Proceedings of the sixteenth international conference on Very large databases
SIGMOD '91 Proceedings of the 1991 ACM SIGMOD international conference on Management of data
A qualitative comparison study of data structures for large line segment databases
SIGMOD '92 Proceedings of the 1992 ACM SIGMOD international conference on Management of data
Multidimensional access methods
ACM Computing Surveys (CSUR)
The Grid File: An Adaptable, Symmetric Multikey File Structure
ACM Transactions on Database Systems (TODS)
Multidimensional binary search trees used for associative searching
Communications of the ACM
The K-D-B-tree: a search structure for large multidimensional dynamic indexes
SIGMOD '81 Proceedings of the 1981 ACM SIGMOD international conference on Management of data
A class of data structures for associative searching
PODS '84 Proceedings of the 3rd ACM SIGACT-SIGMOD symposium on Principles of database systems
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
G-Tree: A New Data Structure for Organizing Multidimensional Data
IEEE Transactions on Knowledge and Data Engineering
Spatial Searching in Geometric Databases
Proceedings of the Fourth International Conference on Data Engineering
The Generalized Grid File: Description and Performance Aspects
Proceedings of the Sixth International Conference on Data Engineering
Efficient Processing of Spatial Queries in Line Segment Databases
SSD '91 Proceedings of the Second International Symposium on Advances in Spatial Databases
Indexing the fully evolvement of spatiotemporal objects
WSEAS Transactions on Information Science and Applications
Ordered polyline trees for efficient search of objects moving on a graph
ICCSA'10 Proceedings of the 2010 international conference on Computational Science and Its Applications - Volume Part I
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Points, lines, and regions are the three basic entities for constituting vector-based objects in spatial databases. Many indexing methods (G-tree, K-D-B tree, Quad-tree, PMR-tree, Grid-file, R-tree, and so on) have been widely discussed for handling point or region data. These traditional methods can efficiently organize point or region objects in a space into a hashing or hierarchical directory. They provide efficient access methods to meet the requirement of accurate retrievals. However, two problems are encountered when their techniques are applied to deal with line segments. The first is that representing line segments by means of point or region objects cannot exactly and properly preserve the spatial information about the proximities of line segments. The second problem is derived from the large dead space and overlapping areas in external and internal nodes of the hierarchical directory caused by the use of rectangles to enclose line objects. In this paper, we propose an indexing structure for line segments based on B + -tree to remedy these two problems. Through the experimental results, we demonstrate that our approach has significant improvement over the storage efficiency. In addition, the retrieval efficiency has also been significantly prompted as compared to the method using R-tree index scheme. These improvements derive mainly from the proposed data processing techniques and the new indexing method.