An efficient space-partitioning based algorithm for the K-means clustering

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

Volumn 1574, Issue , 1999, Pages 355-360

  AlSabti, Khaled ^a   Ranka, Sanjay ^b   Singh, Vineet ^c  

^a KING SAUD UNIVERSITY   (Saudi Arabia)

^b UNIVERSITY OF FLORIDA   (United States)

^c HITACHI AMERICA LTD   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA MINING;

DIRECT ALGORITHMS; INPUT PATTERNS; K-MEANS; NOVEL ALGORITHM; SPACE PARTITIONING;

K-MEANS CLUSTERING;

EID: 84947732194     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-48912-6_47     Document Type: Conference Paper

References (5)

1. K. AlSabti. Efficient Algorithms for Data Mining. Ph.D. Thesis, Syracuse University, 1998.
2. R. C. Dubes and A. K. Jain. Algorithms for Clustering Data. Prentice Hall, 1988.
3. D. Judd, P. McKinley, and A. Jain. Large-Scale Parallel Data Clustering. Proc. Int’l Conference on Pattern Recognition, August 1996.
4. K. Mehrotra, C.K. Mohan, and S. Ranka. Elements of Artificial Neural Networks. MIT Press, 1996.
5. T. Zhang, R. Ramakrishnan, and M. Livny. BIRCH: An Efficient Data Clustering Method for Very Large Databases. Proc. of the ACM SIGMOD’96.