A Novel Visual analytics Approach for Clustering Large-Scale Social Data

A Novel Visual analytics Approach for Clustering Large-Scale Social Data

ID:40557827

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页数:8页

时间:2019-08-04

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1、2013IEEEInternationalConferenceonBigDataANovelVisualanalyticsApproachforClusteringLarge-ScaleSocialDataZhangyeWangJuanxiaZhouWeiChenStateKeyLabofCAD&CGStateKeyLabofCAD&CGStateKeyLabofCAD&CGZhejiangUniversityZhejiangUniversityZhejiangUniversityHangzhou,ChinaHangzhou,ChinaHangzhou,Chinazywan

2、g@cad.zju.edu.cnxjzhou@zjucadcg.zju.edu.cnchenwei@cad.zju.edu.cnChangChenJiyuanLiaoRossMaciejewskiCollegeofSoftwareEngineeringStateKeyLabofCAD&CGSchoolofCIDSEUniversityofScienceandTechnologyofChinaZhejiangUniversityArizonaStateUniversityHefei,ChinaHangzhou,ChinaUSAlawangel@163.comjyliao@zj

3、ucadcg.zju.edu.cnrmacieje@asu.eduAbstract—Socialdatareferstodataindividualscreatethatistypeofdataasusertagdata.knowinglyandvoluntarilysharedbythemandisanexcitingGiventheubiquityofsuchdata,methodsforexploringavenueintogaininginsightintointerpersonalbehaviorsandandanalyzingsocialdatalinkshav

4、ebecomeacriticalinteraction.However,suchdataislarge,heterogeneousandresearchtopic.Byanalyzingusertagsanduserbehavioroftenincomplete,propertiesthatmaketheanalysisofsuchdataextremelychallenging.Onecommonmethodofexploringdata,itisexpectedthatinsightsintosocietalpatternscansuchdataisthroughclu

5、steranalysis,whichcanenableanalystsbegleanedandusedtoinformgovernmentalpolicyandtofindgroupsofrelatedusers,behaviorsandinteractions.Thisbusinessdecisionsaswellasinfluencehumanbehavior[2].paperpresentsanovelvisualanalysisapproachfordetectingForexample,previouswork[3]exploresclusteringusersclu

6、sterswithinlarge-scalesocialnetworksbyutilizingadivide-intogroupstodeveloptargetedmarketstrategybasedonanalyze-recombineschemethatsequentiallyperformsdatapartitioning,subsetclusteringandresultrecombinationwithindemographicsandbehavioralpatterns.However,ourabil-anintegratedvisualinterface.A

7、casestudyonamicroblogitytoextractknowledgefromtheselargeheterogeneousmessagingdata(with4.8millionsusers)isusedtodemonstratedatasourcesisstilllimitedduetothelatent,subtleandthefeasibilityofthisapproachandcomparisonsarealsounpredictablerelationshipsthatmaybehidd

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