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UNINA9910464601703321 |
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Autore |
Hogan Aidan |
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Titolo |
Reasoning techniques for the web of data / / Aidan Hogan |
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Pubbl/distr/stampa |
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[Burke, Virginia] : , : IOS Press, , 2014 |
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©2014 |
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ISBN |
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Descrizione fisica |
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1 online resource (344 p.) |
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Collana |
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Studies on the Semantic Web, , 2215-0870 ; ; Volume 019 |
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Disciplina |
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Soggetti |
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Semantic computing |
Artificial intelligence |
Electronic books. |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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""Title Page""; ""Contents""; ""Prologue""; ""Introduction""; ""Problem Statement""; ""Incomplete Agreement on Assertional Identifiers""; ""Use of Analogous Terminologies""; ""Hypothesis""; ""Contribution and Thesis Structure""; ""Impact""; ""Background""; ""The World Wide Web""; ""The Semantic Web""; ""Resource Description Framework""; ""RDF Schema""; ""Web Ontology Language""; ""RDF Web Publishing and Linked Data""; ""RDF Search Engines""; ""Notation and Core Concepts""; ""RDF""; ""Turtle Syntax""; ""Linked Data Principles and Provenance""; ""Atoms and Rules"" |
""Terminological Data: RDFS/OWL""""Distribution Framework""; ""Crawling, Corpus and Ranking""; ""Crawler""; ""Breadth-first Crawling""; ""Incorporating Politeness""; ""On-disk Queue""; ""Multi-threading""; ""Crawling RDF/XML""; ""Distributed Approach""; ""Related Work""; ""Critical Discussion and Future Directions""; ""Evaluation Corpus""; ""Crawl Statistics""; ""Corpus Statistics""; ""Related Work""; ""Critical Discussion and Future Directions""; ""Ranking""; ""Rationale and High-level Approach""; ""Creating and Ranking the Source Graph""; ""Distributed Ranking Implementation"" |
""Ranking Evaluation and Results""""Related Work""; ""Critical Discussion and Future Directions""; ""Core""; ""Web Reasoning""; ""Linked Data Reasoning: Overview""; ""Incomplete Reasoning: Rationale""; ""Rule- |
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based Reasoning""; ""Forward Chaining""; ""OWL 2 RL/RDF Scalability""; ""Distinguishing Terminological Data""; ""Implementing T-split Inferencing""; ""Optimising the Assertional Program""; ""Merging Equivalent T-ground Rules""; ""Rule Index""; ""Rule Saturation""; ""Preliminary Performance Evaluation""; ""Towards Linked Data Reasoning""; ""``A-linear'' OWL 2 RL/RDF"" |
""Authoritative Reasoning""""Distributed Reasoning""; ""Linked Data Reasoning Evaluation""; ""Related Work""; ""Scalable/Distributed Reasoning""; ""Web Reasoning""; ""Critical Discussion and Future Directions""; ""Annotated Reasoning""; ""Generalised Annotated Programs""; ""Use-case Annotations""; ""Blacklisting""; ""Authoritative Analysis""; ""Triple Ranks""; ""Formal Annotation Framework""; ""Annotation Domains""; ""(Specialised) Annotated Programs""; ""Least Fixpoint and Decidability""; ""Seeding Annotations""; ""T-split Annotated Programs""; ""Annotated Reasoning Tasks""; ""Constraints"" |
""Annotated Linked Data Reasoning""""Ranking Triples: Implementation/Evaluation""; ""Reasoning: Implementation/Evaluation""; ""Repair: Implementation/Evaluation""; ""Related Work""; ""Annotated Reasoning""; ""Inconsistency Repair""; ""Critical Discussion and Future Directions""; ""Consolidation""; ""OWL Equality Semantics""; ""Corpus: Naming Across Sources""; ""Base-line Consolidation""; ""High-level approach""; ""Distributed approach""; ""Evaluation""; ""Extended Reasoning Consolidation""; ""High-level approach""; ""Distributed approach""; ""Evaluation"" |
""Statistical Concurrence Analysis (Synopsis)"" |
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Sommario/riassunto |
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Linked Data publishing has brought about a novel "Web of Data": a wealth of diverse, interlinked, structured data published on the Web. These Linked Datasets are described using the Semantic Web standards and are openly available to all, produced by governments, businesses, communities and academia alike. However, the heterogeneity of such data - in terms of how resources are described and identified - poses major challenges to potential consumers. Herein, we examine use cases for pragmatic, lightweight reasoning techniques that leverage Web vocabularies (described in RDFS and OWL) to better i |
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