Visual Data Mining in Transportation Using Multiresolution Data Aggregation

被引：1

作者：

Wang, Xiao Kun ^{[1
]}

Yang, Li ^{[1
]}

机构：

[1] Western Michigan Univ, Dept Comp Sci, Kalamazoo, MI 49008 USA

来源：

FUZZY SYSTEM AND DATA MINING | 2016年 / 281卷

关键词：

Data aggregation; transportation data; visual data mining;

D O I：

10.3233/978-1-61499-619-4-195

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Big data pose fundamental challenges to both data mining and data visualization in transportation research. This paper presents a strategy of using multiresolution data aggregation as an efficient representation of large data for visual data mining. Data aggregated at multiple resolutions are stored in internal nodes of a partition-based high dimensional tree index. Such a multiresolution data representation has build-in support of data scalability. Existing visualization techniques are extended to support this data representation.

引用

页码：195 / 199

页数：5

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