DocumentCode
2500860
Title
Adaptive algorithms for balanced multidimensional clustering
Author
Yu, Clement T. ; Jiang, Tsang Ming
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., Illinois Univ., Chicago, IL, USA
fYear
1988
fDate
1-5 Feb 1988
Firstpage
386
Lastpage
393
Abstract
The G-K-D tree (generalized K-D tree) method aims at reducing the average number of data page accesses per query, but it ignores the cost of index search. The authors propose two adaptive algorithms that take into consideration both data page access cost and index page access cost. It attempts to find a minimum total cost. Experimental results indicate that the proposed algorithms are superior to the G-K-D tree method
Keywords
database theory; pattern recognition; trees (mathematics); G-K-D tree; adaptive algorithms; balanced multidimensional clustering; data page access cost; data page accesses per query; generalized K-D tree; index page access cost; index search; Adaptive algorithm; Clustering algorithms; Costs; Databases; Multidimensional systems; Remuneration; Upper bound;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Engineering, 1988. Proceedings. Fourth International Conference on
Conference_Location
Los Angeles, CA
Print_ISBN
0-8186-0827-7
Type
conf
DOI
10.1109/ICDE.1988.105482
Filename
105482
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