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
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;
Conference_Titel :
Data Engineering, 1988. Proceedings. Fourth International Conference on
Conference_Location :
Los Angeles, CA
Print_ISBN :
0-8186-0827-7
DOI :
10.1109/ICDE.1988.105482