{"title":"基于轨迹表示的两组特征的空间区域函数分类新方法","authors":"Haitao Zhang, Che Yu, Yan Jin","doi":"10.4018/ijdwm.2020070101","DOIUrl":null,"url":null,"abstract":"Trajectoryisasignificantfactorforclassifyingfunctionsofspatialregions.Manyspatialclassification methods use trajectories to detect buildings and districts in urban settings. However, methods thatonly take intoconsideration the localspatiotemporalcharacteristics indicatedby trajectories maygenerateinaccurateresults.Inthisarticle,anovelmethodforclassifyingfunctionofspatial regionsbasedontwosetsofcharacteristicsindicatedbytrajectoriesisproposed,inwhichthelocal spatiotemporalcharacteristicsaswellastheglobalconnectioncharacteristicsareobtainedthrough twosetsofcalculations.Themethodwasevaluatedintwoexperiments:onethatmeasuredchanges in theclassificationmetric throughasplits ratiofactor,andone thatcompared theclassification performancebetweentheproposedmethodandmethodsbasedonasinglesetofcharacteristics.The resultsshowedthattheproposedmethodismoreaccuratethanthetwotraditionalmethods,witha precisionvalueof0.93,arecallvalueof0.77,andanF-Measurevalueof0.84. KeyWoRDS Function of Spatial Regions, Global Connection Characteristics, Local Spatiotemporal Characteristics, Spatial Classification, Trajectory","PeriodicalId":54963,"journal":{"name":"International Journal of Data Warehousing and Mining","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Novel Method for Classifying Function of Spatial Regions Based on Two Sets of Characteristics Indicated by Trajectories\",\"authors\":\"Haitao Zhang, Che Yu, Yan Jin\",\"doi\":\"10.4018/ijdwm.2020070101\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Trajectoryisasignificantfactorforclassifyingfunctionsofspatialregions.Manyspatialclassification methods use trajectories to detect buildings and districts in urban settings. However, methods thatonly take intoconsideration the localspatiotemporalcharacteristics indicatedby trajectories maygenerateinaccurateresults.Inthisarticle,anovelmethodforclassifyingfunctionofspatial regionsbasedontwosetsofcharacteristicsindicatedbytrajectoriesisproposed,inwhichthelocal spatiotemporalcharacteristicsaswellastheglobalconnectioncharacteristicsareobtainedthrough twosetsofcalculations.Themethodwasevaluatedintwoexperiments:onethatmeasuredchanges in theclassificationmetric throughasplits ratiofactor,andone thatcompared theclassification performancebetweentheproposedmethodandmethodsbasedonasinglesetofcharacteristics.The resultsshowedthattheproposedmethodismoreaccuratethanthetwotraditionalmethods,witha precisionvalueof0.93,arecallvalueof0.77,andanF-Measurevalueof0.84. KeyWoRDS Function of Spatial Regions, Global Connection Characteristics, Local Spatiotemporal Characteristics, Spatial Classification, Trajectory\",\"PeriodicalId\":54963,\"journal\":{\"name\":\"International Journal of Data Warehousing and Mining\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2020-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Data Warehousing and Mining\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.4018/ijdwm.2020070101\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Data Warehousing and Mining","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.4018/ijdwm.2020070101","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
期刊介绍：
The International Journal of Data Warehousing and Mining (IJDWM) disseminates the latest international research findings in the areas of data management and analyzation. IJDWM provides a forum for state-of-the-art developments and research, as well as current innovative activities focusing on the integration between the fields of data warehousing and data mining. Emphasizing applicability to real world problems, this journal meets the needs of both academic researchers and practicing IT professionals.The journal is devoted to the publications of high quality papers on theoretical developments and practical applications in data warehousing and data mining. Original research papers, state-of-the-art reviews, and technical notes are invited for publications. The journal accepts paper submission of any work relevant to data warehousing and data mining. Special attention will be given to papers focusing on mining of data from data warehouses; integration of databases, data warehousing, and data mining; and holistic approaches to mining and archiving
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