{"title":"i-tStar: Interactive Trajectory Star Coordinates","authors":"Jing He, Lingxiao Li, Xin Wang","doi":"10.1145/3495018.3501046","DOIUrl":null,"url":null,"abstract":"There are many sources of geographic big data, and most of them come from heterogeneous environments. As the techniques evolved, these data sources contain attribute information of different spatial scales, time scales and complexity levels. In this case, visualizing high-dimensional spatiotemporal trajectory data is extremely challenging. Therefore, we propose a new solution, trajectory behavior feature, for moving objects that are integrated into a view to display and extract spatiotemporal patterns.","PeriodicalId":6873,"journal":{"name":"2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture","volume":"54 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3495018.3501046","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
There are many sources of geographic big data, and most of them come from heterogeneous environments. As the techniques evolved, these data sources contain attribute information of different spatial scales, time scales and complexity levels. In this case, visualizing high-dimensional spatiotemporal trajectory data is extremely challenging. Therefore, we propose a new solution, trajectory behavior feature, for moving objects that are integrated into a view to display and extract spatiotemporal patterns.