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基于改进QR-树的空间数据索引的研究 被引量:3

Research on the spatial index based on improvement QR tree
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摘要 分析了基于常规QR-树建立空间数据索引的数据结构,常规四叉树在数据量特别大时,导致其QR-树深度特别深,占用空间大,查询效率低,并且平面区域分割极限的确定很不灵活。提出了一种改进QR-的数据模型来建立高效的空间数据索引,通过检测水平和垂直相交区域以确定图元所属节点,从而实现海量数据的快速检索。 It analyzes date structure that establishes spatial date index on the basis of general QR-tree. As data of QR-tree is great, which creates the depth of QR-deeper, more store space and lower efficiency of search, confirmation of the limit of plane region segmentation is not fairly flexible. Based on it, the author puts forward the date model improving QR-to establish effective spatial date index, and the method makes certain map element through checking intersecting aea at horizontal area, and vertical area, to realize quick index of multitudinous dates.
作者 黄明 陈哲
出处 《黑龙江工程学院学报》 CAS 2005年第3期18-20,共3页 Journal of Heilongjiang Institute of Technology
基金 黑龙江省教育厅资助项目(1054177)
关键词 QR-树 改进QR-树 空间索引 QR-tree improving QR-tree spatial index
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  • 1[1]Guttman A. R-trees: A Dynamic Index Structure for Spatial Searching. ACM SIGMOD, 1984
  • 2[2]Beckmann N, Kriegel H P, Schneider R, et al. The R*-tree: An Efficient and Robust Access Method for Points and Rectangles. ACM SIGMOD, Atlantic, USA, 1990
  • 3[3]Berchtold S, Keim D A, Kriegel H P. The X-tree: An Index Structure for High-Dimensional Data. The 22nd Int. Conf. on VLDB, Mumbai(Bombay), India, 1996
  • 4胡志勇,郭薇.空间数据库索引研究[J].计算机研究与发展,2000,(增刊):164-170.
  • 5[5]Sellis T,Roussopoulos N,Faloutsos C.The R+-tree:A Dynamic Index for Multi-dimensional Objects.The 13th Int.Conf.on Very Large Databases,Brighton,U.K.,1987
  • 6[1]A Guttman. R-Trees:A Dynamic Index Structure for Spatial Searching[C].In:Proc ACM SIGMOD, 1984-06:47~57
  • 7[2]N Beckmann,H P Kriegel,R Schneider et al.The R*-tree :An Efficient and Robust Access Method for Points and Rectangles[C].In:Proc ACM SIGMOD,Atlantic City,USA,1990:322~331
  • 8[3]T Sellis,N Roussopoulos,C Faloutsos.The R+-Tree:A Dynamic Index for Multidimensional Objects[C].In:Proc 13th Int Conf on Very Large Databases, Brighton, U K, 1987-09: 507~518
  • 9[4]S Berchtold,D A Keim,H P Kriegel.The X-tree :An Index Structure for High-Dimensional Data[C].In:Proc of the 22nd Int Conf on VLDB,Mumbai(Bombay) ,India, 1996:28~39
  • 10郑玉明,廖湖声.面向空间数据库引擎的扩充数据模型及其操纵语言GSQL[J].计算机工程与应用,2002,38(3):123-125. 被引量:13

共引文献50

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  • 1董鹏,李津平,白予琦,钱贞国,杨崇俊.基于改进四叉树索引的矢量地图叠加分析算法[J].计算机辅助设计与图形学学报,2004,16(4):530-534. 被引量:17
  • 2徐少平,王命延,王炜立.一种基于R树和四叉树的移动对象空间数据库混合索引结构[J].计算机与数字工程,2006,34(3):54-57. 被引量:8
  • 3吴敏君,郭永洪,陈天滋.一种有效的混合空间索引机制[J].计算机工程与应用,2006,42(29):193-197. 被引量:4
  • 4GAEGAN M. A efficient use of Quadtrees in a geographical information system[J]. Int. J. GIS, 1989,3 (3) : 32-- 43.
  • 5Zuliansyah M,Supangkat S H,Priyana Y,et al.3D Spatial Models for Geometric Description of Spatial Ohjects[C] //Proc.of the 2008 IEEE Int'l Conf.on Cybernetics and Intelligent Systems.Chengdu.China:[s.n.] ,2008.
  • 6Fu Yuchen,Hu Zhiyong,Guo Wei.et al.A Hybrid Spatial Index Structure[C] //Proc.of the 2003 Int'l Conf.on Machine Learning and Cybernetics.Xi'an,China:[s.n.] ,2003.
  • 7Mao Huaqing,Bian Fuling.Design and Implementation of QR+Tree Index AIgorithms[C] //Proc.of the 2007 Int'l Conf.on Wireless Communications,Networking and Mobile Computing.Shanghai,China:[s.n.] ,2007.
  • 8Zalik K R.An Efficient K-means Clustering Algorithm[J].Pattern Recognition Letters,2008,29(9):1385-1391.
  • 9程承旗,任伏虎,濮国梁,等.空间信息剖分组织导论[M].北京:科学出版社,2012.
  • 10Finkel R A , Bentley J L. Quad Trees a Data Struc- ture for Retrieval on Composite Keys[J], Acta In- formatica ,1974,4(1) : 1-9.

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