DocumentCode :
1773409
Title :
Research for the nearest neighbor query based on RBRT tree
Author :
Tang Yuanxin ; Guo Wenlan ; Cui Yongli ; Lan Huajian ; Chen Deyun
Author_Institution :
Sch. of Comput. Sci. & Technol., Harbin Univ. of Sci. & Technol. Harbin, Harbin, China
fYear :
2014
fDate :
21-23 Oct. 2014
Firstpage :
251
Lastpage :
254
Abstract :
The nearest neighbor query of spatial dataset is an important issue in spatial data query area. In order to overcome the disadvantages of existing spatial index structure in data organization and querying, the new nearest neighbor query methods and pruning rules were proposed based on RBRT tree. The NN RT search algorithm was given. The NN_RT search approach calculated and pruned nodes of each level from top to bottom. A large number of data points were filtered in advance. Furthermore, in allusion to the data information of the trapezoidal spatial object and trapezoidal distribution, the methods of querying nearest neighbor in the restricted area based on RBRT tree were studied, The NN_FRTsearch algorithm and NN_LRTsearch algorithm were proposed. Theory and experiments show the algorithms which proposed have certain advantages on the aspect of query efficiency.
Keywords :
data handling; pattern clustering; query processing; NN RT search algorithm; RBRT tree; data information; data organization; data points; data querying; nearest neighbor query methods; nearest neighbor querying; pruning rules; spatial data query area; spatial dataset; spatial index structure; trapezoidal distribution; trapezoidal spatial object; Algorithm design and analysis; Educational institutions; Filtering algorithms; Nearest neighbor searches; Spatial databases; Spatial indexes; R tree; RBRT tree; nearest neighbor query; restricted area; spatial data clustering;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Strategic Technology (IFOST), 2014 9th International Forum on
Conference_Location :
Cox´s Bazar
Print_ISBN :
978-1-4799-6060-6
Type :
conf
DOI :
10.1109/IFOST.2014.6991115
Filename :
6991115
Link To Document :
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