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
收藏
页码：195 / 199
页数：5
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