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Data management in the semanti...
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Data management in the semantic web / editor, Hal Jin.
Saved in:
Bibliographic Details
Other Authors:
Jin, Hal
Format:
eBook
Language:
English
Published:
Hauppauge, N.Y. :
Nova Science Publishers,
©2011.
Subjects:
Web databases.
Internet searching.
Semantic Web.
COMPUTERS
>
Online Services
>
Resource Directories.
COMPUTERS
>
System Administration
>
Storage & Retrieval.
Internet searching
Semantic Web
Web databases
Online Access:
Click for online access
Holdings
Description
Table of Contents
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Table of Contents:
DATA MANAGEMENT IN THE SEMANTIC WEB ; DATA MANAGEMENT IN THE SEMANTIC WEB ; CONTENTS ; PREFACE ; INTERPRETATIONS OF THE WEB OF DATA; Abstract; 1. Introduction; 2. ADistributedKnowledgeBase; 2.1. RDFSchema; 2.2. WebOntologyLanguage; 2.3. Non-AxiomaticLogic; 2.3.1. TheNon-AxiomaticLanguage; 2.3.2. TheNon-AxiomaticReasoner; 3. ADistributedMulti-RelationalNetwork; 3.1. Single-RelationalNetworks; 3.2. Multi-RelationalNetworks; 3.3. Single-RelationalNetworkAlgorithms; 3.3.1. ShortestPath; 3.3.2. Eccentricity, Radius, and Diameter; 3.3.3. ClosenessandBetweennessCentrality; 3.3.4. StationaryProbabilityDistribution.
3.3.5. PageRank3.3.6. SpreadingActivation; 3.3.7. AssortativeMixing; 3.4. PortingSingle-RelationalAlgorithmstotheMulti-RelationalDomain; 3.4.1. AMulti-RelationalPathAlgebra; 3.4.2. Multi-RelationalGrammarWalkers; 4. ADistributedObjectRepository; 4.1. PartialObjectRepository; 4.2. FullObjectRepository; 4.3. VirtualMachineRepository; 5. Conclusion; Acknowledgments; References; 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 ; Related Terms ; References ; A SEMANTIC TREE REPRESENTATION FOR DOCUMENT CATEGORIZATION WITH A COMPOSITE KERNEL; Abstract; 1. Introduction; 2. RelatedWork; 3. TheUMLSFramework; 4. DocumentModeling; 5. TheSemanticKernel; 5.1. TheMercerKernelFramework; 5.2. TheUMLS-basedKernel; 5.3. TheConceptKernel; 6. ExperimentalEvaluation; 6.1. TheSVMClassifier; 6.2. TheMultinomialNaiveBayesClassifier; 6.3. TheCorpus; 6.4. ExperimentalSetup; 6.5. ExperimentalResults; 6.6. Discussionaboutthe2007CMCMedicalNLPChallenge.
7. ConclusionAcknowledgments; References; ONTOLOGY REUSE
IS IT FEASIBLE?; 1. Introduction; 2. OntologyReuse; 2.1. ProcessOverview; 2.2. StateofPractice; 2.3. Methodologies, MethodsandTools; 3. AnEconomicModelforOntologyReuse; 3.1. AnEconomicAnalysisofOntologyReuse; 3.2. TowardsanEconomicModelforOntologyReuse; 3.2.1. TheONTOCOMModel; 3.2.2. ExtensionsofONTOCOMforReuse; 3.2.3. CalculatingtheRelativeCostsofOntologyReuse; 3.3. ApplicationoftheModel; 4. ConclusionsandOutlook; References; 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.
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