交通传感器数据的交互与协同可视化分析

2017 IEEE Conference on Visual Analytics Science and Technology (VAST) Pub Date : 2017-10-01 DOI:10.1109/VAST.2017.8585432

Chufan Lai, Qiangqiang Liu, Lu Feng, Chenglei Yue, Xi Chen, Yang Hu, Zhanyi Wang, Pengju Teng, Xiaoru Yuan

{"title":"交通传感器数据的交互与协同可视化分析","authors":"Chufan Lai, Qiangqiang Liu, Lu Feng, Chenglei Yue, Xi Chen, Yang Hu, Zhanyi Wang, Pengju Teng, Xiaoru Yuan","doi":"10.1109/VAST.2017.8585432","DOIUrl":null,"url":null,"abstract":"In VAST Challenge 2017, we propose an interactive and collaborative visual analytic system for the analysis of traffic sensor data. Our system fully incorporates the power of spatial-temporal visualization, sequence mining techniques and collaborative analysis. It allows users to conduct multi-facet and interactive data analysis in a highly efficient way. We discuss technical details in this report, and demonstrate the effectiveness of our system via convincing cases.","PeriodicalId":149607,"journal":{"name":"2017 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Interactive and Collaborative Visual Analysis on Traffic Sensor Data\",\"authors\":\"Chufan Lai, Qiangqiang Liu, Lu Feng, Chenglei Yue, Xi Chen, Yang Hu, Zhanyi Wang, Pengju Teng, Xiaoru Yuan\",\"doi\":\"10.1109/VAST.2017.8585432\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In VAST Challenge 2017, we propose an interactive and collaborative visual analytic system for the analysis of traffic sensor data. Our system fully incorporates the power of spatial-temporal visualization, sequence mining techniques and collaborative analysis. It allows users to conduct multi-facet and interactive data analysis in a highly efficient way. We discuss technical details in this report, and demonstrate the effectiveness of our system via convincing cases.\",\"PeriodicalId\":149607,\"journal\":{\"name\":\"2017 IEEE Conference on Visual Analytics Science and Technology (VAST)\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE Conference on Visual Analytics Science and Technology (VAST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VAST.2017.8585432\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Conference on Visual Analytics Science and Technology (VAST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VAST.2017.8585432","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

在VAST挑战赛2017中，我们提出了一个交互式和协作的视觉分析系统，用于分析交通传感器数据。我们的系统充分融合了时空可视化、序列挖掘技术和协同分析的力量。它允许用户以高效的方式进行多方面和交互式的数据分析。我们在本报告中讨论了技术细节，并通过令人信服的案例证明了我们系统的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Interactive and Collaborative Visual Analysis on Traffic Sensor Data

In VAST Challenge 2017, we propose an interactive and collaborative visual analytic system for the analysis of traffic sensor data. Our system fully incorporates the power of spatial-temporal visualization, sequence mining techniques and collaborative analysis. It allows users to conduct multi-facet and interactive data analysis in a highly efficient way. We discuss technical details in this report, and demonstrate the effectiveness of our system via convincing cases.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2017 IEEE Conference on Visual Analytics Science and Technology (VAST)

自引率

0.00%

发文量