메뉴 건너뛰기




Volumn 29, Issue 9, 2008, Pages 1372-1384

A general grid-clustering approach

Author keywords

Clustering; Core grid; Grid size; Locality

Indexed keywords

CLUSTER ANALYSIS; CLUSTERING ALGORITHMS; DATA STRUCTURES; FEATURE EXTRACTION; PARAMETER ESTIMATION; USER INTERFACES;

EID: 43249118570     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2008.02.019     Document Type: Article
Times cited : (37)

References (25)
  • 1
    • 43249113450 scopus 로고    scopus 로고
    • Agrawal, R., Gehrke, J., Gunopulos, D., Raghavan, P., 1998. Automatic subspace clustering of high dimensional data. In: Proc. ACM SIGMOD Internat. Conf., Seattle, WA, pp. 73-84.
    • Agrawal, R., Gehrke, J., Gunopulos, D., Raghavan, P., 1998. Automatic subspace clustering of high dimensional data. In: Proc. ACM SIGMOD Internat. Conf., Seattle, WA, pp. 73-84.
  • 2
    • 23944436897 scopus 로고    scopus 로고
    • Automatic subspace clustering of high dimensional data
    • Agrawal R., Gehrke J., Gunopulos D., et al. Automatic subspace clustering of high dimensional data. Data Mining. Knowl. Disc. 11 1 (2005) 5-33
    • (2005) Data Mining. Knowl. Disc. , vol.11 , Issue.1 , pp. 5-33
    • Agrawal, R.1    Gehrke, J.2    Gunopulos, D.3
  • 3
    • 43249096566 scopus 로고    scopus 로고
    • AlphaMiner2.0: .
    • AlphaMiner2.0: .
  • 4
    • 84947205653 scopus 로고    scopus 로고
    • Beyer, K.S., Goldstein, J., Ramakrishnan, R., 1999. When is 'Nearest Neighbor' meaningful? In: Proc. 1st Internat. Conf. Database Theory (ICDT), pp. 217-235.
    • Beyer, K.S., Goldstein, J., Ramakrishnan, R., 1999. When is 'Nearest Neighbor' meaningful? In: Proc. 1st Internat. Conf. Database Theory (ICDT), pp. 217-235.
  • 6
  • 7
    • 0001345686 scopus 로고    scopus 로고
    • Context-sensitive learning methods for text categorization
    • Cohen W., and Singer W. Context-sensitive learning methods for text categorization. ACM. Trans. Info. Systems 17 2 (1999) 141-173
    • (1999) ACM. Trans. Info. Systems , vol.17 , Issue.2 , pp. 141-173
    • Cohen, W.1    Singer, W.2
  • 8
    • 0346216908 scopus 로고    scopus 로고
    • A new shifting grid clustering algorithm
    • Eden W., Ma M., and Tommy W.S. A new shifting grid clustering algorithm. Pattern Recognition 37 (2004) 503-514
    • (2004) Pattern Recognition , vol.37 , pp. 503-514
    • Eden, W.1    Ma, M.2    Tommy, W.S.3
  • 9
    • 0002442796 scopus 로고    scopus 로고
    • Machine learning in automated text categorization
    • Fabrizio S. Machine learning in automated text categorization. ACM Comput. Surv. 34 1 (2002) 1-47
    • (2002) ACM Comput. Surv. , vol.34 , Issue.1 , pp. 1-47
    • Fabrizio, S.1
  • 10
    • 0041471321 scopus 로고    scopus 로고
    • A new cluster isolation criterion based on dissimilarity increments
    • Fred A., and Leitao J. A new cluster isolation criterion based on dissimilarity increments. IEEE Trans. Pattern Anal. Machine Intell. 25 8 (2003) 944-952
    • (2003) IEEE Trans. Pattern Anal. Machine Intell. , vol.25 , Issue.8 , pp. 944-952
    • Fred, A.1    Leitao, J.2
  • 11
    • 84883402747 scopus 로고    scopus 로고
    • Grabusts, P., Borisov, A., 2002. Using grid-clustering methods in data classification. In: Internat. Conf. on Parallel Computing in Electrical Engineering.
    • Grabusts, P., Borisov, A., 2002. Using grid-clustering methods in data classification. In: Internat. Conf. on Parallel Computing in Electrical Engineering.
  • 12
    • 0032091595 scopus 로고    scopus 로고
    • Guha, S., Rastogi, R., Shim, K., 1998. CURE: An efficient clustering algorithm for large databases. In: Proc. ACM SIGMOD Internat. Conf. Management of Data, pp. 73-84.
    • Guha, S., Rastogi, R., Shim, K., 1998. CURE: An efficient clustering algorithm for large databases. In: Proc. ACM SIGMOD Internat. Conf. Management of Data, pp. 73-84.
  • 13
    • 0034228041 scopus 로고    scopus 로고
    • ROCK: A robust clustering algorithm for categorical attributes
    • Guha S., Rastogi R., and Shim K. ROCK: A robust clustering algorithm for categorical attributes. Inform. Systems 25 5 (2000) 345-366
    • (2000) Inform. Systems , vol.25 , Issue.5 , pp. 345-366
    • Guha, S.1    Rastogi, R.2    Shim, K.3
  • 15
    • 43249116682 scopus 로고    scopus 로고
    • Hinneburg, A., Keim, D., 1999. Optimal grid-clustering: Toward breaking the curse of dimensionality in high-dimensional clustering. In: Proc. 25th VLDB Conf., pp. 506-517.
    • Hinneburg, A., Keim, D., 1999. Optimal grid-clustering: Toward breaking the curse of dimensionality in high-dimensional clustering. In: Proc. 25th VLDB Conf., pp. 506-517.
  • 17
    • 33750527085 scopus 로고    scopus 로고
    • Information cut for clustering using a gradient decent approach
    • Jenssen R., Erdogmus D., Hild K., et al. Information cut for clustering using a gradient decent approach. Pattern Recognition 40 3 (2007) 796-806
    • (2007) Pattern Recognition , vol.40 , Issue.3 , pp. 796-806
    • Jenssen, R.1    Erdogmus, D.2    Hild, K.3
  • 18
    • 22944453351 scopus 로고    scopus 로고
    • Cluster validity in high-dimensional datasets
    • Kim M., Yoo H., and Ramakrishn R.S. Cluster validity in high-dimensional datasets. LNAI 3192 (2004) 178-187
    • (2004) LNAI , vol.3192 , pp. 178-187
    • Kim, M.1    Yoo, H.2    Ramakrishn, R.S.3
  • 19
    • 4344647570 scopus 로고    scopus 로고
    • Efficient disk-based K-means clustering for relational databases
    • Ordonez C., and Omiecinski E. Efficient disk-based K-means clustering for relational databases. IEEE Trans. Knowl. Data Eng. 16 8 (2004) 909-921
    • (2004) IEEE Trans. Knowl. Data Eng. , vol.16 , Issue.8 , pp. 909-921
    • Ordonez, C.1    Omiecinski, E.2
  • 20
    • 43249105582 scopus 로고    scopus 로고
    • Schikuta, E., 1993. Grid-Clustering: A hierarchical clustering method for very large data sets. In: Technical Report TR-CRPC No. 93358, Center for Research on Parallel Computation, Rice University, P.O. Box 1892, Houston, TX 77251-1892.
    • Schikuta, E., 1993. Grid-Clustering: A hierarchical clustering method for very large data sets. In: Technical Report TR-CRPC No. 93358, Center for Research on Parallel Computation, Rice University, P.O. Box 1892, Houston, TX 77251-1892.
  • 21
    • 43249112066 scopus 로고    scopus 로고
    • UCI Machine Learning Repository. .
    • UCI Machine Learning Repository. .
  • 22
    • 16444383160 scopus 로고    scopus 로고
    • Survey of clustering algorithm
    • Xu R., and Wunsch D. Survey of clustering algorithm. IEEE Trans. Neural Network 16 3 (2005) 645-661
    • (2005) IEEE Trans. Neural Network , vol.16 , Issue.3 , pp. 645-661
    • Xu, R.1    Wunsch, D.2
  • 24
    • 37249074851 scopus 로고    scopus 로고
    • A general c-means clustering approach
    • Yu J. A general c-means clustering approach. IEEE Trans. Pattern Anal. Machine Intell. 25 8 (2003) 944-952
    • (2003) IEEE Trans. Pattern Anal. Machine Intell. , vol.25 , Issue.8 , pp. 944-952
    • Yu, J.1
  • 25
    • 0030157145 scopus 로고    scopus 로고
    • Zhang, T., Ramakrishnan, R., Livny, M., 1996. BIRCH: An efficient data clustering method for very large databases. In: Proc. ACM SIGMOD Conf. Management of Data, pp. 103-114.
    • Zhang, T., Ramakrishnan, R., Livny, M., 1996. BIRCH: An efficient data clustering method for very large databases. In: Proc. ACM SIGMOD Conf. Management of Data, pp. 103-114.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.