Диссертация (1137055), страница 18
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Таксономия разделов, связанных с анализом данных имашинным обучением, по классификации ACM CCS 2012Таблица 1. Таксономия ACM CCS 2012 (на языке оригинала)Индекс1.1.1.1.1.1.1.1.1.1.1.1.1.2.1.1.1.3.1.1.1.4.1.1.1.4.1.1.1.1.4.2.1.1.1.4.3.*1.1.1.5.1.1.1.6.1.1.1.7.1.1.1.8.1.1.1.9.1.1.1.10.1.1.1.11.1.1.1.12.1.1.1.13.1.1.1.13.1. 1.1.1.13.61.1.1.14.1.1.1.15.1.1.1.16.1.1.1.17.1.1.2.1.1.2.1.-1.1.2.12.2.2.1.2.1.1.2.1.1.1.2.1.1.2.2.1.1.3.2.1.1.4.2.1.1.5.2.1.1.6.Название предметаTheory ofcomputationTheory and algorithms for application domainsMachine learning theorySample complexity and generalization boundsBoolean function learningUnsupervised learning and clusteringKernel methodsSupport vector machinesGaussian processesModellingBoostingBayesian analysisInductive inferenceOnline learning theoryMulti-agent learningModels of learningQuery learningStructured predictionReinforcement learning…Active learningSemi-supervised learningMarkov decision processesRegret boundsDatabase theory…Mathematics of computingProbability and statisticsProbabilistic representationsBayesian networksMarkov networksFactor graphsDecision diagramsEquational modelsCausal networks119Индекс2.1.1.7.2.1.1.8.2.1.1.8.1.2.1.1.8.2.2.1.1.8.3.2.1.2.2.1.2.1.-2.1.2.6.2.1.3.2.1.3.1.2.1.3.2.2.1.3.3.2.1.3.4.2.1.3.5.2.1.3.5.1.2.1.3.5.4.2.1.3.6.2.1.3.7.2.1.3.7.1*2.1.3.8.2.1.3.8.1.2.1.3.8.2.2.1.3.9.2.1.4.2.1.5.2.1.5.1.2.1.5.2.2.1.5.3.2.1.5.3.1.2.1.5.4.2.1.5.5.2.1.5.6.2.1.5.7.2.1.5.8.2.1.5.9.2.1.5.10.2.1.6.2.1.6.1.2.1.7.2.1.8.2.1.9.3.3.1.3.1.1.Название предметаStochastic differential equationsNonparametric representationsKernel density estimatorsSpline modelsBayesian nonparametric modelsProbabilistic inference problems…Probabilistic reasoning algorithmsVariable eliminationLoopy belief propagationVariational methodsExpectation maximizationMarkov-chain Monte Carlo methods…Sequential Monte Carlo methodsKalman filters and hidden Markov modelsFactorial HMMResampling methodsBootstrappingJackknifingRandom number generationProbabilistic algorithmsStatistical paradigmsQueueing theoryContingency table analysisRegression analysisRobust regressionTime series analysisSurvival analysisRenewal theoryDimensionality reductionCluster analysisStatistical graphicsExploratory data analysisStochastic processesMarkov processesNonparametric statisticsDistribution functionsMultivariate statisticsInformation systemsData management systemsDatabase design and models120Индекс3.1.1.1.3.1.1.2.3.1.1.3.3.1.1.3.1.3.1.1.3.2.3.1.1.4.3.1.1.5.3.1.1.5.1.3.1.1.5.2.3.1.1.5.3.3.1.1.5.4.3.1.1.5.5.3.1.1.5.6.3.1.1.5.7.3.1.2.3.1.2.1.3.1.2.1.1.3.1.2.1.2.3.1.2.1.3.3.1.2.1.4.3.1.2.1.5.3.1.2.2.3.1.2.2.1.3.1.2.2.3.3.1.3.3.1.3.1.-3.1.3.12.3.1.4.3.1.4.1.3.1.4.1.1.3.1.4.2.3.1.4.2.13.1.4.2.2.3.1.4.3.3.1.4.3.1.3.1.4.4.3.1.5.3.1.5.1.-3.1.5.9.3.2.3.2.1.3.2.1.1.3.2.1.2.3.2.1.2.1*3.2.1.2.2*Название предметаRelational database modelEntity relationship modelsGraph-based database modelsHierarchical data modelsNetwork data modelsPhysical data modelsData model extensionsSemi-structured dataData streamsData provenanceIncomplete dataTemporal dataUncertaintyInconsistent dataData structuresData access methodsMultidimensional range searchData scansPoint lookupsUnidimensional range searchProximity searchData layout…Database management system engines…Query languagesRelational database query languagesStructured Query LanguageXML query languagesXPathXQueryQuery languages for non-relational enginesMapReduce languagesCall level interfacesInformation integration…Information systems applicationsData miningData cleaningCollaborative filteringItem-basedScalable121Индекс3.2.1.3.3.2.1.3.1*3.2.1.3.2*3.2.1.3.3*Название предметаAssociation rules3.2.1.4.3.2.1.4.1*3.2.1.4.2*3.2.1.4.3**3.2.1.4.4*3.2.1.4.5*3.2.1.4.6*3.2.1.4.7*3.2.1.5.3.2.1.6.3.2.1.7*3.2.1.7.1*3.2.1.7.2*3.2.1.7.3*3.2.1.7.4*3.2.1.7.5*3.2.1.8.*3.2.1.11*3.2.1.11.1*3.2.1.11.2*3.2.1.10.*3.2.1.9*3.2.1.9.1.*3.2.1.9.2.*3.2.1.9.3*3.2.1.12*3.3.3.3.1.3.3.1.2.3.3.1.3.3.3.1.3.13.3.1.3.3.3.3.1.4.3.3.1.5.3.3.1.6*3.4.3.4.1.3.4.1.1.ClusteringTypes of association rulesInterestingnessParallel computationMassive data clusteringConsensus clusteringFuzzy clusteringAdditive clusteringFeature weight clusteringConceptual clusteringBiclusteringNearest-neighbor searchData stream miningGraph miningGraph partitioningFrequent graph miningGraph based conceptual clusteringAnomaly detectionCritical nodes detectionProcess miningText miningText categorizationKey-phrase indexingData mining toolsSequence miningRule and pattern discoveryTrajectory clusteringMarket graphFormal concept analysisWorld Wide WebWeb miningSite wrappingData extraction and integration…Web log analysisTraffic analysisKnowledge discoveryInformation retrievalDocument representationDocument structure122Индекс3.4.1.2.3.4.1.3.3.4.1.4.3.4.1.5.3.4.1.6.3.4.1.7.3.4.1.8.3.4.2.3.4.2.1.-3.4.2.5.3.4.3.3.4.3.1.-3.4.3.4.3.4.4.3.4.4.1.3.4.4.2.3.4.4.3.3.4.4.4.3.4.4.5.3.4.4.6.3.4.4.7.3.4.4.8.3.4.4.9.3.4.5.3.4.5.1.-3.4.5.10.3.4.6.3.4.6.1.-3.4.6.5.3.4.7.3.4.7.1.-3.4.7.3.4.+04.1.4.1.2.4.1.2.1.4.1.2.2.4.1.2.3.4.1.2.4.4.1.2.5.4.1.2.6.4.1.2.7*4.1.3.4.1.3.1.-4.1.3.4.4.1.4.4.1.4.1.4.1.5.4.1.6.Название предметаDocument topic modelsContent analysis and feature selectionData encoding and canonicalizationDocument collection modelsOntologiesDictionariesThesauriInformation retrieval query processing…Users and interactive retrieval…Retrieval models and rankingRank aggregationProbabilistic retrieval modelsLanguage modelsSimilarity measuresLearning to rankCombination, fusion and federated searchInformation retrieval diversityTop-k retrieval in databasesNovelty in information retrievalRetrieval tasks and goals…Evaluation of retrieval results…Specialized information retrieval…Human-centered computingVisualizationVisualization techniquesTreemapsHyperbolic treesHeat mapsGraph drawingsDendrogramsCladogramsElastic mapsVisualization application domains…Visualization systems and toolsVisualization toolkitsVisualization theory, concepts and paradigmsEmpirical studies in visualization123Индекс4.1.7.5.+05.1.5.1.1.5.1.1.2.5.1.1.3.5.1.1.4.5.1.1.5.5.1.1.6.5.1.1.7.5.1.1.7.1*5.1.1.8.5.1.1.9.5.1.2.5.1.2.1.5.1.2.2.5.1.2.3.5.1.2.4.5.1.2.5.5.1.2.6.5.1.2.7.5.1.2.8.5.1.2.9.5.1.2.10.5.1.2.11.5.1.2.12.5.1.3.5.1.3.1.5.1.3.1.1.5.1.3.1.2.5.1.3.1.3.5.1.3.1.4.5.1.3.1.5.5.1.3.1.6.5.1.3.1.7.5.1.3.1.8.5.1.3.1.9.5.1.3.1.10.5.1.3.2.5.1.3.2.1.5.1.3.2.1.1**5.1.3.2.2.5.1.3.2.3.Название предметаVisualization design and evaluation methodsComputing methodologiesArtificial intelligenceNatural language processingInformation extractionMachine translationDiscourse, dialogue and pragmaticsNatural language generationSpeech recognitionLexical semanticsWikipedia based semanticsPhonology / morphologyLanguage resourcesKnowledge representation and reasoningDescription logicsSemantic networksNonmonotonic, default reasoning and belief revisionProbabilistic reasoningVagueness and fuzzy logicCausal reasoning and diagnosticsTemporal reasoningCognitive roboticsOntology engineeringLogic programming and answer set programmingSpatial and physical reasoningReasoning about belief and knowledgeComputer visionComputer vision problemsInterest point and salient region detectionsImage segmentationVideo segmentationShape inferenceObject detectionObject recognitionObject identificationTrackingReconstructionMatchingComputer vision representationsImage representationsShape representationsAppearance and texture representations124Индекс5.1.3.2.4.5.2.5.2.1.5.2.1.1.5.2.1.1.1.5.2.1.1.2.5.2.1.1.3.5.2.1.1.4.5.2.1.1.5.5.2.1.1.6.5.2.1.2.5.2.1.2.1.5.2.1.2.2.5.2.1.2.3.5.2.1.2.4.5.2.1.2.5.5.2.1.2.6.5.2.1.2.7.5.2.1.2.7.1*5.2.1.2.7.2*5.2.1.3.5.2.1.3.1.5.2.1.3.5.5.2.1.4.5.2.1.4.1.5.2.1.4.3.5.2.2.5.2.2.1.5.2.2.2.5.2.2.3.5.2.2.4.5.2.2.5.5.2.2.6.5.2.2.7.5.2.2.7.1*5.2.3.5.2.3.1.5.2.3.1.1*5.2.3.1.2*5.2.3.1.3*5.2.3.2.5.2.3.2.1.*Название предметаHierarchical representationsMachine learningLearning paradigmsSupervised learningRankingLearning to rankSupervised learning by classificationSupervised learning by regressionStructured outputsCost-sensitive learningUnsupervised learningCluster analysisAnomaly detectionMixture modelingTopic modelingSource separationMotif discoveryDimensionality reduction and manifoldlearningReinforcement learning…Multi-task learning…Learning settingsBatch learningOnline learning settingsLearning from demonstrationsLearning from critiquesLearning from implicit feedbackActive learning settingsSemi-supervised learning settingsKernel approachMachine learning approachesClassification and regression treesParallel implementationSplittting criteriaModel treesKernel methodsKernel support vector machines125Индекс5.2.3.2.1.1**5.2.3.2.2.5.2.3.2.3*5.2.3.2.4*5.2.3.2.5**5.2.3.3.5.2.3.3.1*5.2.3.3.2*5.2.3.3.2.1*5.2.3.3.3*5.2.3.3.3.1*5.2.3.3.3.2*5.2.3.3.4*5.2.3.3.5*5.2.3.4.5.2.3.4.1.5.2.3.4.2.5.2.3.5.5.2.3.5.1.5.2.3.5.2.5.2.3.5.3.5.2.3.5.4.5.2.3.5.5.5.2.3.5.6.5.2.3.5.7.*5.2.3.6.5.2.3.6.1.5.2.3.6.2*5.2.3.6.2.1*5.2.3.7.5.2.3.7.1.5.2.3.7.2.5.2.3.7.3.5.2.3.7.3.1*5.2.3.7.3.2*5.2.3.7.4.5.2.3.7.6.5.2.3.7.8.*5.2.3.7.9*5.2.3.7.10**5.2.3.7.10.1**5.2.3.8.5.2.3.8.1*Название предметаGaussian processesKernel MatrixKernel Independent componentsKernel-based clusteringNeural networksSelf organized mapTraining approachesRepresentationEvolving NNEnsemblingLogical and relational learningInductive logic learningStatistical relational learningLearning in probabilistic graphical modelsMaximum likelihood modelingMaximum entropy modelingMaximum a posteriori modelingMixture modelsLatent variable modelsBayesian network modelsMarkov network modelsLearning linear modelsPerceptron algorithmLinear Discriminant AnalysisFactorization methodsNon-negative matrix factorizationFactor analysisPrincipal component analysisCanonical correlation analysisLatent Dirichlet allocationIndependent Component AnalysisNonlinear Principal ComponentsMultidimentional scalingRule learningNeuro-fuzzy approach126Индекс5.2.3.9.5.2.3.10.5.2.3.11.5.2.3.12.5.2.3.13.5.2.3.13.1.5.2.3.14*5.2.3.15*5.2.4.5.2.4.1.5.2.4.1.1.5.2.4.1.5.5.2.4.2.5.2.4.2.1.5.2.4.2.2.5.2.4.2.3.**5.2.4.3.5.2.4.3.1*5.2.4.4.5.2.4.5.5.2.4.5.1*5.2.5.Название предметаInstance-based learningMarkov decision processesPartially-observable Markov decision processesStochastic gamesLearning latent representationsDeep belief networksMultiresolutionSupport vector machinesMachine learning algorithmsDynamic programming for Markov decision processes…Ensemble methodsBoostingBaggingFusion of classifiersSpectral methodsSpectral clusteringFeature selectionRegularizationGeneralized eigenvalueCross-validation.
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