Data management in the semantic web [[electronic resource] /] / Hal Jin, editor

• Record Nr.: UNINA9910825006303321
• Pubbl/distr/stampa: Hauppauge, N.Y., : Nova Science Publishers, c2012
• ISBN: 1-61324-760-5
• Edizione: [1st ed.]
• Descrizione fisica: 1 online resource (450 p.)
• Collana: Distributed, cluster and grid computing
• Altri autori (Persone): JinHal
• Disciplina: 025.042/7
• Soggetti: Web databases; Internet searching; Semantic Web
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Intro -- DATA MANAGEMENT IN THE SEMANTIC WEB -- DATA MANAGEMENT IN THE SEMANTIC WEB -- CONTENTS -- PREFACE -- Chapter1INTERPRETATIONSOFTHEWEBOFDATA -- Abstract -- 1Introduction -- 2ADistributedKnowledgeBase -- 2.1RDFSchema -- 2.2WebOntologyLanguage -- 2.3Non-AxiomaticLogic -- 2.3.1TheNon-AxiomaticLanguage -- 2.3.2TheNon-AxiomaticReasoner -- 3ADistributedMulti-RelationalNetwork -- 3.1Single-RelationalNetworks -- 3.2Multi-RelationalNetworks -- 3.3Single-RelationalNetworkAlgorithms -- 3.3.1ShortestPath -- 3.3.2Eccentricity,Radius,andDiameter -- 3.3.3ClosenessandBetweennessCentrality -- 3.3.4StationaryProbabilityDistribution -- 3.3.5PageRank -- 3.3.6SpreadingActivation -- 3.3.7AssortativeMixing -- 3.4PortingSingle-RelationalAlgorithmstotheMulti-RelationalDomain -- 3.4.1AMulti-RelationalPathAlgebra -- 3.4.2Multi-RelationalGrammarWalkers -- 4ADistributedObjectRepository -- 4.1PartialObjectRepository -- 4.2FullObjectRepository -- 4.3VirtualMachineRepository -- 5Conclusion -- Acknowledgements -- References -- Chapter 2 TOWARD SEMANTICS-AWARE WEB CRAWLING -- ABSTRACT -- 1 Introduction -- 2 Related Work -- 3 Semantics-Aware Crawler -- 3.1 Identifying Topic-Specific URLs -- 3.2 Building Training Examples -- 3.3 Ordering URLs in the Crawler's Frontier -- 4 Experimental Evaluation -- 4.1 Semantics-Aware Crawling Performance -- 5 Discussion -- 6 ; Conclusion -- References -- Related Terms -- Chapter3ASEMANTICTREEREPRESENTATIONFORDOCUMENTCATEGORIZATIONWITHACOMPOSITEKERNEL -- Abstract -- 1Introduction -- 2Relatedwork -- 3TheUMLSFramework -- 4DocumentModeling -- 5TheSemanticKernel -- 5.1TheMercerkernelframework -- 5.2TheUMLS-basedKernel -- 5.3TheConceptKernel -- 6ExperimentalEvaluation -- 6.1TheSVMClassifier -- 6.2TheMultinomialNaiveBayesClassifier -- 6.3Thecorpus -- 6.4Experimentalsetup -- 6.5Experimentalresults.; 6.6Discussionaboutthe2007CMCMedicalNLPChallenge -- 7Conclusion -- Acknowledgments -- References -- Chapter4ONTOLOGYREUSE-ISITFEASIBLE? -- 1Introduction -- 2OntologyReuse -- 2.1ProcessOverview -- 2.2StateofPractice -- 2.3Methodologies,MethodsandTools -- 3AnEconomicModelforOntologyReuse -- 3.1AnEconomicAnalysisofOntologyReuse -- 3.2TowardsanEconomicModelforOntologyReuse -- 3.2.1TheONTOCOMmodel -- 3.2.2ExtensionsofONTOCOMforReuse -- 3.2.3CalculatingtheRelativeCostsofOntologyReuse -- 3.3ApplicationoftheModel -- 4ConclusionsandOutlook -- References -- Chapter 5 COMPUTATIONAL LOGIC AND KNOWLEDGE REPRESENTATION ISSUES IN DATA ANALYSIS FOR THE SEMANTIC WEB -- ABSTRACT -- 1 Introduction -- 2 Automated Reasoning for Ontology Engineering -- 2.1 Logical databases versus knowledge dynamism -- 3 Poor Representation and Deficient Ontologies -- 3.1 Skolem noise and poor representation -- 3.2 A special case: Semantic Mobile Web 2.0 -- 4 When is an Ontology Robust? -- 4.1 Representational perspective -- 4.2 Computational logic perspective -- 5 Lattice Categorical Theories as Robust Ontologies -- 5.1 Computational viewpoint of ontological Extensions -- 5.2 Representational perspective: Knowledge reconciliation and ontological extensions -- 5.3 Merging robust ontologies -- 5.4 Conservative retractions -- 5.5 Conservative retractions -- 6 Anomalies in Ontologies -- 6.1 Inconsistency: debugging, updating and beyond -- 6.2 Arguments, logic and trust -- 7 FOL as the Universal Provider for Formal Semantics -- 7.1 Model Theory for Semantic Web -- 8 Untrustworthy Information Versus Ontology and Knowledge -- 8.1 Mental attitudes and ontology reasoning -- 8.2 Emergent Ontologies -- 9 Understanding Ontologies: Mereotopology and Entailment-based Visualization -- 10 Meta-logical Trust -- 10.1 Extend OWL to ROWL.; 10.2 Verification of Description Logics -- 11 Final Remarks -- Acknowledgments -- References -- Chapter6APPLYINGSEMANTICWEBTECHNOLOGIESTOBIOLOGICALDATAINTEGRATIONANDVISUALIZATION -- Abstract -- 1Introduction -- 2SemanticWebtechnologies -- 3SemanticWebforthelifesciences -- 3.1Biologicaldataarehugeinvolume -- 3.2Biologicaldatasourcesareheterogeneous -- 3.3Bio-ontologiesdonotfollowstandardsforontologydesign -- 3.4Biologicalknowledgeiscontextdependant -- 3.5Dataprovenanceisofcrucialimportance -- 4BiologicaldataintegrationwithSemanticWebTechnologies -- 4.1Datagathering -- 4.2Dataconversion -- 4.3OntologyofgeneratedRDFdescriptions -- 4.4PrincipeofURIsencoding -- 4.5Unificationofresources -- 4.6Ontologiesmerging -- 4.7Datarepository -- 4.8InformationretrievalwithSPARQL -- 5Datavisualization -- 6Discussion -- 7Conclusion -- References -- Chapter 7 AN ONTOLOGY AND PEER-TO-PEER BASED DATA AND SERVICE UNIFIED DISCOVERY SYSTEM -- ABSTRACT -- 1 Introduction -- 2 Preliminaries -- 2.1 Terms and definitions -- 2.2 Ontological ; data -- 2.2.1 Resource domain ontology -- 2.2.2 Thesaurus ontology -- 2.2.3 Service description ontology -- 2.2.4 QoS ontology -- 2.3 JXTA -- 3. Design of Unified Discovery System -- 4 Combine with JXTA -- 5. Resource registry and discovery -- 5.1. Resource registry process -- 5.2 Resource discovery process -- 5.3 Algorithms -- 5.3.1 Getting group location algorithm -- 5.3.2 Locating resource algorithm -- 5.3.3 Service matching algorithm -- 6 Implementation and Experimental Results -- 7 Related Work -- 8 Conclusion -- References -- Chapter8THEDESIGNANDDEVELOPMENTOFASEMANTICENVIRONMENTFORHOLISTICEGOVERNMENTSERVICES -- Abstract -- 1Introduction -- 2Analysisoftheproblem&amp -- motivation -- 3RelatedWork -- 4BusinessModel -- 5LifeEvents.Theknowledgemodel -- 6Semanticsupport -- 6.1Semantics.; 6.2Applyingsemantics -- 7SupportingArchitecture -- 8LEsinmotion -- 9Conclusion -- 10Acknowledgment -- References -- Chapter 9 SEMANTIC TOPIC MODELING AND ITS APPLICATION IN BIOINFORMATICS -- ABSTRACT -- 1 Introduction -- 2 Latent Dirichlet allocation (LDA) model -- 2.1 Model specification -- 2.2 Statistical learning -- 3 Applications of LDA in biomedical research -- 3.1 Identifying biological related topics -- 3.2 Enhancing text categorization with semantic-enriched representation and training data augmentation -- 3.3 Evaluating the functional coherence of protein groups -- 4 Discussion -- Acknowledgments -- References -- Chapter 10 SUPPORTING A USER IN HIS ANNOTATION AND BROWSING ACTIVITIES IN FOLKSONOMIES -- ABSTRACT -- 1 Introduction -- 2 Preliminaries -- 2.1 Basic Definitions -- 3 Phase 1: Neighborhood Computation -- 3.1 Step 2: Construction of the sets of candidate tags starting fromTSetInput -- 3.2 Step 3: Construction of NeighTSetInput starting from the sets of candidate tags -- 4 Phase 2: Hierarchy Construction -- 4.1 The MST-based algorithm -- 4.2 The Concentric algorithm -- 5 Prototype Description -- 5.1 Class Diagram -- 5.2 Use Case and Sequence Diagrams -- 6 Experiments -- 7 Related Work -- 8 Conclusions -- References -- Chapter 11 DATA MANAGEMENT IN SENSOR NETWORKS USING SEMANTIC WEB TECHNOLOGIES -- ABSTRACT -- 1 Introduction -- 2 Sensor Networks -- 2.1 Sensor Nodes: Functionality and Characteristics -- 2.2 Sensor Networks Topologies -- 2.3 Application Areas -- 2.4 Sensor Web: Data and Services in a Sensor Network -- 3 Knowledge Management in Sensor Networks -- 3.1 Current Approaches -- 3.2 A Unifying Generic Architecture for Sensor Data Management -- 3.2.1 Data Layer -- 3.2.2 Processing Layer -- 3.2.3 Semantic Layer -- 3.2.4 Use Case Scenario.; 4 Conclusions - Open Issues -- References -- Chapter 12 CHINESE SEMANTIC DEPENDENCY ANALYSIS -- ABSTRACT -- 1 Introduction -- 2 Semantic Annotation -- Semantic Role Labeling -- Semantic Dependency Analysis -- 3 Chinese Semantic Dependency Corpus and Tag Set -- 4 Semantic Dependency Relation Classification -- Mutli-Classifier Classification -- Classification Features -- Rule-Based Correction -- 5 Experimental Results -- 6 The SEEN System -- Syntatic Analysis Module -- Headword Assignment Module -- Semantic Dependency Assignment Module -- 7 Conclusion -- References -- Chapter 13 CREATING PERSONAL CONTENT MANAGEMENT SYSTEMS USING SEMANTIC WEB TECHNOLOGIES -- ABSTRACT -- 1 Introduction -- 2 Related Work -- 3 PCMS Metadata Model -- 3.1 Content-independent metadata -- 3.1.1 System Metadata -- 3.1.2 Security Metadata -- 3.1.3 User Metadata -- 3.2 Image-related Metadata -- 4 Semantic PCMS -- 4.1 Interoperability Issues -- 4.2 Semantic ; Metadata Model -- 4.3 Lower layer -- 4.4 Mapping and rules -- 5 Metadata Service -- 5.1 Metadata Management -- 5.2 XML to RDF Conversion -- 6 Use Case Scenario -- 6.1 Solving the Use Case Scenario with the Proposed System -- 6.2 Solving the Use Case Scenario with the Related Work -- 7 Conclusion -- 8 Acknowledgments -- References -- Chapter 14 A HYBRID DATA LAYER TO UTILIZE OPEN CONTENT FOR HIGHER-LAYERED APPLICATIONS -- ABSTRACT -- 1 Introduction -- Resources and Open Content -- Web 3.0 alias Social Semantic Web behind the scenes -- 2 How to Utilize Open Content for Higher-layered Applications? -- 3. State of the Art and Related Work -- 4 qKAI Application Framework -- qKAI system layer -- Data storage and change management -- Discovering Linked Data by setting Points of Interest -- SQL replaces SPARQL -- Hybrid knowledge index -- Change management.; Reusability and extensibility.