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DataMining:ConceptsandTechniques(3rded.)—Chapter13—JiaweiHan,MichelineKamber,andJianPeiUniversityofIllinoisatUrbana-Champaign&SimonFraserUniversity©2011Han,Kamber&Pei.Allrightsreserved.3Chapter13:DataMiningTrendsandResearchFrontiersMiningComplexTypesofDataOtherMethodologiesofDataMiningDataMiningApplicationsDataMiningandSocietyDataMiningTrendsSummary4MiningComplexTypesofDataMiningSequenceDataMiningTimeSeriesMiningSymbolicSequencesMiningBiologicalSequencesMiningGraphsandNetworksMiningOtherKindsofData5MiningSequenceDataSimilaritySearchinTimeSeriesDataSubsequencematch,dimensionalityreduction,query-basedsimilaritysearch,motif-basedsimilaritysearchRegressionandTrendAnalysisinTime-SeriesDatalongterm+cyclic+seasonalvariation+randommovementsSequentialPatternMininginSymbolicSequencesGSP,PrefixSpan,constraint-basedsequentialpatternminingSequenceClassificationFeature-basedvs.sequence-distance-basedvs.model-basedAlignmentofBiologicalSequencesPair-wisevs.multi-sequencealignment,substitutionmatirces,BLASTHiddenMarkovModelforBiologicalSequenceAnalysisMarkovchainvs.hiddenMarkovmodels,forwardvs.Viterbivs.Baum-Welchalgorithms6MiningGraphsandNetworksGraphPatternMiningFrequentsubgraphpatterns,closedgraphpatterns,gSpanvs.CloseGraphStatisticalModelingofNetworksSmallworldphenomenon,powerlaw(log-tail)distribution,densificationClusteringandClassificationofGraphsandHomogeneousNetworksClustering:FastModularityvs.SCANClassification:modelvs.pattern-basedminingClustering,RankingandClassificationofHeterogeneousNetworksRankClus,RankClass,andmetapath-based,user-guidedmethodologyRoleDiscoveryandLinkPredictioninInformationNetworksPathPredictSimilaritySearchandOLAPinInformationNetworks:PathSim,GraphCubeEvolutionofSocialandInformationNetworks:EvoNetClus7MiningOtherKindsofDataMiningSpatialDataSpatialfrequent/co-locatedpatterns,spatialclusteringandclassificationMiningSpatiotemporalandMovingObjectDataSpatiotemporaldatam...