土木工程专业聚类分析基本概念及算法大学毕业论文外文文献翻译及原文.docx

土木工程专业聚类分析基本概念及算法大学毕业论文外文文献翻译及原文.docx

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土木工程专业聚类分析基本概念及算法大学毕业论文外文文献翻译及原文

毕业设计（论文）

外文文献翻译

文献、资料中文题目：

聚类分析—基本概念及算法

文献、资料英文题目：

文献、资料来源：

文献、资料发表（出版）日期：

院（部）：

专业：

土木工程

班级：

姓名：

学号：

指导教师：

翻译日期：

2017.02.14

本科毕业论文

外文文献及译文

文献、资料题目：

ClusterAnalysis

—BasicConceptsandAlgorithms

文献、资料来源：

文献、资料发表（出版）日期：

院（部）：

土木工程学院

专业：

土木工程

外文文献：

ClusterAnalysis

—BasicConceptsandAlgorithms

Clusteranalysisdividesdataintogroups（clusters）thataremeaningful,useful,orboth.Ifmeaningfulgroupsarethegoal,thentheclustersshouldcapturethenaturalstructureofthedata.Insomecases,however,clusteranalysisisonlyausefulstartingpointforotherpurposes,suchasdatasummarization.Whetherforunderstandingorutility,clusteranalysishaslongplayedanimportantroleinawidevarietyoffields:

psychologyandothersocialsciences,biology,statistics,patternrecognition,informationretrieval,machinelearning,anddatamining.

Therehavebeenmanyapplicationsofclusteranalysistopracticalproblems.Weprovidesomespecificexamples,organizedbywhetherthepurposeoftheclusteringisunderstandingorutility.

ClusteringforUnderstandingClasses,orconceptuallymeaningfulgroupsofobjectsthatsharecommoncharacteristics,playanimportantroleinhowpeopleanalyzeanddescribetheworld.Indeed,humanbeingsareskilledatdividingobjectsintogroups（clustering）andassigningparticularobjectstothesegroups（classification）.Forexample,evenrelativelyyoungchildrencanquicklylabeltheobjectsinaphotographasbuildings,vehicles,people,animals,plants,etc.Inthecontextofunderstandingdata,clustersarepotentialclassesandclusteranalysisisthestudyoftechniquesforautomaticallyfindingclasses.Thefollowingaresomeexamples:

Biology.Biologistshavespentmanyyearscreatingataxonomy（hierarchicalclassification）ofalllivingthings:

kingdom,phylum,class,order,family,genus,andspecies.Thus,itisperhapsnotsurprisingthatmuchoftheearlyworkinclusteranalysissoughttocreateadisciplineofmathematicaltaxonomythatcouldautomaticallyfindsuchclassificationstructures.Morerecently,biologistshaveappliedclusteringtoanalyzethelargeamountsofgeneticinformationthatarenowavailable.Forexample,clusteringhasbeenusedtofindgroupsofgenesthathavesimilarfunctions.

•InformationRetrieval.TheWorldWideWebconsistsofbillionsofWebpages,andtheresultsofaquerytoasearchenginecanreturnthousandsofpages.Clusteringcanbeusedtogroupthesesearchresultsintoasmallnumberofclusters,eachofwhichcapturesaparticularaspectofthequery.Forinstance,aqueryof“movie”mightreturnWebpagesgroupedintocategoriessuchasreviews,trailers,stars,andtheaters.Eachcategory（cluster）canbebrokenintosubcategories（sub-clusters）,producingahierarchicalstructurethatfurtherassistsauser’sexplorationofthequeryresults.

•Climate.UnderstandingtheEarth’sclimaterequiresfindingpatternsintheatmosphereandocean.Tothatend,clusteranalysishasbeenappliedtofindpatternsintheatmosphericpressureofpolarregionsandareasoftheoceanthathaveasignificantimpactonlandclimate.

•PsychologyandMedicine.Anillnessorconditionfrequentlyhasanumberofvariations,andclusteranalysiscanbeusedtoidentifythesedifferentsubcategories.Forexample,clusteringhasbeenusedtoidentifydifferenttypesofdepression.Clusteranalysiscanalsobeusedtodetectpatternsinthespatialortemporaldistributionofadisease.

•Business.Businessescollectlargeamountsofinformationoncurrentandpotentialcustomers.Clusteringcanbeusedtosegmentcustomersintoasmallnumberofgroupsforadditionalanalysisandmarketingactivities.

ClusteringforUtility：

Clusteranalysisprovidesanabstractionfromindividualdataobjectstotheclustersinwhichthosedataobjectsreside.Additionally,someclusteringtechniquescharacterizeeachclusterintermsofaclusterprototype;i.e.,adataobjectthatisrepresentativeoftheotherobjectsinthecluster.Theseclusterprototypescanbeusedasthebasisforanumberofdataanalysisordataprocessingtechniques.Therefore,inthecontextofutility,clusteranalysisisthestudyoftechniquesforfindingthemostrepresentativeclusterprototypes.

•Summarization.Manydataanalysistechniques,suchasregressionorPCA,haveatimeorspacecomplexityofO（m2）orhigher（wheremisthenumberofobjects）,andthus,arenotpracticalforlargedatasets.However,insteadofapplyingthealgorithmtotheentiredataset,itcanbeappliedtoareduceddatasetconsistingonlyofclusterprototypes.Dependingonthetypeofanalysis,thenumberofprototypes,andtheaccuracywithwhichtheprototypesrepresentthedata,theresultscanbecomparabletothosethatwouldhavebeenobta