Inference and learning systems for uncertain relational data /:
Gespeichert in:
| 1. Verfasser: | |
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| Körperschaft: | |
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Amsterdam, Netherlands :
IOS Press,
2018.
|
| Schriftenreihe: | Studies on the Semantic Web ;
vol. 035. |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | 1 online resource |
| Bibliographie: | Includes bibliographical references. |
| ISBN: | 9781614998921 1614998922 |
Internformat
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| 505 | 0 | |a Intro; Title Page; Abstract; Acknowledgements; Contents; List of Figures; List of Tables; List of Algorithms; List of Acronyms; Introduction; Motivation; Aims of the Thesis; Structure of the Thesis; Structure; Thesis Contributions; Inference in Probabilistic Logic Programming; Inference in Probabilistic Description Logics; Learning Systems in Probabilistic Logic Programming; Learning Systems in Probabilistic Description Logics; How to read this thesis; Probabilistic Logics; Fundamentals of First-Order Logic and Logic Programming; Introduction; First-Order Logic; Syntax; Tarski's semantics. | |
| 505 | 8 | |a Logic ProgrammingProlog; Normal Logic Programs; First-Order Logic vs Logic Programs; Conclusions; Distribution Semantics; Introduction; Formal Definition; Conclusions; Probabilistic Logic Programming Languages; Introduction; Logic Programs with Annotated Disjunctions; LPADs Syntax; LPADs Semantics; ProbLog; ProbLog Syntax; Conclusions; Description Logics and OWL; Introduction; Description Logics; Syntax; Concept and Role Constructors; Concept Constructors; Role constructors; Knowledge Base; Nomenclature; Semantics; Decidability of Description Logics; Description Logics and First-Order Logic. | |
| 505 | 8 | |a The OWL Ontology LanguageOWL Syntax; OWL sublanguages; Tools for OWL; Conclusions; Reasoning in Description Logics; Reasoning Problems; Closed vs Open World Assumption; Reasoning Techniques; Pellet; Tableau Algorithm; Explanation finding; Pinpointing formula; Conclusions; Probabilistic Description Logics; Introduction; The Distribution Semantics for Description Logics: DISPONTE; Syntax; Semantics; Assumption of Independence; Related Work; Conclusions; Inference in Probabilistic Logics; Decision Diagrams; Introduction; Multivalued Decision Diagrams; Binary Decision Diagrams; Conclusions. | |
| 505 | 8 | |a Fundamentals of Exact Probabilistic Logical InferenceInference Approaches; Exact Probabilistic Logical Inference; Splitting Algorithm; Inference with Multi-valued Decision Diagrams; Inference with Binary Decision Diagrams; Conclusions; Inference in Probabilistic Logic Programming; Introduction; cplint; Exact Inference: the PITA module; Approximate Inference: the MCINTYRE module; Causal Inference with cplint; Causal Inference in PLP; Causal Exact Inference with cplint; Causal Approximate Inference with cplint; Notable Examples; Simpson's Paradox; Viral Marketing; Experiments. | |
| 505 | 8 | |a Hybrid Probabilistic Logic Programs with cplintSampling the Arguments of Unconditional Queries over Hybrid Programs; Conditional Queries over Hybrid Logic Programs; cplint on SWISH: a Web interface for cplint; SWISH; cplint on SWISH; Examples; Related Work; Work on causality inference; Work on Hybrid Probabilistic Logic Programs; Web application for PLP; Conclusions; Inference in Probabilistic Description Logics; Introduction; BUNDLE; How to use BUNDLE; TRILL; TRILLP; How to use TRILL and TRILLP; TRILL on SWISH; Inference Complexity; Experiments; Comparing the Systems; Related Work. | |
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| contents | Intro; Title Page; Abstract; Acknowledgements; Contents; List of Figures; List of Tables; List of Algorithms; List of Acronyms; Introduction; Motivation; Aims of the Thesis; Structure of the Thesis; Structure; Thesis Contributions; Inference in Probabilistic Logic Programming; Inference in Probabilistic Description Logics; Learning Systems in Probabilistic Logic Programming; Learning Systems in Probabilistic Description Logics; How to read this thesis; Probabilistic Logics; Fundamentals of First-Order Logic and Logic Programming; Introduction; First-Order Logic; Syntax; Tarski's semantics. Logic ProgrammingProlog; Normal Logic Programs; First-Order Logic vs Logic Programs; Conclusions; Distribution Semantics; Introduction; Formal Definition; Conclusions; Probabilistic Logic Programming Languages; Introduction; Logic Programs with Annotated Disjunctions; LPADs Syntax; LPADs Semantics; ProbLog; ProbLog Syntax; Conclusions; Description Logics and OWL; Introduction; Description Logics; Syntax; Concept and Role Constructors; Concept Constructors; Role constructors; Knowledge Base; Nomenclature; Semantics; Decidability of Description Logics; Description Logics and First-Order Logic. The OWL Ontology LanguageOWL Syntax; OWL sublanguages; Tools for OWL; Conclusions; Reasoning in Description Logics; Reasoning Problems; Closed vs Open World Assumption; Reasoning Techniques; Pellet; Tableau Algorithm; Explanation finding; Pinpointing formula; Conclusions; Probabilistic Description Logics; Introduction; The Distribution Semantics for Description Logics: DISPONTE; Syntax; Semantics; Assumption of Independence; Related Work; Conclusions; Inference in Probabilistic Logics; Decision Diagrams; Introduction; Multivalued Decision Diagrams; Binary Decision Diagrams; Conclusions. Fundamentals of Exact Probabilistic Logical InferenceInference Approaches; Exact Probabilistic Logical Inference; Splitting Algorithm; Inference with Multi-valued Decision Diagrams; Inference with Binary Decision Diagrams; Conclusions; Inference in Probabilistic Logic Programming; Introduction; cplint; Exact Inference: the PITA module; Approximate Inference: the MCINTYRE module; Causal Inference with cplint; Causal Inference in PLP; Causal Exact Inference with cplint; Causal Approximate Inference with cplint; Notable Examples; Simpson's Paradox; Viral Marketing; Experiments. Hybrid Probabilistic Logic Programs with cplintSampling the Arguments of Unconditional Queries over Hybrid Programs; Conditional Queries over Hybrid Logic Programs; cplint on SWISH: a Web interface for cplint; SWISH; cplint on SWISH; Examples; Related Work; Work on causality inference; Work on Hybrid Probabilistic Logic Programs; Web application for PLP; Conclusions; Inference in Probabilistic Description Logics; Introduction; BUNDLE; How to use BUNDLE; TRILL; TRILLP; How to use TRILL and TRILLP; TRILL on SWISH; Inference Complexity; Experiments; Comparing the Systems; Related Work. |
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| series2 | Studies on the semantic web ; |
| spelling | Cota, Giuseppe, author. Inference and learning systems for uncertain relational data / Giuseppe Cota. Amsterdam, Netherlands : IOS Press, 2018. 1 online resource text txt rdacontent computer c rdamedia online resource cr rdacarrier Studies on the semantic web ; vol. 035 Includes bibliographical references. Online resource; title from PDF title page (IOS Press, viewed August 24, 2018). Intro; Title Page; Abstract; Acknowledgements; Contents; List of Figures; List of Tables; List of Algorithms; List of Acronyms; Introduction; Motivation; Aims of the Thesis; Structure of the Thesis; Structure; Thesis Contributions; Inference in Probabilistic Logic Programming; Inference in Probabilistic Description Logics; Learning Systems in Probabilistic Logic Programming; Learning Systems in Probabilistic Description Logics; How to read this thesis; Probabilistic Logics; Fundamentals of First-Order Logic and Logic Programming; Introduction; First-Order Logic; Syntax; Tarski's semantics. Logic ProgrammingProlog; Normal Logic Programs; First-Order Logic vs Logic Programs; Conclusions; Distribution Semantics; Introduction; Formal Definition; Conclusions; Probabilistic Logic Programming Languages; Introduction; Logic Programs with Annotated Disjunctions; LPADs Syntax; LPADs Semantics; ProbLog; ProbLog Syntax; Conclusions; Description Logics and OWL; Introduction; Description Logics; Syntax; Concept and Role Constructors; Concept Constructors; Role constructors; Knowledge Base; Nomenclature; Semantics; Decidability of Description Logics; Description Logics and First-Order Logic. The OWL Ontology LanguageOWL Syntax; OWL sublanguages; Tools for OWL; Conclusions; Reasoning in Description Logics; Reasoning Problems; Closed vs Open World Assumption; Reasoning Techniques; Pellet; Tableau Algorithm; Explanation finding; Pinpointing formula; Conclusions; Probabilistic Description Logics; Introduction; The Distribution Semantics for Description Logics: DISPONTE; Syntax; Semantics; Assumption of Independence; Related Work; Conclusions; Inference in Probabilistic Logics; Decision Diagrams; Introduction; Multivalued Decision Diagrams; Binary Decision Diagrams; Conclusions. Fundamentals of Exact Probabilistic Logical InferenceInference Approaches; Exact Probabilistic Logical Inference; Splitting Algorithm; Inference with Multi-valued Decision Diagrams; Inference with Binary Decision Diagrams; Conclusions; Inference in Probabilistic Logic Programming; Introduction; cplint; Exact Inference: the PITA module; Approximate Inference: the MCINTYRE module; Causal Inference with cplint; Causal Inference in PLP; Causal Exact Inference with cplint; Causal Approximate Inference with cplint; Notable Examples; Simpson's Paradox; Viral Marketing; Experiments. Hybrid Probabilistic Logic Programs with cplintSampling the Arguments of Unconditional Queries over Hybrid Programs; Conditional Queries over Hybrid Logic Programs; cplint on SWISH: a Web interface for cplint; SWISH; cplint on SWISH; Examples; Related Work; Work on causality inference; Work on Hybrid Probabilistic Logic Programs; Web application for PLP; Conclusions; Inference in Probabilistic Description Logics; Introduction; BUNDLE; How to use BUNDLE; TRILL; TRILLP; How to use TRILL and TRILLP; TRILL on SWISH; Inference Complexity; Experiments; Comparing the Systems; Related Work. Logic programming. http://id.loc.gov/authorities/subjects/sh86003454 Programmation logique. COMPUTERS Programming General. bisacsh Logic programming fast IOS Press. http://id.loc.gov/authorities/names/no2015091156 Studies on the Semantic Web ; vol. 035. http://id.loc.gov/authorities/names/no2009156151 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1876775 Volltext |
| spellingShingle | Cota, Giuseppe Inference and learning systems for uncertain relational data / Studies on the Semantic Web ; Intro; Title Page; Abstract; Acknowledgements; Contents; List of Figures; List of Tables; List of Algorithms; List of Acronyms; Introduction; Motivation; Aims of the Thesis; Structure of the Thesis; Structure; Thesis Contributions; Inference in Probabilistic Logic Programming; Inference in Probabilistic Description Logics; Learning Systems in Probabilistic Logic Programming; Learning Systems in Probabilistic Description Logics; How to read this thesis; Probabilistic Logics; Fundamentals of First-Order Logic and Logic Programming; Introduction; First-Order Logic; Syntax; Tarski's semantics. Logic ProgrammingProlog; Normal Logic Programs; First-Order Logic vs Logic Programs; Conclusions; Distribution Semantics; Introduction; Formal Definition; Conclusions; Probabilistic Logic Programming Languages; Introduction; Logic Programs with Annotated Disjunctions; LPADs Syntax; LPADs Semantics; ProbLog; ProbLog Syntax; Conclusions; Description Logics and OWL; Introduction; Description Logics; Syntax; Concept and Role Constructors; Concept Constructors; Role constructors; Knowledge Base; Nomenclature; Semantics; Decidability of Description Logics; Description Logics and First-Order Logic. The OWL Ontology LanguageOWL Syntax; OWL sublanguages; Tools for OWL; Conclusions; Reasoning in Description Logics; Reasoning Problems; Closed vs Open World Assumption; Reasoning Techniques; Pellet; Tableau Algorithm; Explanation finding; Pinpointing formula; Conclusions; Probabilistic Description Logics; Introduction; The Distribution Semantics for Description Logics: DISPONTE; Syntax; Semantics; Assumption of Independence; Related Work; Conclusions; Inference in Probabilistic Logics; Decision Diagrams; Introduction; Multivalued Decision Diagrams; Binary Decision Diagrams; Conclusions. Fundamentals of Exact Probabilistic Logical InferenceInference Approaches; Exact Probabilistic Logical Inference; Splitting Algorithm; Inference with Multi-valued Decision Diagrams; Inference with Binary Decision Diagrams; Conclusions; Inference in Probabilistic Logic Programming; Introduction; cplint; Exact Inference: the PITA module; Approximate Inference: the MCINTYRE module; Causal Inference with cplint; Causal Inference in PLP; Causal Exact Inference with cplint; Causal Approximate Inference with cplint; Notable Examples; Simpson's Paradox; Viral Marketing; Experiments. Hybrid Probabilistic Logic Programs with cplintSampling the Arguments of Unconditional Queries over Hybrid Programs; Conditional Queries over Hybrid Logic Programs; cplint on SWISH: a Web interface for cplint; SWISH; cplint on SWISH; Examples; Related Work; Work on causality inference; Work on Hybrid Probabilistic Logic Programs; Web application for PLP; Conclusions; Inference in Probabilistic Description Logics; Introduction; BUNDLE; How to use BUNDLE; TRILL; TRILLP; How to use TRILL and TRILLP; TRILL on SWISH; Inference Complexity; Experiments; Comparing the Systems; Related Work. Logic programming. http://id.loc.gov/authorities/subjects/sh86003454 Programmation logique. COMPUTERS Programming General. bisacsh Logic programming fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh86003454 |
| title | Inference and learning systems for uncertain relational data / |
| title_auth | Inference and learning systems for uncertain relational data / |
| title_exact_search | Inference and learning systems for uncertain relational data / |
| title_full | Inference and learning systems for uncertain relational data / Giuseppe Cota. |
| title_fullStr | Inference and learning systems for uncertain relational data / Giuseppe Cota. |
| title_full_unstemmed | Inference and learning systems for uncertain relational data / Giuseppe Cota. |
| title_short | Inference and learning systems for uncertain relational data / |
| title_sort | inference and learning systems for uncertain relational data |
| topic | Logic programming. http://id.loc.gov/authorities/subjects/sh86003454 Programmation logique. COMPUTERS Programming General. bisacsh Logic programming fast |
| topic_facet | Logic programming. Programmation logique. COMPUTERS Programming General. Logic programming |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1876775 |
| work_keys_str_mv | AT cotagiuseppe inferenceandlearningsystemsforuncertainrelationaldata AT iospress inferenceandlearningsystemsforuncertainrelationaldata |