Title :
A new node-split algorithm in R-tree based on spatial clustering
Author :
Gong, Jun ; Ke, Shengnan
Author_Institution :
Key Lab. of Poyang Lake Wetland & Watershed, Jiangxi Normal Univ., Nanchang, China
Abstract :
R-tree is widely used in spatial database as a spatial access method. The node-split algorithm is the key sub-algorithm to generate R-tree. In traditional methods, the one-to-two split mode is applied. However, this leads to uneven node-shape. A brand-new node-split method is put forward. In this method, the 2-to-3 split mode is utilized based on spatial clustering principle, which can guarantee more average node shape. This feature can make the query performance more stable.
Keywords :
pattern clustering; tree data structures; visual databases; 2-to-3 split mode; R-tree based; brand new node split method; key sub algorithm; node split algorithm; query performance; spatial access method; spatial clustering; spatial database; split mode; uneven node shape; Algorithm design and analysis; Clustering algorithms; Heuristic algorithms; Pediatrics; Shape; Spatial databases; Three dimensional displays; R-tree; node-split; spatial clustering; spatial database;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2010 Seventh International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5931-5
DOI :
10.1109/FSKD.2010.5569703
