Efficient clustering algorithm based on local optimality of K-means

Ruan Jian Xue Bao/Journal of Software

Volumn 19, Issue 7, 2008, Pages 1683-1692

  Lei, Xiao Feng ^a,b   Xie, Kun Qing ^a   Lin, Fan ^a   Xia, Zheng Yi ^c  

^a PEKING UNIVERSITY   (China)

^b CHINA UNIVERSITY OF MINING AND TECHNOLOGY   (China)

^c Logistics Science Research Institute   (China)

Author keywords

Clustering; Connectivity; Density based; K Means; K MeanSCAN

Indexed keywords

ALGORITHMS; CHLORINE COMPOUNDS; FLOW OF SOLIDS; GRAPH THEORY; LEARNING ALGORITHMS; OPTIMAL CONTROL SYSTEMS; SENSITIVITY ANALYSIS;

CLUSTERING; CLUSTERING QUALITY; CONNECTED GRAPHS; CONNECTIVITY; DENSITY-BASED; GRAPH-SEARCH ALGORITHMS; K-MEANS; K-MEANS ALGORITHMS; K-MEANSCAN; LOCAL MINIMUMS; LOCAL OPTIMALITY; NOVEL CLUSTERING; SUB-CLUSTERS;

CLUSTERING ALGORITHMS;

EID: 48549089676     PISSN: 10009825     EISSN: None     Source Type: Journal    
DOI: 10.3724/SP.J.1001.2008.01683     Document Type: Article

References (8)

1. Han JW, Kamber M. Data Mining: Concepts and Techniques. 2nd ed., Morgan Kaufmann Publishers, 2001. 223-250.
2. Ester M, Kriegel HP, Sander J, Xu XW. A density-based algorithm for discovering clusters in large spatial database with noise. In: Simoudis E, Han J, Fayyad UM, eds. Proc. of the 2nd Int'l Conf. on Knowledge Discovery and Data Mining. Portland: AAAI Press, 1996. 226-231.
3. Zhang T, Ramakrishnan R, Linvy M. BIRCH: An efficient data clustering method for very large databases. In: Jagadish HV, Mumick IS, eds. Proc. of the ACM SIGMOD Int'l Conf. on Management of Data. Montreal: ACM Press, 1996. 103-114.
4. Guha S, Rastogi R, Shim K. CURE: An efficient clustering algorithm for large databases. In: Haas LM, Tiwary A, eds. Proc. of the ACM SIGMOD Int'l Conf. on Management of Data. New York: ACM Press, 1998. 73-84.
5. Ankerst M, Breuning M, Kriegel HP, Sander J. OPTICS: Ordering points to identify the clustering structure. In: Delis A, Faloutsos C, Ghandeharizadeh S, eds. Proc. of the ACM SIGMOD Int'l Conf. on Management of Data. Philadelphia: ACM Press, 1999. 49-60.
6. Karypis G, Han EH, Kumar V. CHAMELEON: A hierarchical clustering algorithm using dynamic modeling. Computer, 1999, 32(8): 68-75.
7. Hand DJ, Vinciotti V. Choosing k for two-class nearest neighbour classifiers with unbalanced classes. Pattern Recognition Letters, 2003, 24(9): 1555-1562.
8. Stonebraker M, Frew J, Gardels K, Meredith J. The SEQUOIA 2000 storage benchmark. In: Buneman P, ed. Proc. of the ACM SIGMOD Int'l Conf. on Management of Data. Washington: ACM Press, 1993. 2-11.