轨迹数据挖掘-介绍.ppt

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1、Chapter1TrajectoryPreprocessingJohnKrummMicrosoftResearchRedmond,WAUSAWang-ChienLeePennsylvaniaStateUniversityUniversityPark,PAUSATrafficinfoNavigationLocalweatherEmergencyserviceLogisticsLocation-BasedServicesGeographicalInformationSystem(GIS)TrackingMobileCommerceSystemModelforLBS

2、sThelocationsoftrackedmovingobjectsarereportedtothelocationserverviawirelesscommunications.TheLBSapplicationssubmitqueriestotheservertoretrievemovingobjectdataforanalysisorotherapplicationneeds.Trajectories{,,...,}PositioningtechnologiesGlobalpositioning

3、system(GPS)Network-based(e.g.,usingcellularorwifiaccesspoints)Dead-Reckoning(forestimation)MobileObjectDatabasesResearchcommunitieshavemadetremendousresearchefforttosupportLBSs.E.g.,Mobileobjectdatabases(MODs)Inadditiontoconventionalsearchfunctionsofmovingobjects,manyLBSapplicationsn

4、eedtoanalyzeandminevariousmovingpatternsandphenomenonoftrackedobjects.TrajectoryManagement:trajectoriesofmovingobjects,i.e.,theirgeographical-temporaltraces,areoftentreatedasfirst-classcitizensinMODs.TrajectoryPreprocessingProblemstosolvewithtrajectoriesLotsoftrajectories→lotsofdataN

5、oisecomplicatesanalysisandinferenceEmploythedatareductionandfilteringtechniquesSpecializeddatacompressionfortrajectoriesPrincipledfilteringtechniquesPart1-CompressionPerformanceMetricsTrajectorydatareductiontechniquesaimstoreducetrajectorysizew/ocompromisingmuchprecision.PerformanceM

6、etricsProcessingtimeCompressionRateErrorMeasureThedistancebetweenalocationontheoriginaltrajectoryandthecorrespondingestimatedlocationontheapproximatedtrajectoryisusedtomeasuretheerrorintroducedbydatareduction.ExamplesarePerpendicularEuclideanDistanceorTimeSynchronizedEuclideanDistanc

7、e.IllustrationofErrorMeasuresPerpendicularEuclideanDistanceTimeSynchronizedEuclideanDistanceTrajectoryDataReductionClassificationofDataReductionTechniques.BatchedCompression:Collectfullsetoflocationpointsandthencompressthedatasetfortransmissiontothelocationserver.Applications:content

8、sharingsites