Rules and Reasoning

8th International Joint Conference, RuleML+RR 2024, Bucharest, Romania, September 16–18, 2024, Proceedings

AvSabrina Kirrane,Mantas Šimkus

Häftad, Engelska, 2024

Del 15183 i serien Lecture Notes in Computer Science

706 kr

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Beskrivning

This book constitutes the proceedings of the 8th International Joint Conference on Rules and Reasoning, RuleML+RR 2024, held in Bucharest, Romania, during September 16-18, 2024.The 12 full papers and 4 short papers included in this book were carefully reviewed and selected from 35 submissions.The RuleML+RR symposia were devoted to disseminating research, applications, languages, and standards for rule technologies, with attention to both theoretical and practical developments, to challenging new ideas and to industrial applications.

Produktinformation

Utgivningsdatum:2024-09-15
Mått:155 x 235 x 15 mm
Vikt:417 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:250
Förlag:Springer International Publishing AG
ISBN:9783031724060

Utforska kategorier

Innehållsförteckning

.- Using Answer Set Programming for Integrity Maintenance in a Smart Home System..- Collaborative Benchmarking Rule-Reasoners with B-Runner..- Rule Confidence Aggregation for Knowledge Graph Completion..- RIFF: Inducing Rules for Fraud Detection from Decision Trees..- Ontology-Based Update in Virtual Knowledge Graphs via Schema Mapping Recovery..- Reevaluation of Inductive Link Prediction..- Judicial Explanations..- OntoRaster: Extending VKGs with Raster Data..- Complete Approximations of Incomplete Queries..- Reasoning in Rough Description Logics with Multiple Indiscernibility Relations..- A Benchmark for Rule Induction in Automated Business Decisions..- Revising Defeasible Theories via Instructions..- FaithEL: Strongly Faithful Knowledge Base Embeddings for ELH..- RDF Surfaces as a First-Order language for the Semantic Web..- Ambiguities in Defeasible Logic: A computational efficient framework and algorithms..- Legally-Guided Automated Decision-Making System Using Language Model Agents for Autonomous Driving.