Paper Info
Title
Efficient and compact indexing structure for processing of spatial queries in line-based databases
Abstract
Points, lines and regions are the three basic entities for constituting vector-based objects in spatial databases. Many indexing schemes have been widely discussed for handling point or region data. These traditional schemes can efficiently organize point or region objects in a space into a hashing or hierarchical directory, and they provide efficient access methods for accurate retrievals. However, two difficulties arise when applying such methods to line segments: (1) the spatial information of line segments may not be precisely expressed in terms of that of points and/or regions, and (2) traditional methods for handling line segments can generate a large amount of dead space and overlapping areas in internal and external nodes in the hierarchical directory. The first problem impedes high-quality spatial conservation of line segments in a line-based database, while the second degrades the system performance over time. This study develops a novel indexing structure of line segments based on compressed B^+ trees. The proposed method significantly improves the time and space efficiencies over that of the R-tree indexing scheme.
Year
DOI
Venue
2008
10.1016/j.datak.2007.09.009
Data Knowl. Eng.
Keywords
Field
DocType
high-quality spatial conservation,spatial query,line-based databases,space efficiency,hierarchical directory,spatial information,r-tree indexing scheme,compact indexing structure,novel indexing structure,spatial databases,line segment,dead space,indexing scheme,system performance,indexation,line segments,r tree,gis,access method,spatial database
Spatial analysis,Data mining,R-tree,Line segment,Access method,Computer science,Directory,Search engine indexing,Hash function,Database,Spatial database
Journal
Volume
Issue
ISSN
64
1
0169-023X
Citations 
PageRank 
References 
5
0.54
17
Authors
1
Name
Order
Citations
PageRank
Hung-Yi Lin1398.74