalizing the notion of support. In: KDD '04: Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining. ACM Press, New York, NY, USA, pp 689-694
26. Strehl A, Ghosh J, Mooney R (2000) Impact of similarity measures on web-page clusteWing. In: Proceedings of AAAI: workshop of artificial intelligence for web search, AAAI, pp 58-64. http://citeseer.nj.nec.com/ strehl00impact.html
27. TREC (1996) http://trec.nist.gov
28. Tung AKH, Ng RT, Lakshmanan LVS, Han J (2001) Constraint-based clustering in large databases. In: Den Bussche JV, Vianu V (eds) Database theory-ICDT 2001, 8th International Conference, pp 405-419
29. Wang K, Xu C, Liu B (1999) Clustering transactions using large items. In: Proceedings of the 1999 ACM CIKM international conference on information and knowledge management, pp 483-490
30. Xiong H, He X, Ding C, Zhang Y, Kumar V, Holbrook S (2005) Identification of functional modules in protein complexes via hyperclique pattern discovery. In: Proceedings of the pacific symposium on biocomputing
31. Xiong H, Steinbach M, Tan P-N, Kumpar V (2004) HICAP: Hierarchial Clustering with Pattern Preservation. In: Proceedings of 2004 SIAM International Conference on Data Mining (SDM), pp 279-290
32. Xiong H, Tan P, Kumar V (2003) Mining strong affinity association patterns in data sets with skewed support distribution. In: Proceedings of the third IEEE international conference on data mining (ICDM), pp 387-394
33. Xiong H, Tan P-N, Kumar V (2006) Hyperclique pattern discovery. Data Mining Knowl Discov J 13(2):219-242
34. Zhao Y, Karypis G (2002) Evaluation of hierarchical clustering algorithms for document datasets. In: Proceedings of the 2002 ACM CIKM international conference on information and knowledge management, ACM Press, New York, pp 515-524
35. Zhao Y, Karypis G (2004) Criterion functions for document clustering: experiments and analysis. Mach Learn 55(3):311-331
36. Zhong S, Ghosh J (2005) Generative model-based document clustering: A comparative study. Knowl Inf Syst 8(3):374-384