摘要
交通事故数据中蕴含细粒度的局部时空模式,但它们往往被数据全集所掩盖而难以被发现.找到合适的数据子集是发现有意义的局部时空模式的重要前提,也是最为烦琐的过程.为此,提出基于张量分解方法自动获取数据子集的交通事故局部时空模式可视分析方法.首先,对交通事故数据集进行张量建模;并运用张量分解方法自动获取一组捕获了数据集各维度上的分布特征的向量,以表征数据集的多维模式;然后,利用这组向量指导数据集的聚类划分,从而将数据全集划分为若干有利于发现局部时空模式的数据子集,并设计了一套可视分析系统,以支持用户半自动化探索不同数据子集的局部时空模式和对得到的模式进行可视分析.最后,利用可视分析系统对合肥市交通事故接警数据进行局部时空模式的探索与分析,实验结果得到合肥交警部门相关专家的认同,表明该方法能够有效地辅助用户发掘数据集中所蕴含的局部时空模式.
Traffic accident data contains fine-grained local spatio-temporal patterns.They are difficult to detect because they are often obscured by the full data set.Finding the right subset of data is an important prerequisite for discovering meaningful local spatio-temporal patterns,and it is also the most cumbersome process.For this reason,a visual analysis method of local spatio-temporal patterns of traffic accidents based on tensor decom-position algorithm is proposed to automatically obtain data subsets.The tensor modeling of the traffic accident is performed first,and then the tensor decomposition algorithm is applied to the modeled tensor to obtain a set of vectors which capture the distribution of the dataset in each dimension and can characterize its multidimen-sional patterns.Then,this set of vectors is used to guide the clustering of the data set,thereby dividing the data set into several data subsets that are conducive to discovering local spatiotemporal patterns.A visual analytics system is also designed to support semi-automated exploration of different data subset with local spa-tio-temporal patterns and visual analytics of the obtained patterns.Finally,the visual analysis system is used to explore and analyze the local spatio-temporal patterns of traffic accident data in Hefei.The experimental re-sults are recognized by relevant experts from the Hefei traffic police department,indicating that this method can effectively assist users in discovering the local spatio-temporal patterns contained in the data set.
作者
罗月童
刘新月
郭正跃
刘晓平
Luo Yuetong;Liu Xinyue;Guo Zhengyue;Liu Xiaoping(School of Computer Science and Information Technology,Hefei University of Technology,Hefei 230601)
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2021年第8期1222-1233,共12页
Journal of Computer-Aided Design & Computer Graphics
基金
国家重点研发计划(2017YFB1402200)
国家自然科学基金(61602146)
安徽省科技攻关计划(1604d0802009).
关键词
交通事故
可视分析
局部时空模式
张量分解
traffic accident
visual analytics
local spatio-temporal patterns
tensor decomposition
