A Novel Method for Classifying Function of Spatial Regions Based on Two Sets of Characteristics Indicated by Trajectories

IF 0.5 4区计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING

International Journal of Data Warehousing and Mining Pub Date : 2020-07-01 DOI:10.4018/ijdwm.2020070101

Haitao Zhang, Che Yu, Yan Jin

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引用次数: 0

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

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基于轨迹表示的两组特征的空间区域函数分类新方法

Trajectoryisasignificantfactorforclassifyingfunctionsofspatialregions。Manyspatialclassification方法使用轨迹来探测城市环境中的建筑物和区域。然而，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。关键词:空间区域功能，全局连接特征，局部时空特征，空间分类，轨迹

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来源期刊

International Journal of Data Warehousing and Mining COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

2.40

自引率

0.00%

发文量

审稿时长

>12 weeks

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