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空间co-location模式挖掘算法研究综述

Summary on Algorithms for Mining Spatial Co-location Patterns
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摘要 空间co-location模式代表的是一组空间特征的子集,它们的实例在空间中频繁的关联。它是空间数据挖掘的一个重要研究方向。首先给出co-location模式的基本概念;然后描述了针对不同数据领域提出的各种算法,并重点分析了算法提出的思路及主要特点;最后对Co-location模式挖掘未来的研究方向作了探讨。 Spatial co-location patterns are traditionally defined as the subsets of features whose instances are frequently located together in geographic space .It is an important research direction for spatial data mining .Firstly ,the concepts of co-location patterns are reviewed .Then ,many popular algorithms based on different data fields are described ,which highlights the processes and dominant features of different co-location algorithms .Finally ,the future work on co-location patterns min-ing algorithms are discussed .
作者 余翠兰
机构地区 云南德宏师范高等专科学校计算机科学系
出处 《计算机与数字工程》 2014年第7期1131-1136,共6页 Computer & Digital Engineering
基金 云南省教育厅科学研究基金项目(编号:2013c202 2013Y571)资助
关键词 CO-LOCATION模式 负模式 稀有特征 不确定数据 co-location pattern negative pattern rare features uncertain data
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
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参考文献38

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二级参考文献73

  • 1包玉珍,王丽珍,周丽华.空间co-location模式挖掘算法介绍及应用[J].郑州大学学报（理学版）,2007,39(3):84-88. 被引量：2
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  • 4Huang Y, Shekhar S, Xiong H. Discovering colocation patterns from spatial data sets: A general approach[J]. IEEE Transactions on Knowledge and Data Engineering, 2004,16(12): 1472-1485.
  • 5Yoo J S, Shekhar S, Celik M. A Join-less approach for colocation pattern mining: A summary of results[C]//Proc of the 5th IEEE Int Conf on Data Mining, ICDM 2005, Houston, Nov, 2005 : 813-816.
  • 6Yoo J, Shekhar S. A partial join approach for mining co-location patterns[C]//Proc of ACM International Symposium on Advances in Geographic Information Systems (ACM-GIS), 2004.
  • 7Wang L, Bao Y, Lu J, et al. A new join-less approach for colocation pattern mining[C]//Proceedings of the IEEE 8th International Conference on Computer and Information Technology (CIT2008), Syney, Australia, 2008: 197-202.
  • 8Wang Lizhen, Bao Yuzhen, Lu Zhongyu. Efficient discovery of spatial co-location patterns using the iCPI-tree[J]. The Open Information Systems Journal, 2009,3 : 69-80.
  • 9Wang Lizhen, Zhou Lihua, Lu Joan, et al. An order-cliquebased approach for mining maximal co-locations[J]. Information Sciences, 2009, 179:3370-3382.
  • 10Kao B, Lee S D, Cheung D W, et al. Clustering uncertain data using voronoi diagrams[C]//Sth IEEE International Conference on Data Mining, ICDM'08, Pisa, 15-19 Dec, 2008:333-342.

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计算机与数字工程
2014年 第7期

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