基于加权欧氏距离的空间Co-location模式挖掘算法研究

计算机科学 ›› 2014, Vol. 41 ›› Issue (Z6): 425-428.

基于加权欧氏距离的空间Co-location模式挖掘算法研究

周剑云,王丽珍,杨增芳

普洱学院计算机科学系普洱665000;云南大学信息学院计算机科学与工程系昆明650091;玉溪师范学院信息技术工程学院玉溪653100

出版日期:2018-11-14 发布日期:2018-11-14
基金资助:
本文受云南省教育厅科研基金项目:支持网络课程建设的数据挖掘构架研究(2013Y107),国家自然科学基金项目:非线性环境取能系统随机动力学问题研究(11265012)资助

Algorithm of Mining Spatial Co-location Patterns Based on Weighted Euclidean Distance

ZHOU Jian-yun,WANG Li-zhen and YANG Zeng-fang

Online:2018-11-14 Published:2018-11-14

摘要/Abstract

摘要： 空间Co_location模式挖掘关注空间对象实例在一定区域内同时出现的关系。目前大多数研究都是把空间对象的各个实例按同等权重对待,但现实中容易发现同一类对象的不同实例其大小规模、重要程度或是影响力覆盖范围都是不一样的。因此考虑空间对象实例的影响力因素,引入加权欧氏距离阈值参与计算,能发现更具实际价值的Co_location模式。

关键词: 空间数据挖掘,Co-location模式挖掘,加权欧氏距离中图法分类号TP392文献标识码A

Abstract: The spatial Co-location pattern mining concerns about occurrence relationship of spatial objects’ instances at the same time in a certain area．Most of the papers studied based on the spatial objects’ instances have the same weight,but in reality it is easy to find that the different instances of the same type of object probably has different size,different importance,or different influence．In this paper,we consider the influence factors of the spatial objects’ instances.A concept of the weighted Euclidean distance was introduced and corresponding mining algorithm was designed,in order to find more valuable spatial co-location rules．

Key words: Spatial data mining,Co-location pattern mining,Weighted euclidean distance

周剑云,王丽珍,杨增芳. 基于加权欧氏距离的空间Co-location模式挖掘算法研究[J]. 计算机科学, 2014, 41(Z6): 425-428. https://doi.org/

ZHOU Jian-yun,WANG Li-zhen and YANG Zeng-fang. Algorithm of Mining Spatial Co-location Patterns Based on Weighted Euclidean Distance[J]. Computer Science, 2014, 41(Z6): 425-428. https://doi.org/

参考文献

[1] 高世健,王丽珍,等.基于凝聚层次聚类的co_location模式挖掘[J].广西师范大学学报:自然科学版,2011(29):167-173
[2] 边馥苓,万幼．k_邻近空间关系下的空间同位模式挖掘算法[J].武汉大学学报:信息科学版,2009(34):331-338
[3] 王占全,王申康,华成.空间分类数据同位规则挖掘算法[J].计算机辅助设计与图形学学报,2005(17):2339-2344
[4] 杨柽,李勃,等．同位模式挖掘中一种改进的极大团事务化算法[J].云南民族大学学报,2010(19):305-308
[5] 周园,云正富,赵国庆.基于空间同位模式的贝叶斯网构建[C]∥Proceedings of 2010International Conference on Broadcast Technology and Multimedia Communication．Volume 2,2010
[6] 陆叶,王丽珍,张晓峰.从不确定数据集中挖掘频繁Co-location模式[J].计算机科学与探索,2009,3(6):656-664
[7] 高世健,王丽珍,肖清.一种基于U_AHC的不确定空间co_location模式挖掘算法[J].计算机研究与发展,2011(S3):60-66
[8] 肖清,陈红梅,王丽珍.基于DS理论的不确定空间co_location模式挖掘[J].云南大学学报:自然科学版,2011,3(S2):182-187
[9] 欧阳志平,王丽珍,周丽华.实例位置模糊的空间co_location模式挖掘研究[J].计算机科学与探索,2012(12):1144-1152
[10] 欧阳志平,王丽珍,陈红梅.模糊对象的空间Co_location模式挖掘研究[J].计算机学报,2011(10):1947-1954
[11] 冯岭,王丽珍,高世健.一种带稀有特征的空间co-location模式挖掘新方法[J]．南京大学学报:自然科学版,2012(1):99-107
[12] 陆亿红,王子仁,黄燕.适合稀少空间特征的同位模式挖掘算法[J].浙江工业大学学报,2007(4):408-412
[13] S Sha-shi,Huang Yan.Discovering spatial co-location patterns:Asummary of results[C]∥Proceedings of the 7thInternational Symposium on Spatial and Temporal Databases．Redondo Beach,CA,2001:236-256
[14] Uang Y,Xiong H,Shekhar S,et al．Mining Confident Co-location Rules without A Support Threshold[C]∥Proc．2003ACMSymposium on Applied Computing．New York,NY,USA,2003:497-501
[15] Xiong H,Shekhar S,Huang Y,et al.A Framework for discove-ringco-location patterns in datasets with extended spatial objects[C]∥Berry M W,Dayal U,Kamath C,et al.,eds.Proceedings of theFourth SIAM International Conference on Data Mining.Flo-rida,USA,2004:78-89
[16] Yoo Jin Soung,Shekhar S.A partial join approach for mining co-location patterns[C]∥Foser D P,Cruz I F,Ronthaler M．,eds.12^thACM International Workshop on Geographic Information Systems．Washington,DC,USA,2004:241-249
[17] Yoo Jin Soung,Shekhar S,Celik M.A Join-less Approach forCo-location Pattern Mining:A Summary of Results[C]∥Proceedings of the IEEE International Conference on Data Mining (ICDM)．Houston,USA,2005

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