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Artificial

Intelligence Methodology Systems and Applications 16th International Conference AIMSA 2014

Varna Bulgaria September 11 13 2014 Proceedings 1st Edition Gennady Agre

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Gennady Agre Pascal Hitzler

Adila A. Krisnadhi Sergei O. Kuznetsov (Eds.)

Artificial Intelligence: Methodology, Systems, and Applications

16th International Conference, AIMSA 2014 Varna, Bulgaria, September 11–13, 2014

Proceedings

LectureNotesinArtificialIntelligence8722

SubseriesofLectureNotesinComputerScience

LNAISeriesEditors

RandyGoebel UniversityofAlberta,Edmonton,Canada

YuzuruTanaka

HokkaidoUniversity,Sapporo,Japan

WolfgangWahlster DFKIandSaarlandUniversity,Saarbrücken,Germany

LNAIFoundingSeriesEditor

JoergSiekmann

DFKIandSaarlandUniversity,Saarbrücken,Germany

GennadyAgrePascalHitzler

AdilaA.KrisnadhiSergeiO.Kuznetsov(Eds.)

ArtificialIntelligence: Methodology,Systems, andApplications

16thInternationalConference,AIMSA2014 Varna,Bulgaria,September11-13,2014

Proceedings

VolumeEditors

GennadyAgre

BulgarianAcademyofSciences

InstituteofInformationandCommunicationTechnologies

Sofia,Bulgaria

E-mail:agre@iinf.bas.bg

PascalHitzler

WrightStateUniversity Dayton,OH,USA

E-mail:pascal.hitzler@wright.edu

AdilaA.Krisnadhi

WrightStateUniversity,Dayton,OH,USA and UniversityofIndonesia,Depok,Indonesia E-mail:krisnadhi@gmail.com

SergeiO.Kuznetsov NationalResearchUniversity HigherSchoolofEconomics Moscow,Russia

E-mail:skuznetsov@hse.ru

ISSN0302-9743e-ISSN1611-3349

ISBN978-3-319-10553-6e-ISBN978-3-319-10554-3 DOI10.1007/978-3-319-10554-3

SpringerChamHeidelbergNewYorkDordrechtLondon

LibraryofCongressControlNumber:2014946289

LNCSSublibrary:SL7–ArtificialIntelligence

©SpringerInternationalPublishingSwitzerland2014

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Preface

AIMSA2014wasthe16thinabiennialseriesofAIconferencesthathavebeen heldinBulgariasince1984.TheseriesbeganasaforumforscientistsfromEasternEuropetoexchangeideaswithresearchersfromotherpartsoftheworld,at atimewhensuchmeetingsweredifficulttoarrangeandattend.Theconference hasthrivedfor30years,andnowfunctionsasaplacewhereAIresearchersfrom allovertheworldcanmeetandpresenttheirresearch.

AIMSAcontinuestoattractsubmissionsfromallovertheworld,withsubmissionsfrom27countries.Therangeoftopicsisalmostequallybroad,from traditionalareassuchascomputervisionandnaturallanguageprocessingto emergingareassuchasminingthebehaviorofWeb-basedcommunities.Itis goodtoknowthatthedisciplineisstillbroadeningtherangeofareasthatit includesatthesametimeascementingtheworkthathasalreadybeendonein itsvariousestablishedsubfields.

TheProgramCommitteeselectedjustover30%ofthesubmissionsaslong papers,andfurtheraccepted15shortpapersforpresentationattheconference.WeareextremelygratefultotheProgramCommitteeandtheadditional reviewers,whoreviewedthesubmissionsthoroughly,fairlyandveryquickly.

Specialthanksgotoourinvitedspeakers,BernhardGanter(TUDresden), BorisG.Mirkin(HigherSchoolofEconomics,Moscow)andDiegoCalvanese (FreeUniversityofBozen-Bolzano).Theinvitedtalksweregroupedaroundontologydesignandapplication,whetherusingclusteringandbiclusteringapproaches(B.G.Mirkin),formalconceptanalysis,abranchofappliedlattice theory(B.Ganter),orbeingconcernedwithontology-baseddataaccess(D. Calvanese).

Finally,specialthanksgototheAComInproject(AdvancedComputingfor Innovation,FP7Capacitygrant316087)forthegeneroussupportforAIMSA 2014,aswellasBulgarianArtificialIntelligenceAssociation(BAIA),andInstituteofInformationandCommunicationTechnologiesatBulgarianAcademyof Sciences(IICT-BAS)assponsoringinstitutionsofAIMSA2014.

June2014GennadyAgre PascalHitzler AdilaA.Krisnadhi SergeiKuznetsov

Organization

ProgramCommittee

GennadyAgreInstituteofInformationTechnologies, BulgarianAcademyofSciences,Bulgaria GaliaAngelovaInstituteforParallelProcessing,Bulgarian AcademyofSciences,Bulgaria GrigorisAntoniouUniversityofHuddersfield,UK S¨orenAuerUniversit¨atLeipzig,Germany SebastianBaderMMIS,ComputerScience,RostockUniversity, Germany

RomanBartakCharlesUniversityinPrague,CzechRepublic ChristophBeierleUniversityofHagen,Germany MeghynBienvenuCNRS,Universit´eParis-Sud,France DiegoCalvaneseKRDBResearchCentre,FreeUniversity ofBozen-Bolzano,Italy VirginioCantoniUniversit`adiPavia,Italy StefanoA.CerriLIRMM:UniversityofMontpellierandCNRS, France

MichelleCheathamWrightStateUniversity,USA DavideCiucciUniversityofMilan,Italy ChrisCornelisGhentUniversity,Belgium MadalinaCroitoruLIRMM,UniversityMontpellierII,France IsabelCruzUniversityofIllinoisatChicago,USA ClaudiaD’AmatoUniversit`adiBari,Italy ArturD’AvilaGarcezCityUniversityLondon,UK DarinaDichevaWinston-SalemStateUniversity,USA YingDingIndianaUniversity,USA DanailDochevInstituteofInformationTechnologies, BulgarianAcademyofSciences,Bulgaria StefanEdelkampUniversityofBremen,Germany EsraErdemSabanciUniversity,Turkey FlorianaEspositoUniversit`adiBari,Italy WilliamMichaelFitzgeraldEMCInformationSystemsInternational, Ireland

MiguelA.Guti´errez-NaranjoUniversityofSevilla,Spain BarbaraHammerInstituteofComputerScience,Clausthal UniversityofTechnology,Germany

PascalHitzlerWrightStateUniversity,USA DmitryIgnatovHigherSchoolofEconomics,Moscow,Russia

GrigoryKabatyanskyInstituteforInformationTransmission Problems,RussianAcademyofSciences, Russia

MehdyKaytoueLIRIS-CNRS,andINSALyon,France

GabrieleKern-IsbernerTechnicalUniversityofDortmund,Germany

KristianKerstingTechnicalUniversityofDortmund,Fraunhofer IAIS,Germany

VladimirKhoroshevskyComputingCenterofRussianAcademyof Science,Moscow,Russia

MatthiasKnorrCENTRIA,UniversidadeNovadeLisboa, Portugal

PetiaKoprinkova-HristovaBulgarianAcademyofSciences,Bulgaria

IrenaKoprinskaTheUniversityofSydney,Australia

PetarKormushevIITGenoa,Italy

AdilaA.KrisnadhiWrightStateUniversity,USA,andFacultyof ComputerScience,UniversitasIndonesia, Indonesia

Kai-UweKuehnbergerUniversityofOsnabr¨uck,InstituteofCognitive Science,Germany

OliverKutzUniversityofBremen,SFB/TR8Spatial Cognition,Germany

SergeiO.KuznetsovNationalResearchUniversityHigherSchool ofEconomics,Moscow,Russia

LuisLambFederalUniversityofRioGrandedoSul,Brazil

EvelinaLammaENDIF,UniversityofFerrara,Italy

JoohyungLeeArizonaStateUniversity,USA

YueMaTechnicalUniversityofDresden,Germany

FrederickMaierFloridaInstituteforHumanandMachine Cognition,USA

RiichiroMizoguchiJapanAdvancedInstituteofScienceand Technology,Japan

ReinhardMuskensTilburgCenterforLogicandPhilosophyof Science,TheNetherlands

KazumiNakamatsuUniversityofHyogo,Japan

AmedeoNapoliLORIA,CNRS-InriaNancy,andUniversity ofLorraine,France

SergeiObiedkovHigherSchoolofEconomics,Moscow,Russia

ManuelOjeda-AciegoDepartmentofAppliedMathematics, UniversityofMalaga,Spain

GuilinQiSoutheastUniversity,China

AllanRamsaySchoolofComputerScience,Universityof Manchester,UK

ChedyRa¨ıssiLORIA,CNRS-InriaNancy,France

IoannisRefanidisDepartmentofAppliedInformatics,University ofMacedonia,Greece UteSchmidUniversityofBamberg,Germany

LucianoSerafiniFondazioneBrunoKessler,Italy DominikSlezakUniversityofWarsaw,Poland UmbertoStracciaISTI-CNR,Italy

HannesStrassLeipzig University,Germany DoinaTatarUniversityBabes-Bolyai,Romania AnnetteTenTeijeVrijeUniversiteitAmsterdam,TheNetherlands DanTufisInstitutuldeCercetaripentruInteligenta Artificiala,AcademiaRomana,Romania PetkoValtchevUQAM,Universit´edeMontr´eal,Canada TulayYildirimYildizTechnicalUniversity,Turkey

AdditionalReviewers

Batsakis,Sotiris Beek,Wouter Bellodi,Elena Borgo,Stefano Cordero,Pablo Fanizzi,Nicola Gavanelli,Marco Gluhchev,Georgi Hu,Yingjie Huan,Gao Kashnitsky,Yury

SponsoringInstitutions

Kriegel,Francesco Meri¸cli,Tekin Minervini,Pasquale Mutharaju,Raghava Nakov,Preslav Osenova,Petya Papantoniou,Agissilaos Redavid,Domenico Rizzo,Giuseppe Schwarzentruber,Fran¸cois vanDelden,Andr´ e

BulgarianArtificialIntelligenceAssociation(BAIA) InstituteofInformationandCommunicationTechnologies atBulgarianAcademyofSciences(IICT-BAS)

KeynotePresentationAbstracts

ScalableEnd-UserAccesstoBigData

FreeUniversityofBozen-Bolzano,Italy

KeynoteAbstract

Ontologiesallowonetodescribecomplexdomainsatahighlevelofabstraction, providingend-userswithanintegratedcoherentviewoverdatasourcesthat maintaintheinformationofinterest.Inaddition,ontologiesprovidemechanisms forperformingautomatedinferenceoverdatatakingintoaccountdomainknowledge,thussupportingavarietyofdatamanagementtasks.Ontology-basedData Access(OBDA)isarecentparadigmconcernedwithprovidingaccesstodata sourcesthroughamediatingontology,whichhasgainedincreasedattentionboth fromtheknowledgerepresentationandfromthedatabasecommunities.OBDA posessignificantchallengesinthecontextofaccessinglargevolumesofdata withacomplexstructureandhighdinamicity.Itthusrequiresnotonlycarefully tailoredlanguagesforexpressingtheontologyandthemappingtothedata, butalsosuitablyoptimizedalgorithmsforefficientlyprocessingqueriesoverthe ontologybyaccessingtheunderlyingdatasources.Inthistalkwepresentthe foundationsofOBDArelyingonlightweightontologylanguages,anddiscuss noveltheoreticalandpracticalresultsforOBDAthatarecurrentlyunderdevelopmentinthecontextoftheFP7IPprojectOptique.Theseresultsmakeit possibletoscaletheapproachsoastocopewiththechallengesthatarisein realworldscenarios,e.g.,thoseoftwolargeEuropeancompaniesthatprovide use-casesfortheOptiqueproject.

AbouttheSpeaker

DiegoCalvaneseisaprofessorattheKRDBResearchCentrefor KnowledgeandData,FreeUniversityofBozen-Bolzano,Italy.His researchinterestsincludeformalismsforknowledgerepresentation andreasoning,ontologylanguages,descriptionlogics,conceptualdata modelling,dataintegration,graphdatamanagement,data-awareprocessverification,andservicemodellingandsynthesis.Heisactivelyinvolvedin severalnationalandinternationalresearchprojectsintheaboveareas,andhe istheauthorofmorethan250refereedpublications,includingonesinthemost prestigiousinternationaljournalsandconferencesinDatabasesandArtificial Intelligence.HeisoneoftheeditorsoftheDescriptionLogicHandbook.In 2012–2013hehasbeenavisitingresearcherattheTechnicalUniversityofViennaasPauliFellowofthe“WolfgangPauliInstitute”.Hewillbetheprogram chairofPODS2015.

FormalConceptsforLearningandEducation

KeynoteAbstract

FormalConceptAnalysishasanelaborateanddeepmathematicalfoundation, whichdoesnotrelyonnumericaldata.Itis,sotospeak,fiercequalitativemathematics,thatbuildsonthealgebraictheoryoflatticesandorderedsets.Since itsemergenceinthe1980s,notonlythemathematicaltheoryisnowmature, butalsoavarietyofalgorithmsandofpracticalapplicationsindifferentareas. Conceptualhierarchiesplayarolee.g.,inclassification,inreasoningaboutontologies,inknowledgeacquisitionandthetheoryoflearning.FormalConcept Analysisprovidesnotonlyasolidmathematicaltheoryandeffectivealgorithms; italsooffersexpressivegraphics,whichcansupportthecommunicationofcomplexissues.

InourlecturewegiveanintroductiontothebasicideasandrecentdevelopmentsofFormalConceptAnalysis,amathematicaltheoryofconceptsand concepthierarchiesandthendemonstratethepotentialbenefitsandapplicationsofthismethodwithexamples.Wewillalsoreviewsomerecentapplication methodsthatarecurrentlybeingworkedout.Inparticularwewillpresentresults ona“methodologyoflearningassignments”andon“conceptualexploration”.

AbouttheSpeaker

BernhardGanterisapioneerofformalconceptanalysis.Hereceived hisPhDin1974fromtheUniversityofDarmstadt,Germany,and becameProfessorin1978.Currently,heisaProfessorofMathematicsandtheDeanofScienceattheTechnicalUniversityofDresden, Germany.Hisresearchinterestsareindiscretemathematics,universal algebra,latticetheory,andformalconceptanalysis.Heisaco-authorofthefirst textbookandeditorofseveralvolumesonformalconceptanalysis.

OntologyasaToolforAutomatedInterpretation

NationalResearchUniversity,HigherSchoolofEconomics, Moscow,Russia

KeynoteAbstract

Inthebeginning,Iamgoingtooutline,in-brief,thecurrentperiodofdevelopmentsintheartificialintelligenceresearch.Thisisofsynthesis,incontrast tothesequenceofpreviousperiods(romanticism,deduction,andinduction). Threemoreorlessmaturedontologies,andtheiruse,willbereviewed:ACM CCS,SNOMEDCTandGO.Thepopularstrategyofinterpretationofsetsof finergranularityviatheso-calledoverrepresentedconceptswillbementioned.A methodforgeneralizationandinterpretationoffuzzy/crispquerysetsbyparsimoniouslyliftingthemtohigherranksofthehierarchywillbepresented.Its currentandpotentialapplicationswillbediscussed.

AbouttheSpeaker

BorisMirkinholdsaPhDinComputerScienceandDScinSystems AnalysisdegreesfromRussianUniversities.In1991–2010,hetravelledthroughlong-termvisitingappointmentsinFrance,Germany, USA,andateachingappointmentasProfessorofComputerScience, BirkbeckUniversityofLondon,UK(2000–2010).Hedevelopsmethodsforclusteringandinterpretationofcomplexdatawithinthe“datarecovery” perspective.Currentlytheseapproachesarebeingextendedtoautomationof textanalysisproblemsincludingthedevelopmentanduseofhierarchicalontologies.Hislatestpublications:textbook“Coreconceptsindataanalysis”(Springer 2011)andmonograph“Clustering:Adatarecoveryapproach”(Chapmanand Hall/CRCPress,2012).

LongPapers

VeselkaBoeva,LilyanaBoneva,andElenaTsiporkova

DmitryI.Ignatov,ElenaNenova,NataliaKonstantinova,and AndreyV.Konstantinov

IvelinaNikolova,DimitarTcharaktchiev,SvetlaBoytcheva, ZhivkoAngelov,andGaliaAngelova

AQualitativeSpatio-TemporalFrameworkBasedonPointAlgebra

MichaelSioutis,Jean-Fran¸coisCondotta,YakoubSalhi,and BertrandMazure

TrainingDatasetsCollectionandEvaluationofFeatureSelection MethodsforWebContentFiltering 129 RomanSuvorov,IlyaSochenkov,andIlyaTikhomirov

FeatureSelectionbyDistributionsContrasting ....................... 139 VarvaraV.TsurkoandAnatolyI.Michalski

EducationalDataMiningforAnalysisofStudents’Solutions

150 KarelVacul´ık,LeonaNezvalov´a,andLuboˇsPopel´ınsk´ y

ShortPapers

DifferentiationoftheScriptUsingAdjacentLocalBinaryPatterns 162 DarkoBrodi´c, ˇ CedomirA.Maluckov,ZoranN.Milivojevi´c,and IvoR.Draganov

NewTechnologyTrendsWatch:AnApproachandCaseStudy ......... 170 IrinaV.EfimenkoandVladimirF.Khoroshevsky

OptimizationofPolytopicSystemEigenvaluesbySwarmofParticles 178 JacekKabzi´nskiandJaroslawKacerka

Back-PropagationLearningofPartialFunctionalDifferentialEquation withDiscreteTimeDelay 186

TiborKmetandMariaKmetova

DynamicSoundFieldsClusterizationUsingNeuro-FuzzyApproach .... 194 PetiaKoprinkova-HristovaandKirilAlexiev

NeuralClassificationforIntervalInformation ........................ 206 PiotrA.KowalskiandPiotrKulczycki

AlexeyNeznanovandAndrewParinov

IonutCristianParaschiv,MihaiDascalu,andS¸tefanTr˘au¸san-Matu

TowardsManagementofOWL-SEffectsbyMeansofaDLAction FormalismCombinedwithOWLContexts 228 DomenicoRedavid,StefanoFerilli,andFlorianaEsposito

ComputationalExperiencewithPseudoinversion-BasedTrainingof NeuralNetworksUsingRandomProjectionMatrices

LucaRubini,RossellaCancelliere,PatrickGallinari, AndreaGrosso,andAntoninoRaiti

TestCasePrioritizationforNUnitBasedTestPlansinAgile Environment

SohailSarwar,YasirMahmood,ZiaUlQayyum,andImranShafi

PatternStructureProjectionsforLearningDiscourseStructures 254 FedorStrok,BorisGalitsky,DmitryIlvovsky,and SergeiO.Kuznetsov

EstimationMethodforPathPlanningParameterBasedonaModified QPSOAlgorithm ................................................

MyongcholTokgoandRenfuLi

OnModelingFormalismsforAutomatedPlanning

JindˇrichVodr´aˇzkaandRomanBart´ak

FinetuningRandomizedHeuristicSearchfor2DPathPlanning: FindingtheBestInputParametersforR*AlgorithmthroughSeriesof Experiments 278 KonstantinYakovlev,EgorBaskin,andIvanHramoin

AnalysisofStrategiesinAmericanFootballUsingNashEquilibrium .... 286 ArturoYee,ReinaldoRodr´ıguez,andMat´ıasAlvarado

StrategiesforReducingtheComplexityofSymbolicModelsforActivity

KristinaYordanova,MartinNyolt,andThomasKirste

LearningProbabilisticSemanticNetwork ofObject-OrientedActionandActivity

DepartmentofInformationSystemsScience,FacultyofEngineering, SokaUniversity,1-236Tangi,Hachioji,Tokyo192-8577,Japan masayasu.atsumi@gmail.com

Abstract. Thispaperproposesamethodoflearningprobabilisticsemanticnetworkswhichrepresentvisualfeaturesandsemanticfeaturesof object-orientedactionsandtheircontextualactivities.Inthismethod, visualmotionfeatureclassesofactionsandactivitiesarelearnedbyan unsupervisedIncrementalProbabilisticLatentComponentAnalysis(IPLCA)andtheseclassesandtheirsemantictagsintheformofcase tripletsareintegratedintoprobabilisticsemanticnetworkstovisually recognizeandverballyinferactionsinthecontextofactivities.Through experimentsusingvideoclipscapturedwiththeKinectsensor,itisshown thatthemethodcanlearn,recognizeandinferobject-orientedactionsin thecontextofactivities.

Keywords: actionrecognition,activityrecognition,probabilistic learning,semanticnetwork,probabilisticinference.

1Introduction

Itisnecessaryforahumansupportrobottounderstandwhatapersonisdoing ineverydaylivingenvironment.Inhumanmotionineverydaylife,thereisalot ofmotionthatinteractswithobjects,whichisreferredtoasan“object-oriented motion”inthisresearch.Themeaningofan object-orientedmotionisdetermined notonlyamotionitselfbutalsoanobjectwithwhichthemotioninteracts andthisviewcorrespondstoanaffordanceinwhichmotionisdependenton objectperception.Inaddition,eachmotionisperformedinacontextwhich isdefinedbyasequenceofmotionsanda certainmotionfrequentlyoccursin somecontextandrarelyoccursinothercontexts.Forexample,amotionusing aforkisfrequentlyobservedinacontextofeatingmeals.Inthisresearch,each object-orientedmotionisreferredtoasanactionandasequenceofactionsis referredtoasanactivityanditisassumedthatanactivitygivesacontextof anactionandpromotesactionrecognition.Thisassumptionisconsistentwith findingsthatcontextimprovescategoryrecognitionofambiguousobjectsina scene[1]andrequiresanextensiontoactionrecognitionofseveralmethods[2,3] whichincorporatecontextintoobjectca tegorization.Thoughobject-oriented actionsandactivitiescanbeclustered intomotionclassesaccordingtovisual motionfeaturesandtheirsemanticfeaturescanbelabeledbyusingmotion

G.Agreetal.(Eds.):AIMSA2014,LNAI8722,pp.1–12,2014. c SpringerInternationalPublishingSwitzerland2014

labelsandtheirtargetlabels,motionclassesandtheirlabelsdonothaveone-toonecorrespondence.Therefore,inthisresearch,motionclassesarelabeledwith targetsynsetsandmotionsynsetsofcasetripletsinaformof“ targetsynset, case,motionsynset ”andmotionclassesandsynsetsareprobabilisticallylinked inprobabilisticsemanticnetworksofactionsandactivities,whereasynsetis asynonymoussetoftheWordNet[4]whichrepresentsaprimitivesemantic feature.Inaddition,contextualrelationshipbetweenactionsandactivitiesis acquiredasco-occurrencebetweenthem.

Thispaperproposesamethodoflearningprobabilisticsemanticnetworkswhich representvisualfeaturesandsemanticfeaturesofobject-orientedactionsandtheir contextualactivities.Italsoprovidesaprobabilisticrecognitionandinference methodofactionsandactivitiesbasedonprobabilisticsemanticnetworks.The maincharacteristicsoftheproposedmethodarethefollowing:(1)visualmotion featureclassesofactionsandactivitiesarelearnedbyanunsupervised“IncrementalProbabilisticLatentComponentAnalysis(I-PLCA)”[5],(2)visualfeature classesofmotionandsynsetsofcasetripletsareintegratedintoprobabilisticsemanticnetworkstovisuallyrecognizeandverballyinferactionsandactivities,and (3)actionsareinferredinthecontextofa ctivitiesthroughacquiredco-occurrence betweenthem.

Asforrelatedwork,Kitanietal.[6]proposedacategorizationmethodof primitiveactionsinvideobyleveragingrelatedobjectsandrelevantbackground featuresascontext.Yaoetal.[7]proposedamutualcontextmodeltojointly recognizeobjectsandhumanposesinstillimagesofhuman-objectinteraction. Alsoin[8],theyproposedamodeltoidentifydifferentobjectfunctionalitiesby estimatinghumanposesanddetectingobjectsinstillimagesofdifferenttypesof human-objectinteraction.Onedifferencebetweenourmethodandtheseexisting methodsisthatourmethodnotonlyusesanactionanditstargetobjectas mutualcontextbutalsousesactivitiesas contextofactions.Anotherdifferenceis thatourmethodprobabilisticallyinfersactionsandactivitiesbyusingdifferent semanticfeatureslinkedwithdifferentvisualmotionfeaturesinprobabilistic semanticnetworks.

2ProposedMethod

2.1Overview

Humanmotioniscapturedasatemporalsequenceofthree-dimensionaljoint coordinatesofahumanskeleton,whichcanbecapturedwiththeMicrosoft Kinectsensor.Sincethisresearchfocusesonobject-orientedmotionsofhands,a temporalsequenceofthree-dimensionalcoordinatesofbothhandjointsrelative toashouldercenterjointarecomputedfromhumanskeletondata.

Amotionfeatureofbothhandsiscomputedfromatemporalsequenceof relativethree-dimensionalcoordinatesofbothhandjointsbythefollowingprocedure.First,relativethree-dimensionalcoordinatesofbothhandjointsare spatially-quantizedatacertainintervalandatemporalsequenceofquantizedcoordinatesandtheirdisplacementareobtainedasamotionrepresentation.Next,

actionsaremanuallysegmentedfromatemporalsequenceofquantizedcoordinatesandtheirdisplacementandthey aresemanticallyannotatedwithcase triplets.Anactivityisalsosegmentedasasequenceofactionsandissemanticallyannotatedwithacasetriplet.Then,foratemporalsequenceofquantized coordinatesandtheirdisplacementofanaction,amotionfeatureoftheactioniscomputedasamotionhistogrambyfirstlydividingthespacearound ashouldercenterintomodestly-sizedregions,secondlycalculatingadisplacementhistogramofeachregionandlastlycombiningthemintoonehistogram.A motionhistogramofanactivityisalsocalculatedinthesameway.

Aprobabilisticsemanticnetworkofactionsislearnedfromasetoftheirmotionhistogramswithcasetriplets.Firstofall,asetofactionclassesisgenerated fromasetofmotionhistogramsbytheprobabilisticclusteringmethodI-PLCA. Here,anactionclassrepresentsamotio nfeatureoftheaction.Then,aprobabilisticsemanticnetworkisgeneratedasanetworkwhosenodesconsistofaction classesandsynsetsofcasetripletsandarelinkedbyjointprobabilitiesofthese classesandsynsets.Aprobabilisticsemanticnetworkofactivitiesisalsolearned fromasetoftheirmotionhistogramswithcasetripletsasanetworkwhose nodesconsistofactivityclassesandsynsetsofcasetripletsandarelinkedby jointprobabilitiesoftheseclassesandsynsets.Here,anactivityclassisgenerated bytheI-PLCAandrepresentsamotionfeatureoftheactivity.Forprobabilistic semanticnetworksofactionsandactivities,co-occurrencebetweenanactionand anactivityisobtainedbycalculatingpointwisemutualinformationoftheircase triplets.Apairofprobabilisticsemanticnetworksofactionsandactivitieswith co-occurrencebetweenthemisreferredtoastheACTNETinthispaper.Fig.1 showsanexampleofanACTNET.

Forasequenceofmotionhistogramsofactions,actionsandanactivityaresequentiallyguessedbyrecognizingactionandactivityclassesandinferringsynsets ofcasetripletsofthem.Firstofall,anactionclassisrecognizedwiththedegree ofconfidenceforamotionhistogramofeachactionandatthesametimean activityclassisrecognizedwiththedegreeofconfidenceforasumofmotion

Probabilistic semantic network of activities

p(sn0, c0)

Target synset: sn0[meal], p(sn0)

Probabilistic semantic network of actions

Motion synset: sv1[eat], p(sv1)

p(sv1, c1)

Motion class: c 0 p(c0), {p(fn|c0)}, {p(ma|c0)} p(sn0, c 0 , sv0)

O, p(sn0, sv0)

Co-occurrence: ω(sni,svj,sn0,sv0), i=1,2, j=1,2,3

Motion synset: sv3[take], p(sv3)

p(sv0, c0)

Motion synset: sv0[eat], p(sv0)

Motion synset: sv2[drink], p(sv2)

I O p(sn1, sv3) O I p(sn2, sv3) p(sn1, sv1) p(sn2, sv2)

Target synset: sn1[fork], p(sn1)

Target synset: sn2[teacup], p(sn2)

p(sv2, c2) p(sv3, c3) p(sn1, c1) p(sn2, c2) p(sn1, c3) p(sn2, c3)

Motion class: c 1 p(c1), {p(fn|c1)}, {p(ma|c1)} p(sn1, c 1 , sv1)

Motion class: c 3 p(c3), {p(fn|c3)}, {p(ma|c3)} p(sni, c 3 , sv3), i=1,2

Motion class: c 2 p(c2), {p(fn|c2)}, {p(ma|c2)} p(sn2, c 2 , sv2)

Fig.1. AnexampleofanACTNET(Symbolsinthefigureareexplainedinthetext.)

histogramsofanactionsequence.Then,synsetsofcasetripletsoftheactions andtheactivityareinferredfromtheseclassesandco-occurrencebetweenthem onprobabilisticsemanticnetworks.

2.2MotionFeatureofActionandActivity

Let pl =(pl x ,pl y ,pl z )and pr =(pr x ,pr y ,pr z

)berelativequantized three-dimensional coordinatesofleftandrighthandsandlet dl =(dl x ,dl y ,dl z )and dr =(dr x ,dr y ,dr z ) betheirdisplacementrespectively.Here, l representsalefthand, r represents arighthandandthedisplacementisgivenbythedifferenceofquantizedcoordinatesbetweentwosuccessiveframes.Let sn [wn ],r,sv [wv ] beacasetriplet whichisusedtoannotateatemporalsequenceofquantizedcoordinatesandtheir displacementofanactionoranactivity,where wn isanounwhichrepresentsa targetofmotionand sn isitssynset, wv isaverbwhichrepresentsmotionand sv isitssynset,and r isacasenotation.Here,asynsetisgivenbyasynonymous setoftheWordNet[4]andacaseiscurrentlyoneoftheobjectivecase(O ), theinstrumentalcase(I )andthelocativecase(L[at| inside| around| above| below | beyond| from| to]).Foratemporalsequenceofquantizedcoordinates andtheirdisplacementofanaction,acasetripletofanactivitywhichincludes theactionisalsogiveninadditiontoacasetripletoftheaction.Then,fora motion m = {((pl ,dl ), (pr ,dr ))t },amotionhistogramisconstructedtorepresent amotionfeatureofbothhandsaroundashouldercenterasfollows.Let B be asetofmodestly-sizedregionswhichisobtainedbydividingthespacearound ashouldercenterandlet |B | bethenumberofregions.Foreachregion b ∈ B , amotionsub-histogramiscomputedforasetofcoordinateanddisplacement data {(pl ,dl )} and {(pr ,dr )} whosecoordinate pl or pr islocatedintheregion b. Amotionsub-histogramhas27binseachbinofwhichcorrespondstowhether displacementispositive,zeroornegativealong x-, y -,and z -axesandiscounted upaccordingtovaluesofdisplacement dl and dr .Amotionhistogram h(m)is constructedasa |B |-plexhistogrambycombiningthesesub-histogramsintoone histogramsothatthesizeof h(m)is27 ×|B |

2.3LearningProbabilisticSemanticNetwork

AnACTNETislearnedthroughgeneratingprobabilisticsemanticnetworks ofactionsandactivitiesfollowedbycalculatingco-occurrencebetweenactions andactivities.Aprobabilisticsemanticnetworkisgeneratedfromasetofmotionhistogramsofactionsoractivitieswiththeircasetriplets.Let h(ma )= [hma (f1 ),...,hma (f|F | )]beamotionhistogramofamotion m withacasetriplet a andlet H = {h(ma )} beasetofmotionhistogramswithcasetriplets.Here, fi ∈ F isabinofahistogramandthesizeofahistogramis |F | =27 ×|B |.A probabilisticsemanticnetworkisobtainedthroughgenerationofmotionclasses byclusteringasetofmotionhistograms H usingI-PLCA[5]andderivationof aprobabilisticnetworkwhosenodesconsistofmotionclassesandsynsetsofcase tripletsandtheyarelinkedbyjointprobabilitiesoftheseclassesandsynsets.

Theproblemtobesolvedforgeneratingmotionclassesisestimatingprobabilities p(ma ,fn )= c p(c)p(ma |c)p(fn |c),namely,aclassprobabilitydistribution {p(c)|c ∈ C },instanceprobabilitydistributions {p(ma |c)|ma ∈ M × A,c ∈ C }, probabilitydistributionsofclassfeatures {p(fn |c)|fn ∈ F,c ∈ C },andthenumberofclasses |C | thatmaximizethefollowinglog-likelihood

= ma fn

ma (fn )log p(ma ,fn )(1)

forasetofmotionhistogram H = {h(ma )},where C isasetofmotionclasses, M isasetofmotions, A isasetofcasetripletsand ma isamotion m witha casetriplet a,thatis,aninstanceofanactionoranactivity.TheseprobabilitydistributionsandthenumberofclassesareestimatedbythetemperedEM algorithmwithsubsequentclassdivision.Theprocessstartswithoneorafew classes,pausesateverycertainnumber ofEMiterationslessthananupperlimit andcalculatesthefollowingdispersionindex

for ∀c ∈ C .Thenaclasswhosedispersionindextakesthemaximumvalue amongallclassesisdividedintotwoclasses.Let c∗ beasourceclasstobe dividedandlet c1 and c2 betargetclassesafterdivision.Then,foramotion m∗ a =argmaxma {p(ma |c∗ )} whichhasthemaximuminstanceprobabilityand itsmotionhistogram h

)],oneclass c1 issetby specifyingaprobabilitydistributionofaclassfeature,aninstanceprobability distributionandaclassprobabilityas

respectivelywhere κ isapositivecorrectioncoefficient.Anotherclass c2 issetby specifyingaprobabilitydistributionofaclassfeature {p(fn |c2 )|fn ∈ F } atrandom,aninstanceprobabilitydistribution {p(ma |c2 )} as0for m∗ a andanequal probability 1 |M |−1 for ∀ma (

= m∗ a ),andaclassprobabilityas p

p

∗ ) 2 . Thisclassdivisionprocessiscontinueduntildispersionindexesorclassprobabilitiesofalltheclassesbecomelessthangiventhresholds.Thetemperature coefficientofthetemperedEMissetto1.0untilthenumberofclassesisfixed andafterthatitisgraduallydecreasedaccordingtoagivenscheduleuntilthe EMalgorithmconvergesandalltheprobabilitydistributionsaredetermined.

Aprobabilisticsemanticnetworkisderivedfromaclassprobabilitydistribution {p(c)|c ∈ C } andinstanceprobabilitydistributions {p(ma |c)|ma ∈ M × A,c ∈ C } associatedwithmotionclasses. Thenetworknodesconsistofmotionclassnodesandsynsetnodes.Asynsetnodeisderivedfromatargetsynset sn oramotionsynset sv ofacasetriplet sn [wn ],r,sv [wv ] whichisgivenbyan instance ma ofanactionoranactivitywhere a = sn [wn ],r,sv [wv ] .Amotion classnodeisderivedfromamotionclass c ∈ C andhasaclassprobability p(c), aprobabilitydistributionofaclassfeature {p(fn |c)|fn ∈ F },aninstanceprobabilitydistribution {p(ma |c)|ma ∈ M × A} andasetofjointprobabilitieseach ofwhichisajointprobabilitywithatargetsynset sn andamotionsynset sv of acasetripletthatannotatestheclass c andisgivenbytheexpression(6)

p(sn ,c,sv )= p(c) ×

(ma |c)(6)

]

where ∗ representsanywordoranycase.Thenetworklinkbetweentwonodes ofamotionclass c andatargetsynset sn hasajointprobability p(sn ,c).The networklinkbetweentwonodesofamotionclass c andamotionsynset sv hasa jointprobability p(sv ,c).Thenetworklinkbetweentwonodesofatargetsynset sn andamotionsynset sv hasajointprobability p(sn ,sv ).Thenetworknodes ofatargetsynset sn andamotionsynset sv haveprobabilities p(sn )and p(sv ) respectively.Theseprobabilitiesarecomputedbytheexpressions(7).

p(sn ,c)= sv p(sn ,c,sv ),p(sv ,c)= sn p(sn ,c,sv ) p(sn ,sv )= c p(sn ,c,sv ) p(sn )= c p(sn ,c),p(sv )= c p(sv ,c)

Inaddition,anoun wn ofatargetsynset sn andaverb wv ofamotionsynset sv aresettothetargetsynsetnodeandthemotionsynsetnoderespectively. Co-occurrencebetweenactionsandactivitiesiscomputedbetweenapairof atargetsynset sn andamotionsynset sv ofanactionandapairofatargetsynset s0 n andamotionsynset s0 v ofanactivitywhentheactionhasa casetriplet sn [wn ],r,sv [wn ] andisincludedintheactivitywithacasetriplet s0 n [w 0 n ],r 0 ,s0 v [w 0 n ] .Let p(sn ,sv )beajointprobabilityofatargetsynset sn and amotionsynset sv ofanactionandlet p(s0 n ,s0 v )beajointprobabilityofatarget synset s0 n andamotionsynset s0 v ofanactivity.Then,co-occurrencebetween themisdefinedbytheexpression(8)

(sn ,sv ,s 0 n ,s 0 v )=log

(sn ,sv ,s0 n ,s0 v )

(sn ,sv )p(s0 n ,s0 v ) (8)

whereajointprobability p(sn ,sv ,s0 n ,s0 v )iscalculatedfromactioninstancesaccordingtotheexpression(9) p(sn ,sv ,s 0 n ,s 0 v )= c p(c) × a= sn [∗],∗,sv [∗] @ s0 n [∗],

(ma |c) (9) where a = sn [∗], ∗,sv [∗] @ s0 n [∗], ∗,s0 v [∗] meansthatanaction ma hasacase tripletwhichmatchesapattern sn [∗], ∗,sv [∗] anditscontextualactivityhasa casetripletwhichmatchesapattern s0 n [∗], ∗,s0 v [∗] .

2.4RecognitionandInferenceofActionandActivity

AnACTNETisusedtorecognizeandinferasequenceofactionsandanactivity foragivensequenceofmotionhistogramsofactions.Firstofall,foreachmotion histogram,amotionclassofanactionisrecognizedwiththedegreeofconfidence andatthesametimeamotionclassofanactivityisrecognizedwiththedegreeof confidenceforasequentialsumofmotionhistogramsofanactionhistory.Then, synsetsofcasetripletsoftheactionsandthecontextualactivityareinferred fromtheseclassesandco-occurrencebetweenactionsandactivities.

Motionclassesofanactionandanactivityarerespectivelyrecognizedfora motionhistogramandasequentialsumofmotionhistogramsofanactionhistory. Let h(m)=[h

)]beamotionhistogramorasumofmotion histogramsandlet

| )]beadistributionofit.Then, amotionclassisobtainedthroughcalculatingsimilaritybetweenprobability distributionsofclassfeatures {p(fn |c)|fn ∈ F,c ∈ C } andthedistribution ˆ h(m) bytheexpression(10)andselectingthemostsimilarclassofalltheclasses C .

Thissimilarityprovidesthedegreeofconfidenceofamotionclass. Foraselectedclass,atargetsynsetandamotionsynsetareinferredwiththeir degreesofconfidence.Let c beamotionclassofanactionoranactivityandlet β beitsdegreeofconfidence.Then,atargetsynset sn ,amotionsynset sv anda pairofthemarerespectivelyinferredwiththeirdegreesofconfidence p(sn |c) × β , p(sv |c) × β and p(sn ,sv |c) × β byfollowinglinksfromanodeofthemotionclass c toadjacentsynsetnodesof sn and sv andretrievingprobabilitiesmaintainedin thosenodesandlinksofanACTNET.Whenadditionalinformationabouteither atargetsynsetoramotionsynsetisgiven,amotionsynsetoratargetsynsetis respectivelyinferredwiththedegreeofconfidence p(sv |c,sn ) × β or p(sn |c,sv ) × β onanACTNET.Byintroducingco-occurrenceintheaboveinference,anaction andanactivityareinterdependentlyinferredwiththedegreeofconfidence.Let c and β beamotionclassofanactionanditsdegreeofconfidenceandlet c0 and β 0 beamotionclassofanactivityanditsdegreeofconfidence.Then,apair ofatargetsynset sn andamotionsynset sv oftheactionandapairofatarget synset s0 n andamotionsynset s0 v oftheactivityareinferredwiththedegreeof confidence β (sn ,sv ,s0 n ,s0 v |c,c0 )thatiscalculatedbytheexpression(11)which incorporatesco-occurrencebetweenthem

where λ isaco-occurrencecoefficient.Whenapairofsynsets(s0 n ,s0 v )ofthe activityisfixedto(s∗ n ,s∗ v )byadditionalinformation,apairofsynsets(sn ,sv ) oftheactionisinferredwiththedegreeofconfidence β (sn ,sv ,s∗ n ,s∗ v |c,c0 ).

Table1. Casetripletsforactivitiesandactionsinasmalldataset

Activity

Action

<03383948-n[fork],O,01216670-v[take]> <03383948-n[fork],I,01166351-v[eat]> <03383948-n[fork],O,01494310-v[put]> <07573696-n[meal], <04398044-n[teapot],O,01216670-v[take]>

O, <04398044-n[teapot],I,02070296-v[pour]> 01166351-v[eat]> <04398044-n[teapot],O,01494310-v[put]> <04397452-n[teacup],O,01216670-v[take]> <04397452-n[teacup],I,01170052-v[drink]> <04397452-n[teacup],O,01494310-v[put]> <06415419-n[notebook],O,02311387-v[take-out]> <06415419-n[notebook],O,01346003-v[open]> <03561345-n[illustration], <06415419-n[notebook],O,01291941-v[close]> O, <06415419-n[notebook],O,01308381-v[put-back]> 01684663-v[paint]> <03908204-n[pencil],O,01216670-v[take]> <03908204-n[pencil],I,01684663-v[paint]> <03908204-n[pencil],O,01494310-v[put]>

3Experiments

3.1ExperimentalFramework

Experimentswereconductedtoevaluatelearning,recognitionandinferenceof object-orientedactionsandactivitiesonACTNETsbyusingvideoclipscaptured withtheKinectSensor.Relativethree-dimensionalcoordinatesofbothhands areinterpolatedtoabout30fps andarequantizedatanintervalof1cm.The spacearoundashouldercenterisdividedasfollowsforconstructingamotion histogram.Thefrontandthesideinthevicinityofthebodyarebothdivided into9regionsthesizeofwhichis30cm onaside.Thefrontandthesideoutside oftheseregionsarerespectivelydividedinto9and8majorregionsandtheback ofthebodyiscoveredbyjustoneregion. Asaresult,thenumberofregionsare 36andthesizeofamotionhistogramis972(=27 × 36).

Twodatasetsofvideoclipswerepreparedforexperiments.Oneisasmalldata setwhichisusedtoillustratethebasiccapabilityoftheproposedmethodinthe experiment1andtheotherisalargerdatasetwhichisusedtoevaluatetheperformanceoftheproposedmethodintheexperiment2.Asmalldatasetcontains 2activitieswhichareannotatedbycasetriplets <07573696-n[meal],O,01166351v[eat]> and <03561345-n[illustration],O,01684663-v[paint]>.Theformeractivity“eatingameal”contains3objectsand9object-orientedactionsandthe latteractivity“paintinganillustration”contains2objectsand7object-oriented actions.Thetotalnumberofactionsis16.Table1showscasetripletsforactivitiesandactionsinthisdataset.Fig.2showsexamplesofmotionquantization, thatis,quantizedcoordinatesandtheirdisplacementofbothhandsofsome actionsinthisdataset.Alargedatasetcontains4activities,10objectsand

<04397452-n[teacup],I,01170052-v[drink]>

(((-32,-38,32),(0,0,0)), ((3,-13,28)(0,1,-1)))

(((-29,-37,32),(0,0,0)), ((10,-8,20),(1,0,0)))

<06415419-n[notebook],O,01346003-v[open]>

(((1,-22,30),(1,0,0)), ((14,-35,20),(0,-1,0)))

(((-12,-26,39),(3,0,-1)), ((8,-34,26),(1,-1,-1)))

Fig.2. Examplesofquantizedmotionofbothhandsinactions

Table2. Activitiesandactionsequencesinalargedataset

Activity

Actionsequence <clothes,O,wear> <necktie,O,take>,<necktie,O,tie>,<jacket,O,take> <jacket,O,wear>,<scarf,O,take>,<scarf,O,wind> <meal,O,eat> <fork,O,take>,<fork,I,eat>,<fork,O,put> <teapot,O,pick-up>,<teapot,I,pour>,<teapot,O,put> <teacup,O,pick-up>,<teacup,I,drink>,<teacup,O,put> <desk,O,clean-up> <notebook-computer,O,close>,<mouse,O,put-back> <book,O,close>,<book,O,put-back> <mop,O,take>,<mop,I,wipe-up> <report,O,write> <notebook-computer,O,open>,<book,O,take> <book,O,open>,<book,O,turn>,<teacup,O,pick-up> <teacup,I,drink>,<teacup,O,put> <mouse,O,operate>,<notebook-computer,I,input>

27object-orientedactionsintotal.Table2showstheseactivitiesandobjectorientedactionsequencesintheabbreviatedformwithoutsynsets.Fig.3shows snapshotsofobject-orientedactionsequencesintwoactivitiesinthisdataset.

Theparametersweresetasfollows.IntheI-PLCA,athresholdofthedispersionindexforclassdivisionwas0.1,athresholdoftheclassprobabilityforclass divisionwas0.1forasmalldatasetand0.05foralargedatasetrespectively, andacorrectioncoefficient κ intheexpression(3)was1.0.InthetemperedEM, atemperaturecoefficientwasdecreasedbymultiplyingitby0.95atevery20 iterationsuntilitbecame0 .8.Aco-occurrencecoefficient λ betweenanaction andanactivityintheexpression(11)wassetto0.2.

3.2ExperimentalResults

ThelefttworowsofTable3showsthecompositionofanACTNETwhichwas learnedintheexperiment1usingasmalldataset.Thenumberofclasseswas automaticallydeterminedbytheclassdivisionintheI-PLCA.Fig.1showsa partofthisACTNETandthedetailofanactivitynetworkofthisACTNETis showninFig.4.TheleftrowofTable4showsresultsofrecognitionandinference foractionsequencesusedforlearning. Theclassificationaccuracyofactivities

<clothes,O,wear>

<necktie, <jacket, <jacket, <scarf, <scarf, O,take> O,tie> O,take> O,wear> O,take> O,wind>

<desk,O,clean-up>

<note-pc, <mouse, <book, <book, <mop, <mop, O,close> O,put-back> O,close> O,put-back> O,take> I,wipe-up>

Fig.3. Examplesofactionsequencesinactivities

Table3. ThecompositionofACTNETs

was100%.Theclassificationaccuracyofactionswas81.3%whenactivitieswere usedascontext,whereasitwas75 0%whenactivitieswerenotusedascontext. Whenadditionalinformationaboutobjectlabelswasgiven,theclassification accuracyofactionswasincreasedupto93.8%.

Intheexperiment2usingalargedataset,4videoclipswerepreparedforeach of4activitiesandrecognitionandinferencewereevaluatedforactionsequences through4-foldcrossvalidation.TherighttworowsofTable3showsthecompositionofACTNETsandtherightrowofTable4showsresultsofrecognition andinferenceofactionsandactivities.Theclassificationaccuracyofactivities was93.8%.Theclassificationaccuracyofactionswas62.5%whenactivitieswere usedascontext,whereasitwas53.3%whenactivitieswerenotusedascontext. Whenadditionalinformationaboutobjectlabelswasgiven,theclassification accuracyofactionswithoutandwithcontextualactivitieswasrespectivelyincreasedupto75.8%and83.4%.ThepercentagevaluesinparenthesesinTable4 aretheclassificationaccuracyofthetoptwoguessesofactionsandactivities.

<necktie,

Synset layer

Motion class layer

Motion instance layer

sn1:07573696-n [meal] p(sn1)=0.49

p(sn1,sv1) =0.49

sv1:01166351-v [eat] p(sv1)=0.49 O

c1: p(c1)=0.39, {p(fn|c1)}, p(sn1, c 1 , sv1)=0.38, p(sn2, c 1 , sv2)=0.01

<07573696-n[meal],O,01166351-v[eat]> ma1:sequence, h(ma1):histogram

p(sn2,sv2) =0.51 O

sn2:03561345-n [illustration] p(sn2)=0.51 sv2:01684663-v [paint] p(sv2)=0.51

c2: p(c2)=0.61, {p(fn|c2)}, p(sn2, c 2 , sv2)=0.50, p(sn1, c 2 , sv1)=0.11

<03561345-n[illustration],O,01684663-v[paint]> ma2:sequence, h(ma2):histogram {p(ma|c)} {p(sn, c), p(sv, c)}

Fig.4. AnactivitynetworkofanACTNET

Table4. Resultsofrecognitionandinference

Experiments Experiment1 Experiment2

Classificationaccuracyofactionswithout 75.0% 53.3% contextualactivities (93.8%) (59.2%)

Classificationaccuracyofactionswith 81.3% 62.5% contextualactivities (100%) (76.7%)

Classificationaccuracyofactionswithout 93.8% 75.8% contextualactivities(whenobjectlabelsaregiven) (100%) (85.8%)

Classificationaccuracyofactionswith 93.8% 83.4% contextualactivities(whenobjectlabelsaregiven) (100%) (96.7%)

4DiscussionandConcludingRemarks

Indatasetsofexperiments,therearethesameactionsfordifferentobjectsand alsodifferentactionswithsimilarmotion,andthesemakeitdifficulttorecognize object-orientedactions.Intheexperiment2,classificationaccuracyismainlydecreasedduetofalserecognitionof5actions <notebook-computer,O, close>, <mouse,O,put-back>, <book,O,close>, <mop,O,take> and <teacup,O, pick-up>,whichsuffertheabovedifficultyandalsohaveinsufficientmotionfeaturessincetheseactionsareperformed inashorttimeonadeskandskeletonextractionoftheKinectsensorisnotaccurateagainstthecrowdedbackgroundon thedesk.Inaddition,inthedatasetofexp eriment2,therearedifferentactivities whichcontainsthesameactionsandjustonefalserecognitionofactivitieswasoccurredononeoftheseactivities.Asreferentialevaluation,thoughexperimental settinganddatasetsaredifferent,accuracy ofsimilaractionrecognitionbyexistingmethods[7,8]is48% ∼ 59%andourmethodachievedbetterresults.

Inconclusion,wehaveproposedalearningmethodofaprobabilisticsemanticnetworkACTNETwhichintegratesvisualfeaturesandsemanticfeatures ofobject-orientedactionsandtheircontextualactivitiesandalsoprovideda methodusingtheACTNETwhichvisuallyrecognizeandverballyinferactions

inthecontextofactivities.Throughtwoexperiments,ithasillustratedthat theACTNETcanlearnintegratedprobabilisticstructureofvisualandsemantic featuresofobject-orientedactionsandactivitiesandithasshownthatactivities andactionscanbewellrecognizedandinferredusingtheACTNET,especially actionunderstandingisimprovedusingthecontextofactivitiesandalsoadditionalinformationaboutobjects.

Acknowledgment. ThisworkwassupportedinpartbyGrant-in-AidforScientificResearch(C)No.23500188fromJapanSocietyforPromotionofScience.

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Semantic-AwareExpertPartitioning

VeselkaBoeva1 ,LilyanaBoneva1 ,andElenaTsiporkova2

1 ComputerSystemsandTechnologiesDepartment, TechnicalUniversityofSofia,4000Plovdiv,Bulgaria vboeva@tu-plovdiv.bg, lil2@abv.bg

2 ICT&SoftwareEngineeringGroup,Sirris,1030Brussels,Belgium elena.tsiporkova@sirris.be

Abstract. Inthispaper,wepresentanovelsemantic-awareclustering approachforpartitioningofexpertsrepresentedbylistsofkeywords.A commonsetofalldifferentkeywordsisinitiallyformedbypoolingall thekeywordsofalltheexpertprofiles.Thesemanticdistancebetween eachpairofkeywordsisthencalculatedandthekeywordsarepartitioned byusingaclusteringalgorithm.Eachexpertisfurtherrepresentedby avectorofmembershipdegreesoftheexperttothedifferentclusters ofkeywords.TheEuclideandistancebetweeneachpairofvectorsis finallycalculatedandtheexpertsareclusteredbyapplyingasuitable partitioningalgorithm.

Keywords: expertlocation,expertpartitioning,knowledgemanagement.

1Introduction

Expertiseretrievalisnotsomethingnewintheareaofinformationretrieval. Findingtherightpersoninanorganizationwiththeappropriateskillsand knowledgeisoftencrucialtothesuccessofprojectsbeingundertaken[31].Expertfindersareusuallyintegratedintoorganizationalinformationsystems,such asknowledgemanagementsystems,recommendersystems,andcomputersupportedcollaborativeworksystems,tosupportcollaborationsoncomplextasks [16].Initialapproachesproposetoolsthatrelyonpeopletoself-assesstheir skillsagainstapredefinedsetofkeywords,andoftenemployheuristicsgeneratedmanuallybasedoncurrentworkingpractice[13,36].Laterapproachestry tofindexpertiseinspecifictypesofdocuments,suchase-mails[9,11]orsource code[31].Insteadoffocusingonlyonspecificdocumenttypessystemsthatindexandminepublishedintranetdocumentsassourcesofexpertiseevidenceare discussedin[17].Intherecentyears,researchonidentifyingexpertsfromonline datasourceshasbeengraduallygaininginterest[4,19,23,37,40,43].Forinstance, TsiporkovaandTourw´eproposeaprototypeofasoftwaretoolimplementing anentityresolutionmethodfortopic-centeredexpertidentificationbasedon bottom-upminingofonlinesources[40].Thetoolextractsinformationfrom onlinesourcesinordertobuildarepositoryofexpertprofilestobeusedfor technologyscoutingpurposes.

G.Agreetal.(Eds.):AIMSA2014,LNAI8722,pp.13–24,2014. c SpringerInternationalPublishingSwitzerland2014

Manyscientistswhoworkontheexpertiseretrievalproblemdistinguishtwo informationretrievaltasks:expertfindingandexpertprofiling,whereexpert findingisthetaskoffindingexpertsgivenatopicdescribingtherequiredexpertise[10],andexpertprofilingisthetaskofreturningalistoftopicsthat apersonisknowledgeableabout[3].Forinstance,in[5,10]expertiseretrieval isapproachedasanassociationfindingtaskbetweentopicsandpeople.InBalog’sPhDthesis,theexpertfindingandprofilingtasksareaddressedbythe applicationofprobabilisticgenerativemodels,specificallystatisticallanguage models[5].

Documentclusteringisawidelystudiedproblemwithmanyapplicationssuch asdocumentorganization,browsing,summarization,classification[1,28].Clusteringanalysisisaprocessthatpartitionsasetofobjectsintogroups,orclusters insuchawaythatobjectsfromthesame clusteraresimilarandobjectsfrom differentclustersaredissimilar.Atextdocumentcanberepresentedeitherin theformofbinarydata,whenweusethepresenceorabsenceofawordinthe documentinordertocreateabinaryvector.Amoreenhancedrepresentation wouldincluderefinedweightingmethodsbasedonthefrequenciesoftheindividualwordsinthedocument,e.g.,TF-IDFweighting[35].However,thesparse andhighdimensionalrepresentationof thedifferentdocumentsnecessitatethe designoftext-specificalgorithmsfordocumentrepresentationandprocessing. Manytechniqueshavebeenproposedtooptimizedocumentrepresentationfor improvingtheaccuracyofmatchingadocumentwithaqueryintheinformation retrievaldomain[2,35].Mostofthesetechniquescanalsobeusedtoimprove documentrepresentationforclustering. Moreover,researchershaveappliedtopic modelstoclusterdocuments.Forexample, clusteringperformanceofprobabilisticlatentsemanticanalysis(PLSA)andLatentDirichletAllocation(LDA)has beeninvestigatedin[28].LDAandPLSAareusedtomodelthecorpusand eachtopicistreatedasacluster.Documentsareclusteredbyexaminingtopic proportionvector.

Inthiswork,weareconcernedwiththeproblemofhowtoclusterexpertsinto groupsaccordingtothedegreeoftheirexpertisesimilarity.Theclusterhypothesisfordocumentretrieval statesthatsimilardocumentstendtoberelevantto thesamerequest[21].Inthecontextofexpertiseretrievalthiscanbere-stated thatsimilarpeopletendtobeexpertsonthesametopics.Traditionalclustering approachesassumethatdataobjectstobeclusteredareindependentandofidenticalclass,andareoftenmodelledbyafixed-lengthvectoroffeature/attribute values.Thesimilaritiesamongobjectsareassessedbasedontheattributevalues ofinvolvedobjects.However,thecalculationofexpertisesimilarityisacomplicatedtask,sincetheexpertexpertiseprofilesusuallyconsistofdomain-specific keywordsthatdescribetheirareaofcompetencewithoutanyinformationforthe bestcorrespondencebetweenthedifferentkeywordsoftwocomparedprofiles. ThereforeBoeva etal. proposetomeasurethesimilaritybetweentwoexpertise profilesasthestrengthoftherelations betweenthesemanticconceptsassociated withthekeywordsofthetwocomparedprofiles[7].Inaddition,theyintroduce theconceptofexpert’sexpertisesphereandshowhowthesubjectinquestion

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As we have said, in order to arrive even hypothetically at this result, it is necessary to assume besides a mere capacity for change, other positive and active principles, some of which we may notice. Thus, we must have as the direct productions of nature on this hypothesis, certain monads or rough draughts, the primary rudiments of plants and animals. We must have, in these, a constant tendency to progressive improvement, to the attainment of higher powers and faculties than they possess; which tendency is again perpetually modified and controlled by the force of external circumstances. And in order to account for the simultaneous existence of animals in every stage of this imaginary progress, we must suppose that nature is compelled to be constantly producing those elementary beings, from which all animals are successively developed. 567

I need not stay to point out how extremely arbitrary every part of this scheme is; and how complex its machinery would be, even if it did account for the facts. It may be sufficient to observe, as others have done, 84 that the capacity of change, and of being influenced by external circumstances, such as we really find it in nature, and therefore such as in science we must represent it, is a tendency, not to improve, but to deteriorate. When species are modified by external causes, they usually degenerate, and do not advance. And there is no instance of a species acquiring an entirely new sense, faculty, or organ, in addition to, or in the place of, what it had before.

84 Lyell, B. . c. iv.

Not only, then, is the doctrine of the transmutation of species in itself disproved by the best physiological reasonings, but the additional assumptions which are requisite, to enable its advocates

to apply it to the explanation of the geological and other phenomena of the earth, are altogether gratuitous and fantastical.

Such is the judgment to which we are led by the examination of the discussions which have taken place on this subject. Yet in certain speculations, occasioned by the discovery of the Sivatherium, a new fossil animal from the Sub-Himalaya mountains of India, M. Geoffroy Saint-Hilaire speaks of the belief in the immutability of species as a conviction which is fading away from men’s minds. He speaks too of the termination of the age of Cuvier, “la clôture du siècle de Cuvier,” and of the commencement of a better zoological philosophy. 85 But though he expresses himself with great animation, I do not perceive that he adduces, in support of his peculiar opinions, any arguments in addition to those which he urged during the lifetime of Cuvier And the reader 86 may recollect that the consideration of that controversy led us to very different anticipations from his, respecting the probable future progress of physiology. The discovery of the Sivatherium supplies no particle of proof to the hypothesis, that the existing species of animals are descended from extinct creatures which are specifically distinct: and we cannot act more wisely than in listening to the advice of that eminent naturalist, M. de Blainville. 87 “Against this hypothesis, which, up to the present time, I regard as purely gratuitous, and likely to turn geologists out of the sound and excellent road in which they now are, I willingly raise my voice, with the most absolute conviction of being in the right.”

85 Compte Rendu de l’Acad. des Sc. 1837, No. 3, p. 81.

86 See B. . c. vii.

87 Compte Rendu, 1837, No. 5, p. 168.

568 [2nd Ed.] [The hypothesis of the progressive developement of species has been urged recently, in connexion with the physiological tenet of Tiedemann and De Serres, noticed in B. . c. vii. sect. 3; —namely, that the embryo of the higher forms of animals passes by gradations through those forms which are permanent in inferior animals. Assuming this tenet as exact, it has been maintained that the higher animals which are found in the more recent strata may have been produced by an ulterior development of the lower forms in the embryo state; the circumstances being such as to favor such a developement. But all the best physiologists agree in declaring that such an extraordinary developement of the embryo is inconsistent with physiological possibility. Even if the progression of the embryo in time have a general correspondence with the order of animal forms as more or less perfectly organized (which is true in an extremely incomplete and inexact degree), this correspondence must be considered, not as any indication of causality, but as one of those marks of universal analogy and symmetry which are stamped upon every part of the creation.

Mr. Lyell 88 notices this doctrine of Tiedemann and De Serres; and observes, that though nature presents us with cases of animal forms degraded by incomplete developement, she offers none of forms exalted by extraordinary developement. Mr. Lyell’s own hypothesis of the introduction of new species upon the earth, not having any physiological basis, hardly belongs to this chapter.]

88 Principles, B. . c. iv.

Sect. 5. Question of Creation as related to Science.

B since we reject the production of new species by means of external influence, do we then, it may be asked, accept the other side of the dilemma which we have stated; and admit a series of creations of species, by some power beyond that which we trace in the ordinary course of nature?

To this question, the history and analogy of science, I conceive, teach us to reply as follows: All palætiological sciences, all speculations which attempt to ascend from the present to the remote past, by the chain of causation, do also, by an inevitable consequence, urge us to look for the beginning of the state of things which we thus contemplate; but in none of these cases have men been able, by the aid of science, to arrive at a beginning which is homogeneous with the 569 known course of events The first origin of language, of civilization, of law and government, cannot be clearly made out by reasoning and research; just as little, we may expect, will a knowledge of the origin of the existing and extinct species of plants and animals, be the result of physiological and geological investigation.

But, though philosophers have never yet demonstrated, and perhaps never will be able to demonstrate, what was that primitive state of things in the social and material worlds, from which the progressive state took its first departure; they can still, in all the lines of research to which we have referred, go very far back; determine many of the remote circumstances of the past sequence of events;— ascend to a point which, from our position at least, seems to be near the origin; and exclude many suppositions respecting the origin itself. Whether, by the light of reason alone, men will ever be able to do more than this, it is difficult to say. It is, I think, no irrational opinion, even on grounds of philosophical analogy alone, that in all

those sciences which look back and seek a beginning of things, we may be unable to arrive at a consistent and definite belief, without having recourse to other grounds of truth, as well as to historical research and scientific reasoning. When our thoughts would apprehend steadily the creation of things, we find that we are obliged to summon up other ideas than those which regulate the pursuit of scientific truths; to call in other powers than those to which we refer natural events: it cannot, then, be considered as very surprizing, if, in this part of our inquiry, we are compelled to look for other than the ordinary evidence of science.

Geology, forming one of the palætiological class of sciences, which trace back the history of the earth and its inhabitants on philosophical grounds, is thus associated with a number of other kinds of research, which are concerned about language, law, art, and consequently about the internal faculties of man, his thoughts, his social habits, his conception of right, his love of beauty. Geology being thus brought into the atmosphere of moral and mental speculations, it may be expected that her investigations of the probable past will share an influence common to them; and that she will not be allowed to point to an origin of her own, a merely physical beginning of things; but that, as she approaches towards such a goal, she will be led to see that it is the origin of many trains of events, the point of convergence of many lines. It may be, that instead of being allowed to travel up to this focus of being, we are only able to estimate its place and nature, and 570 to form of it such a judgment as this; that it is not only the source of mere vegetable and animal life, but also of rational and social life, language and arts, law and order; in short, of all the progressive tendencies by which the highest principles of the intellectual and moral world have been

and are developed, as well as of the succession of organic forms, which we find scattered, dead or living, over the earth.

This reflection concerning the natural scientific view of creation, it will be observed, has not been sought for, from a wish to arrive at such conclusions; but it has flowed spontaneously from the manner in which we have had to introduce geology into our classification of the sciences; and this classification was framed from an unbiassed consideration of the general analogies and guiding ideas of the various portions of our knowledge. Such remarks as we have made may on this account be considered more worthy of attention.

But such a train of thought must be pursued with caution. Although it may not be possible to arrive at a right conviction respecting the origin of the world, without having recourse to other than physical considerations, and to other than geological evidence: yet extraneous considerations, and extraneous evidence, respecting the nature of the beginning of things, must never be allowed to influence our physics or our geology. Our geological dynamics, like our astronomical dynamics, may be inadequate to carry us back to an origin of that state of things, of which it explains the progress: but this deficiency must be supplied, not by adding supernatural to natural geological dynamics, but by accepting, in their proper place, the views supplied by a portion of knowledge of a different character and order. If we include in our Theology the speculations to which we have recourse for this purpose, we must exclude from them our Geology. The two sciences may conspire, not by having any part in common: but because, though widely diverse in their lines, both point to a mysterious and invisible origin of the world.

All that which claims our assent on those higher grounds of which theology takes cognizance, must claim such assent as is consistent with those grounds; that is, it must require belief in respect of all that bears upon the highest relations of our being, those on which depend our duties and our hopes. Doctrines of this kind may and must be conveyed and maintained, by means of information concerning the past history of man, and his social and material, as well as moral and spiritual fortunes. He who believes that a Providence has 571 ruled the affairs of mankind, will also believe that a Providence has governed the material world. But any language in which the narrative of this government of the material world can be conveyed, must necessarily be very imperfect and inappropriate; being expressed in terms of those ideas which have been selected by men, in order to describe appearances and relations of created things as they affect one another. In all cases, therefore, where we have to attempt to interpret such a narrative, we must feel that we are extremely liable to err; and most of all, when our interpretation refers to those material objects and operations which are most foreign to the main purpose of a history of providence. If we have to consider a communication containing a view of such a government of the world, imparted to us, as we may suppose, in order to point out the right direction for our feelings of trust, and reverence, and hope, towards the Governor of the world, we may expect that we shall be in no danger of collecting from our authority erroneous notions with regard to the power, and wisdom, and goodness of His government; or with respect to our own place, duties, and prospects, and the history of our race so far as our duties and prospects are concerned. But that we shall rightly understand the detail of all events in the history of man, or of the skies, or of the earth, which are narrated for the purpose of thus giving a right direction to our

minds, is by no means equally certain; and I do not think it would be too much to say, that an immunity from perplexity and error, in such matters, is, on general grounds, very improbable. It cannot then surprise us to find, that parts of such narrations which seem to refer to occurrences like those of which astronomers and geologists have attempted to determine the laws, have given rise to many interpretations, all inconsistent with one another, and most of them at variance with the best established principles of astronomy and geology

It may be urged, that all truths must be consistent with all other truths, and that therefore the results of true geology or astronomy cannot be irreconcileable with the statements of true theology. And this universal consistency of truth with itself must be assented to; but it by no means follows that we must be able to obtain a full insight into the nature and manner of such a consistency. Such an insight would only be possible if we could obtain a clear view of that central body of truth, the source of the principles which appear in the separate lines of speculation. To expect that we should see clearly how the providential government of the world is consistent with the unvarying laws 572 by which its motions and developements are regulated, is to expect to understand thoroughly the laws of motion, of developement, and of providence; it is to expect that we may ascend from geology and astronomy to the creative and legislative centre, from which proceeded earth and stars; and then descend again into the moral and spiritual world, because its source and centre are the same as those of the material creation. It is to say that reason, whether finite or infinite, must be consistent with itself; and that, therefore, the finite must be able to comprehend the infinite, to travel from any one province of the moral and material universe to any other, to trace their bearing, and to connect their boundaries.

One of the advantages of the study of the history and nature of science in which we are now engaged is, that it warns us of the hopeless and presumptuous character of such attempts to understand the government of the world by the aid of science, without throwing any discredit upon the reality of our knowledge; that while it shows how solid and certain each science is, so long as it refers its own facts to its own ideas, it confines each science within its own limits, and condemns it as empty and helpless, when it pronounces upon those subjects which are extraneous to it The error of persons who should seek a geological narrative in theological records, would be rather in the search itself than in their interpretation of what they might find; and in like manner the error of those who would conclude against a supernatural beginning, or a providential direction of the world, upon geological or physiological reasonings, would be, that they had expected those sciences alone to place the origin or the government of the world in its proper light.

Though these observations apply generally to all the palætiological sciences, they may be permitted here, because they have an especial bearing upon some of the difficulties which have embarrassed the progress of geological speculation; and though such difficulties are, I trust, nearly gone by, it is important for us to see them in their true bearing.

From what has been said, it follows that geology and astronomy are, of themselves, incapable of giving us any distinct and satisfactory account of the origin of the universe, or of its parts. We need not wonder, then, at any particular instance of this incapacity; as, for example, that of which we have been speaking, the impossibility of accounting by any natural means for the production of all the successive tribes of plants and animals which have peopled

the world in the 573 various stages of its progress, as geology teaches us. That they were, like our own animal and vegetable contemporaries, profoundly adapted to the condition in which they were placed, we have ample reason to believe; but when we inquire whence they came into this our world, geology is silent. The mystery of creation is not within the range of her legitimate territory; she says nothing, but she points upwards

Sect. 6.—The Hypothesis of the regular Creation and Extinction of Species.

1. Creation of Species.—We have already seen, how untenable, as a physiological doctrine, is the principle of the transmutability and progressive tendency of species; and therefore, when we come to apply to theoretical geology the principles of the present chapter, this portion of the subject will easily be disposed of. I hardly know whether I can state that there is any other principle which has been applied to the solution of the geological problem, and which, therefore, as a general truth, ought to be considered here. Mr. Lyell, indeed, has spoken 89 of an hypothesis that “the successive creation of species may constitute a regular part of the economy of nature:” but he has nowhere, I think, so described this process as to make it appear in what department of science we are to place the hypothesis. Are these new species created by the production, at long intervals, of an offspring different in species from the parents? Or are the species so created produced without parents? Are they gradually evolved from some embryo substance? or do they suddenly start from the ground, as in the creation of the poet?

Perfect forms

Limbed and full-grown: out of the ground up rose

As from his lair, the wild beast where he wons In forest wild, in thicket, brake, or den; . . . The grassy clods now calved; now half appeared The tawny lion, pawing to get free His hinder parts; then springs as broke from bounds, And rampant shakes his brinded mane; &c &c

Paradise Lost, B. vii.

89 B c xi p 234

Some selection of one of these forms of the hypothesis, rather than the others, with evidence for the selection, is requisite to entitle us to 574 place it among the known causes of change which in this chapter we are considering. The bare conviction that a creation of species has taken place, whether once or many times, so long as it is unconnected with our organical sciences, is a tenet of Natural Theology rather than of Physical Philosophy.

[2nd Ed.] [Mr. Lyell has explained his theory 90 by supposing man to people a great desert, introducing into it living plants and animals: and he has traced, in a very interesting manner, the results of such a hypothesis on the distribution of vegetable and animal species. But he supposes the agents who do this, before they import species into particular localities, to study attentively the climate and other physical conditions of each spot, and to use various precautions It is on account of the notion of design thus introduced that I have, above, described this opinion as rather a tenet of Natural Theology than of Physical Philosophy.

90 B. . c. viii. p. 166.

Mr. Edward Forbes has published some highly interesting speculations on the distribution of existing species of animals and plants. It appears that the manner in which animal and vegetable

forms are now diffused requires us to assume centres from which the diffusion took place by no means limited by the present divisions of continents and islands. The changes of land and water which have thus occurred since the existing species were placed on the earth must have been very extensive, and perhaps reach into the glacial period of which I have spoken above. 91

91 See, in Memoirs of the Geological Survey of Great Britain, vol. i p 336, Professor Forbes’s Memoir “On the Connection between the Distribution of the existing Fauna and Flora of the British Isles, and the Geological Changes which have affected their area, especially during the epoch of the Northern Drift.”

According to Mr. Forbes’s views, for which he has offered a great body of very striking and converging reasons, the present vegetable and animal population of the British Isles is to be accounted for by the following series of events. The marine deposits of the meiocine formation were elevated into a great Atlantic continent, yet separate from what is now America, and having its western shore where now the great semi-circular belt of gulf-weed ranges from the 15th to the 45th parallel of latitude. This continent then became stocked with life, and of its vegetable population, the flora of the west of Ireland, which has many points in common with the flora of Spain and the 575 Atlantic islands (the Asturian flora), is the record The region between Spain and Ireland, and the rest of this meiocene continent, was destroyed by some geological movement, but there were left traces of the connexion which still remain. Eastwards of the flora just mentioned, there is a flora common to Devon and Cornwall, to the south-east part of Ireland, the Channel Isles, and the adjacent provinces of France; a flora passing to a southern character; and having its course marked by the remains of a great rocky barrier, the destruction of which probably took place anterior to the formation of

the narrower part of the channel. Eastward from this Devon or Norman flora, again, we have the Kentish flora, which is an extension of the flora of North-western France, insulated by the breach which formed the straits of Dover. Then came the Glacial period, when the east of England and the north of Europe were submerged, the northern drift was distributed, and England was reduced to a chain of islands or ridges, formed by the mountains of Wales, Cumberland, and Scotland, which were connected with the land of Scandinavia This was the period of glaciers, of the dispersion of boulders, of the grooving and scratching of rocks as they are now found. The climate being then much colder than it now is, the flora, even down to the water’s edge, consisted of what are now Alpine plants; and this Alpine flora is common to Scandinavia and to our mountain-summits. And these plants kept their places, when, by the elevation of the land, the whole of the present German Ocean became a continent connecting Britain with central Europe. For the increased elevation of their stations counterbalanced the diminished cold of the succeeding period. Along the dry bed of the German Sea, thus elevated, the principal part of the existing flora of England, the Germanic flora, migrated. A large portion of our existing animal population also came over through the same region; and along with those, came hyenas, tigers, rhinoceros, aurochs, elk, wolves, beavers, which are extinct in Britain, and other animals which are extinct altogether, as the primigenian elephant or mammoth. But then, again, the German Ocean and the Irish Channel were scooped out; and the climate again changed. In our islands, so detached, many of the larger beasts perished, and their bones were covered up in peat-mosses and caves, where we find them. This distinguished naturalist has further shown that the population of the sea lends itself to the same view. Mr. Forbes says

that the writings of Mr. Smith, of Jordan-hill, “On the last Changes in the relative Levels of the Land and Sea in the British Islands,” published in the Memoirs of the 576 Wernerian Society for 1837–8, must be esteemed the foundation of a critical investigation of this subject in Britain.]

2. Extinction of Species.—With regard to the extinction of species Mr. Lyell has propounded a doctrine which is deserving of great attention here. Brocchi, when he had satisfied himself, by examination of the Sub-Apennines, that about half the species which had lived at the period of their deposition, had since become extinct, suggested as a possible cause for this occurrence, that the vital energies of a species, like that of an individual, might gradually decay in the progress of time and of generations, till at last the prolific power might fail, and the species wither away. Such a property would be conceivable as a physiological fact; for we see something of the kind in fruit-trees propagated by cuttings: after some time, the stock appears to wear out, and loses its peculiar qualities. But we have no sufficient evidence that this is the case in generations of creatures continued by the reproductive powers. Mr. Lyell conceives, that, without admitting any inherent constitutional tendency to deteriorate, the misfortunes to which plants and animals are exposed by the change of the physical circumstances of the earth, by the alteration of land and water, and by the changes of climate, must very frequently occasion the loss of several species. We have historical evidence of the extinction of one conspicuous species, the Dodo, a bird of large size and singular form, which inhabited the Isle of France when that island was first discovered, and which now no longer exists. Several other species of animals and plants seem to be in the course of vanishing from the face of the earth, even under our own observation. And taking into account the

greater changes of the surface of the globe which geology compels us to assume, we may imagine many or all the existing species of living things to be extirpated. If, for instance, that reduction of the climate of the earth which appears, from geological evidence, to have taken place already, be supposed to go on much further, the advancing snow and cold of the polar regions may destroy the greater part of our plants and animals, and drive the remainder, or those of them which possess the requisite faculties of migration and accommodation, to seek an asylum near the equator And if we suppose the temperature of the earth to be still further reduced, this zone of now-existing life, having no further place of refuge, will perish, and the whole earth will be tenanted, if at all, by a new creation. Other causes might produce the same effect as a change of climate; and, without supposing such causes to affect the whole globe, it is easy to 577 imagine circumstances such as might entirely disturb the equilibrium which the powers of diffusion of different species have produced; might give to some the opportunity of invading and conquering the domain of others; and in the end, the means of entirely suppressing them, and establishing themselves in their place.

That this extirpation of certain species, which, as we have seen, happens in a few cases under common circumstances, might happen upon a greater scale, if the range of external changes were to be much enlarged, cannot be doubted. The extent, therefore, to which natural causes may account for the extinction of species, will depend upon the amount of change which we suppose in the physical conditions of the earth. It must be a task of extreme difficulty to estimate the effect upon the organic world, even if the physical circumstances were given. To determine the physical condition to which a given state of the earth would give rise, I have already noted

as another very difficult problem. Yet these two problems must be solved, in order to enable us to judge of the sufficiency of any hypothesis of the extinction of species; and in the mean time, for the mode in which new species come into the places of those which are extinguished, we have (as we have seen) no hypothesis which physiology can, for a moment, sanction.

Sect. 7. The Imbedding of Organic Remains.

T is still one portion of the Dynamics of Geology, a branch of great and manifest importance, which I have to notice, but upon which I need only speak very briefly. The mode in which the spoils of existing plants and animals are imbedded in the deposits now forming, is a subject which has naturally attracted the attention of geologists. During the controversy which took place in Italy respecting the fossils of the Sub-Apennine hills, Vitaliano Donati, 92 in 1750, undertook an examination of the Adriatic, and found that deposits containing shells and corals, extremely resembling the strata of the hills, were there in the act of formation. But without dwelling on other observations of like kind, I may state that Mr. Lyell has treated this subject, and all the topics connected with it, in a very full and satisfactory manner. He has explained, 93 by an excellent collection of illustrative facts, how deposits of various substance and contents are formed; how plants and animals become fossil in peat, in blown sand, in volcanic matter, in 578 alluvial soil, in caves, and in the beds of lakes and seas. This exposition is of the most instructive character, as a means of obtaining right conclusions concerning the causes of geological phenomena. Indeed, in many cases, the similarity of past effects with operations now going on, is so complete, that they may be considered as identical; and the

discussion of such cases belongs, at the same time, to Geological Dynamics and to Physical Geology; just as the problem of the fall of meteorolites may be considered as belonging alike to mechanics and to physical astronomy. The growth of modern peat-mosses, for example, fully explains the formation of the most ancient: objects are buried in the same manner in the ejections of active and of extinct volcanoes; within the limits of history, many estuaries have been filled up; and in the deposits which have occupied these places, are strata containing shells, 94 as in the older formations

92 Lyell, B c iii p 67 (4th ed )

93 B. . c. xiii. xiv. xv. xvi. xvii.

94 Lyell, B. . c. xvii. p. 286. See also his Address to the Geological Society in 1837, for an account of the Researches of Mr Stokes and of Professor Göppert, on the lapidification of vegetables

PHYSICAL GEOLOGY.

CHAPTER VII.

P P G

Sect. 1. Object and Distinctions of Physical Geology.

BEING, in consequence of the steps which we have attempted to describe, in possession of two sciences, one of which traces the laws of action of known causes, and the other describes the phenomena which the earth’s surface presents, we are now prepared to examine how far the attempts to refer the facts to their causes have been successful: we are ready to enter upon the consideration of Theoretical or Physical Geology, as, by analogy with Physical Astronomy, we may term this branch of speculation

The distinction of this from other portions of our knowledge is sufficiently evident In former times, Geology was always associated with Mineralogy, and sometimes confounded with it; but the mistake of such an arrangement must be clear, from what has been said Geology is connected with Mineralogy, only so far as the latter science classifies a large portion of the objects which Geology employs as evidence of its statements. To confound the two is the same error as it would be to treat philosophical history as identical with the knowledge of medals. Geology procures evidence of her conclusions wherever she can; from minerals or from seas; from inorganic or from organic bodies; from the ground or from the skies. The geologist’s business is to learn the past history of the earth; and he is no more limited to one or a few kinds of documents, as his sources of information, than is the historian of man, in the execution of a similar task.

Physical Geology, of which I now speak, may not be always easily separable from Descriptive Geology: in fact, they have generally been combined, for few have been content to describe, without attempting in some measure to explain. Indeed, if they had done so, it is 580 probable that their labors would have been far less zealous, and their expositions far less impressive. We by no means regret, therefore, the mixture of these two kinds of knowledge, which has so often occurred; but still, it is our business to separate them. The works of astronomers before the rise of sound physical astronomy, were full of theories, but these were advantageous, not prejudicial, to the progress of the science.

Geological theories have been abundant and various; but yet our history of them must be brief For our object is, as must be borne in mind, to exhibit these, only so far as they are steps discoverably tending to the true theory of the earth: and in most of them we do not trace this character. Or rather, the portions of the labors of geologists which do merit this praise, belong to the two preceding divisions of the subject, and have been treated of there.

The history of Physical Geology, considered as the advance towards a science as real and stable as those which we have already treated of (and this is the form in which we ought to trace it), hitherto consists of few steps. We hardly know whether the progress is begun. The history of Physical Astronomy almost commences with Newton, and few persons will venture to assert that the Newton of Geology has yet appeared.

Still, some examination of the attempts which have been made is requisite, in order to explain and justify the view which the analogy of scientific history leads us to take, of the state of the subject. Though

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