期刊文献+

基于路由机制的时变路网k近邻算法 被引量:2

k-Nearest Neighbor Algorithm in Dynamic Road Network Based on Routing Mechanism
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摘要 针对现实生活中动态路网的地理信息查询问题,提出了一种基于路由机制的动态路网中k近邻查询的算法。其主导思想是利用空间换时间,用路由表保存历史查询结果,用查询路由表的方法代替传统的最短路径计算,通过历史数据减少系统重复计算并对车辆行驶路径进行规划,用更新路由表的方法适应路况的变化。围绕路由表这一核心,改进相应的k近邻算法的过滤、精炼过程。通过路由表对动态路网进行少量的预处理,减少系统在k近邻搜索中的候选点数量,缩小查询范围,提高搜索效率。 Aiming at the issue of geography information query, a new k-Nearest Neighbor algorithm for dynamic road network was proposed based on routing mechanism. With the idea of "space for time", we saved history query results in routing tables, and substituted the traditional method by requiring tables. We updated the route tables to adapt the time varying road status. With the kernel of routing table, we improved the filtering and refining procedure of kNN algo- rithm. By preprocess of dynamic road network using routing table, the amount of candidate points in k-NN computing is reduced, and the rang of query and the searching efficiency are promoted.
作者 张栋良 唐俊
出处 《计算机科学》 CSCD 北大核心 2013年第2期30-34,共5页 Computer Science
基金 国家自然科学基金青年基金项目(61003089)资助
关键词 路由机制 K近邻算法 时变路网 Routing mechanism,k-nearest neighbor algorithm,Dynamic road network
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参考文献11

  • 1孟小峰;丁治明.移动数据管理概念与技术[M]北京:清华大学出版社,2009.
  • 2Goodsell G. On finding p-th nearest neighbors of scattered points in two dimensions for small p[J].Computer Aided Geometric Design,2000.387-392.
  • 3Jensen C S,Pedersen K T B. Nearest neighbor queries in road networks[A].2003.1-8.
  • 4Roussopoulos N,Kelley S,Vincent F. Nearest neighbor queries[A].1995.71-79.
  • 5Bespamyatnikh S,Snoeyink J. Queries with segments in Voronoi diagrams[A].1999.122-129.
  • 6郝忠孝.时空数据库查询与推理[M]北京:科学出版社,2010.
  • 7赵亮,陈荦,景宁,廖巍.道路网中的移动对象连续K近邻查询[J].计算机学报,2010,33(8):1396-1404. 被引量:14
  • 8陈子军,任彩平,刘文远.路网中查询点速度不确定的连续k近邻查询方法[J].小型微型计算机系统,2011,32(3):430-434. 被引量:4
  • 9卢秉亮,刘娜.路网中移动对象快照K近邻查询处理[J].计算机应用,2011,31(11):3078-3083. 被引量:4
  • 10Demiryurek U,Banaei-Kashani F,Shahabi C. Efficient K-Nearest Neighbor Search in Time-Dependent Spatial Networks[A].2010.432-449.

二级参考文献44

  • 1王涛,李伟生.低代价最短路径树的快速算法[J].软件学报,2004,15(5):660-665. 被引量:29
  • 2林澜,闫春钢,辛肖刚,蒋昌俊.基于稳定分支的变权网络最优路径算法[J].电子学报,2006,34(7):1222-1225. 被引量:10
  • 3Wolfson Ouri.Moving objects information management:The database challenge//Proceedings of the International Workshop on Next Generation Information Technologies and Systems.Caesarea,Israel,2002:75-89.
  • 4Xiong Xiaopeng,Mohamed F M,Walid G A.SEA-CNN:Scalable processing of continuous k-nearest neighbor queries in spatio-temporal databases//Proceedings of the International Conference on Data Engineering.Tokyo,Japan,2005:643-654.
  • 5Yu Xiaohui,Ken Q P,Nick Koudas.Mointoring k-nearest neighbor queries over moving objects//Proceedings of the International Conference on Data Engineering.Tokyo,Japan,2005:631-642.
  • 6Mouratidis K,Hadjieleftheriou M,Papadias D.Conceptual partitioning:An efficient method for continuous nearest neighbor monitoring//Proceedings of the International Conference on Management of Data.Baltimore,USA,2005:634-645.
  • 7Hu Haibo,Xu Jianliang,Dik L L.A generic framework for monitoring continuous spatial queries over moving objects//Proceedings of the International Conference on Management of Data.Baltimore,USA,2005:479-490.
  • 8Hsueh Y L,Zimmermann R,Wang Haojun et al.Partition-based lazy updates for continuous queries over moving objects//Proceedings of the International Symposium on Advances in Geographic Information Systems.Seattle,USA,2007.
  • 9Mouratidis K,Yiu M L,Papadias D et al.Continuous nearest neighbor monitoring in road networks//Proceedings of the International Conference on Very Large Data Bases.Seoul,Korea,2006:43-54.
  • 10Demiryurek U,Banaei K F,Shahabi C.Efficient continuous nearest neighbor query in spatial networks using euclidean restriction//Proceedings of the International Symposium on Spatial and Temporal Database.Aalborg,Denmark,2009:25-43.

共引文献17

同被引文献27

  • 1张明波,陆锋,申排伟,程昌秀.R树家族的演变和发展[J].计算机学报,2005,28(3):289-300. 被引量:95
  • 2黄继先,鲍光淑,夏斌.基于混合聚类算法的动态R-树[J].中南大学学报(自然科学版),2006,37(2):366-370. 被引量:16
  • 3苏金树,张博锋,徐昕.基于机器学习的文本分类技术研究进展[J].软件学报,2006,17(9):1848-1859. 被引量:386
  • 4Atzori Luigi,Iera Antonio,Morabito Giacomo.The Internet of Things:A survey[J].Elsevier,2010,54(15):2787-2805.
  • 5Kotsiantis S B.Supervised Machine Learning:A Review of Classification Techniques Informatica[J].NSF,2007(31):249-268.
  • 6Hastie T,Tibshirani R,Friedman J.The Elements of Statistical Learning,Second Edition[M].Springer,2009.
  • 7Tom Mitchell.机器学习[M].北京:机械工业出版社,2003.
  • 8Zettsu,Koji.Knowledge processing technology:An overview of knowledge cluster systems[J].National Institute of Information and Communications Tech,2012,59(3):155-168.
  • 9李松,张丽平,孙冬璞.空间关系査询与分析[M].哈尔滨:哈尔滨工业大学出版社,2011.
  • 10Guttman A. R-Trees A Dynamic Index Structure for SpatialSearching[C] // Proceedings of Annual Metting ( SIGMOD 84).1984:18-21.

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