A visual approach for spatio-temporal data mining

被引：0
|
作者：
Kechadi, M-Tahar [1 ]
Bertolotto, Michela [1 ]
机构：
[1] Natl Univ Ireland Univ Coll Dublin, Sch Informat & Comp Sci, Dublin 4, Ireland
来源：
IRI 2006: PROCEEDINGS OF THE 2006 IEEE INTERNATIONAL CONFERENCE ON INFORMATION REUSE AND INTEGRATION | 2006年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper we propose a system for mining very large spatio-temporal datasets. The system comprises new techniques to efficiently support the data-mining process, address the spatial and temporal dimensions of the dataset, and visualize and interpret results. In particular, we have developed an advanced visualization tool for flexible and intuitive interaction with the dataset, including functionality for displaying association rules and variable distributions.
引用
收藏
页码：504 / +
页数：2
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