An unsupervised grid-based approach for clustering analysis

Science in China, Series F: Information Sciences

Volumn 53, Issue 7, 2010, Pages 1345-1357

  Yue, Shi Hong ^a   Wang, Jeen Shing ^b   Tao, Gao ^a   Wang, Hua Xiang ^a  

^a TIANJIN UNIVERSITY   (China)

^b NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

Author keywords

Clustering; Grid based algorithm; K means algorithm

Indexed keywords

EID: 77954448046     PISSN: 10092757     EISSN: 18622836     Source Type: Journal    
DOI: 10.1007/s11432-010-3112-z     Document Type: Article

References (20)

1. MacQueen J B. Some methods for classification and analysis of multivariate observations. In: The 5th Berkeley Symposium on Mathematical and Probability. Berkeley, 1967, 1: 281-297.
2. Jenssen R, Erdogmus D, Hild K, et al. Information cut for clustering using a gradient decent approach. Patt Recogn, 2007, 40: 796-806.
3. Xu R, Wunsch D. Survey of clustering algorithm. IEEE Trans Neur Netw, 2005, 16: 645-678.
4. Guha S, Rastogi R, Shim K. CURE: An efficient clustering algorithm for large databases. Inf Syst, 2001, 26: 35-58.
5. Pedrycz W. Fuzzy clustering with a knowledge-based guidance. Patt Recogn Lett, 2004, 25: 469-480.
6. Huang Z, Ng M K, Rong H. Automated variable weighting in k-means type clustering. IEEE Trans Patt Anal Mach Intell, 2005, 27: 657-668.
7. Jing L, Gao Y, Wu G, et al. Feature weighting k-means algorithm for large-scale documents clustering. In: Proc. 1st China Classification Conf. Beijing, China, 2005, 1: 85-90.
8. Fabrizio S. Machine learning in automated text categorization. ACM Comput Surv, 2002, 34: 1-47.
9. Yu J. General C-means clustering model. IEEE Trans Patt Anal Mach Intell, 2003, 25: 1197-1211.
10. Hinneburg A, Keim D A. An efficient approach to clustering in large multimedia databases with noise. In: Proc Int Conf Knowl Disc Data Mining, New York, 1998. 58-65.
11. Eden W, Ma M, Tommy W S. A new shifting grid clustering algorithm. Patt Recogn, 2004, 37: 503-514.
12. Agrawal R, Gehrke J, Gunopulos D. Automatic subspace clustering of high dimensional data. Data Mining. Knowl Discov, 2005, 11: 5-33.
13. Yue S, Wei M, Wang J. A general grid-based approach to clustering. Patt Recogn Lett, 2008, 29: 1372-1384.
14. Ordonez C, Omiecinski E. Efficient disk-based K-means clustering for relational databases. IEEE Trans Knowl Data Eng, 2004, 16: 909-921.
15. Chiang J, Yin Z. Unsupervised minor prototype detection using an adaptive population partitioning algorithm. Patt Recogn, 2007, 40: 3132-3145.
16. Parizeau M, Lee S W. A fuzzy-syntactic approach to allograph modeling for cursive script recognition. IEEE Trans Patt Anal Mach Intell, 1995, 17: 702-712.
17. Chiang H, Yue S, Yin Z. A new fuzzy cover approach to clustering. IEEE Trans Fuzzy Syst, 2004, 12: 199-208.
18. AlphaMiner2. 0: http://bi. hitsz. edu. cn/alphaminer/index. htm.
19. Zalik K. An efficient k-means clustering algorithm. Patt Recogn Lett, 2008, 29: 1385-1391.
20. Krishnapuran R, Keller J M. A possiblistic c-means algorithm. IEEE Trans Fuzzy Syst, 1993, 2: 100-112.