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Behavior Mining of Spatial Objects with Data Field 被引量:2

基于数据场的空间目标行为挖掘(英文)
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摘要 The advanced data mining technologies and the large quantities of remotely sensed Imagery provide a data mining opportunity with high potential for useful results. Extracting interesting patterns and rules from data sets composed of images and associated ground data can be of importance in object identification, community planning, resource discovery and other areas. In this paper, a data field is presented to express the observed spatial objects and conduct behavior mining on them. First, most of the important aspects are discussed on behavior mining and its implications for the future of data mining. Furthermore, an ideal framework of the behavior mining system is proposed in the network environment. Second, the model of behavior mining is given on the observed spatial objects, including the objects described by the first feature data field and the main feature data field by means of the potential function. Finally, a case study about object identification in public is given and analyzed. The experimental results show that the new model is feasible in behavior mining. The advanced data mining technologies and the large quantities of remotely sensed Imagery provide a data mining opportunity with high potential for useful results. Extracting interesting patterns and rules from data sets composed of images and associated ground data can be of importance in object identification, community planning, resource discovery and other areas. In this paper, a data field is presented to express the observed spatial objects and conduct behavior mining on them. First, most of the important aspects are discussed on behavior mining and its implications for the future of data mining. Furthermore, an ideal framework of the behavior mining system is proposed in the network environment. Second, the model of behavior mining is given on the observed spatial objects, including the objects described by the first feature data field and the main feature data field by means of the potential function. Finally, a case study about object identification in public is given and analyzed. The experimental results show that the new model is feasible in behavior mining.
出处 《Geo-Spatial Information Science》 2009年第3期202-211,共10页 地球空间信息科学学报(英文)
基金 Supported by the National 973 Program of China(No.2006CB701305,No.2007CB310804) the National Natural Science Fundation of China(No.60743001) the Best National Thesis Fundation (No.2005047) the National New Century Excellent Talent Fundation (No.NCET-06-0618)
关键词 behavior mining data field spatial object identification spatial data mining 数据挖掘技术 空间对象 行为 数据场 采矿系统 遥感图像 目标识别 数据字段
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参考文献10

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同被引文献18

  • 1刘健庄,栗文青.灰度图象的二维Otsu自动阈值分割法[J].自动化学报,1993,19(1):101-105. 被引量:356
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  • 10吕佩卓,赖声礼,胡蓉,陈佳阳.基于局部统计特征约束的Snake模型图像分割方法[J].华南理工大学学报(自然科学版),2007,35(9):36-39. 被引量:4

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