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Author Summer School on Reasoning Web (15th : 2019 : Bolzano, Italy)

Title Reasoning web : explainable artificial intelligence : 15th International Summer School 2019, Bolzano, Italy, September 20-24, 2019, Tutorial lectures / Markus Krötzsch, Daria Stepanova (eds.)
Published Cham, Switzerland : Springer, 2019

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Description 1 online resource (xi, 283 pages) : illustrations (some color)
Series Lecture notes in computer science ; 11810
LNCS sublibrary. SL 3, Information systems and applications, incl. Internet/Web, and HCI
Lecture notes in computer science ; 11810.
LNCS sublibrary. SL 3, Information systems and applications, incl. Internet/Web, and HCI.
Contents Intro; Preface; Organization; Reasoning Web 2019 Sponsors; Contents; Classical Algorithms for Reasoning and Explanation in Description Logics; 1 Introduction; 2 Description Logics; 2.1 Syntax; 2.2 Semantics; 2.3 Reasoning Problems; 2.4 Reductions Between Reasoning Problems; 3 Tableau Procedures; 3.1 Deciding Concept Satisfiability; 3.2 TBox Reasoning; 4 Axiom Pinpointing; 4.1 Computing One Justification; 4.2 Computing All Justifications; 4.3 Computing All Repairs; 4.4 Computing Justifications and Repairs Using SAT Solvers; 5 Summary and Outlook; A Appendix; A.1 Computational Complexity
A.2 Propositional Logic and SATReferences; Explanation-Friendly Query Answering Under Uncertainty; 1 Introduction; 2 The Datalog+/- Family of Ontology Languages; 2.1 Preliminary Concepts and Notations; 2.2 Syntax and Semantics of Datalog+/-; 2.3 Conjunctive Query Answering; 2.4 Datalog+/- Fragments: In Search of Decidability and Tractability; 3 Query Answering over Probabilistic Knowledge Bases; 3.1 Brief Overview of Basic Probabilistic Graphical Models; 3.2 Probabilistic Datalog+/-; 3.3 Towards Explainable Probabilistic Ontological Reasoning
4 Inconsistency-Tolerant Query Answering with Datalog+/-4.1 Relationship with (Classical) Consistent Answers; 4.2 Relationship with IAR Semantics; 4.3 Lazy Answers; 4.4 Towards Explainable Inconsistency-Tolerant Query Answering; 5 Discussion and Future Research Directions; References; Provenance in Databases: Principles and Applications; 1 Introduction; 2 Provenance; 3 Example Applications; 4 Beyond Relational Provenance; 5 Outlook; References; Knowledge Representation and Rule Mining in Entity-Centric Knowledge Bases; 1 Introduction; 1.1 Knowledge Bases; 1.2 Applications
1.3 Knowledge Representation and Rule Mining2 Knowledge Representation; 2.1 Entities; 2.2 Classes; 2.3 Relations; 2.4 Knowledge Bases; 2.5 The Semantic Web; 2.6 Challenges in Knowledge Representation; 3 Rule Mining; 3.1 Rules; 3.2 Rule Mining; 3.3 Rule Mining Approaches; 3.4 Related Approaches; 3.5 Challenges in Rule Mining; 4 Representation Learning; 4.1 Embedding; 4.2 Neural Networks; 4.3 Knowledge Base Embeddings; 4.4 Challenges in Representation Learning; 5 Conclusion; A Computation of Support and Confidence; References; Explaining Data with Formal Concept Analysis; 1 Introduction; 2 TL
DR -- Formal Concept Analysis in a Nutshell3 Concept Lattices; 3.1 Formal Contexts and Cross Tables; 3.2 The Derivation Operators; 3.3 Formal Concepts, Extent and Intent; 3.4 Conceptual Hierarchy; 3.5 Concept Lattice Diagrams; 3.6 Supremum and Infimum; 3.7 Complete Lattices; 3.8 The Basic Theorem of FCA; 3.9 Computing All Concepts of a Context; 3.10 Drawing Concept Lattices; 3.11 Clarifying and Reducing a Formal Context; 3.12 Additive and Nested Line Diagrams; 4 Closure Systems; 4.1 Definition and Examples; 4.2 The Next Closure Algorithm; 5 Implications; 5.1 Implications of a Formal Context
Summary The research areas of Semantic Web, Linked Data, and Knowledge Graphs have recently received a lot of attention in academia and industry. Since its inception in 2001, the Semantic Web has aimed at enriching the existing Web with meta-data and processing methods, so as to provide Web-based systems with intelligent capabilities such as context awareness and decision support. The Semantic Web vision has been driving many community efforts which have invested a lot of resources in developing vocabularies and ontologies for annotating their resources semantically. Besides ontologies, rules have long been a central part of the Semantic Web framework and are available as one of its fundamental representation tools, with logic serving as a unifying foundation. Linked Data is a related research area which studies how one can make RDF data available on the Web and interconnect it with other data with the aim of increasing its value for everybody. Knowledge Graphs have been shown useful not only for Web search (as demonstrated by Google, Bing, etc.) but also in many application domains. -- Provided by publisher
Notes Includes author index
Online resource; title from PDF title page (SpringerLink, viewed September 26, 2019)
Subject Semantic Web -- Congresses
Semantic computing -- Congresses
Semantic computing
Semantic Web
Genre/Form Electronic books
proceedings (reports)
Conference papers and proceedings
Conference papers and proceedings.
Actes de congrès.
Form Electronic book
Author Krötzsch, Markus, editor.
Stepanova, Daria, editor
ISBN 9783030314231
3030314235