重庆邮电大学学报（自然科学版）2018，Vol.30Issue(1)：40-52,13.DOI:10.3979/j.issn.1673-825X.2018.01.005
面向公共安全的时空数据挖掘综述
A survey of data mining on spatial-temporal user behavior data for public safety
摘要
Abstract
With the popularity of smart phones and wireless sensors,large amount of data with timestamps and geo-locations (spatial-temporal) has been produced continuously.This spatial-temporal data records individual behaviors by time and locations,shows macro and micro behavior patterns of people by statistical methods,which is very important for studying the human behavior,especially significant for managing the public safety for city administrators.In this paper,we survey the state-of-the-art research of the human behavior mining for public safety on spatial-temporal data in four aspects,and provide our work in each aspect respectively.We discussed two types of spatial-temporal data,one is smartphone data,and the other is smart card data of public transit.The former shows the individual and crowd behavior from "point" view,and the latter shows the crowd behavior pattern from "line" view.With the former data,we discussed how to discover suspect individuals;with the latter data,we introduced how to find harmful events from short-term and burst passenger traffic,so as to provide the early warning to administration if necessary.We compared our model with existing ones such as ARIMA,SARI-MA,SVR,NN,and LSTM.The result shows that our model can reduce the error up to 27.78％ for short-term traffic prediction,and up to 14.68x for burst traffic prediction.关键词
时空分析/大数据/异常发现/数据预测Key words
spatial-temporal analysis/big data/outlier detection/prediction分类
信息技术与安全科学引用本文复制引用
王永坤,王海洋,潘平峻,李龙元,金耀辉..面向公共安全的时空数据挖掘综述[J].重庆邮电大学学报（自然科学版）,2018,30(1):40-52,13.基金项目
国家自然科学基金(61371084)The National Natural Science Foundation of China(61371084) （61371084）
