Meroño Peñuela / Celino / Corcho | The Semantic Web: ESWC 2024 Satellite Events | Buch | 978-3-031-78951-9 | sack.de

Buch, Englisch, Band 15344, 348 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 575 g

Reihe: Lecture Notes in Computer Science

Meroño Peñuela / Celino / Corcho

The Semantic Web: ESWC 2024 Satellite Events

Hersonissos, Crete, Greece, May 26-30, 2024, Proceedings, Part I
Erscheinungsjahr 2025
ISBN: 978-3-031-78951-9
Verlag: Springer Nature Switzerland

Hersonissos, Crete, Greece, May 26-30, 2024, Proceedings, Part I

Buch, Englisch, Band 15344, 348 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 575 g

Reihe: Lecture Notes in Computer Science

ISBN: 978-3-031-78951-9
Verlag: Springer Nature Switzerland


This two volume set constitutes the refereed proceedings of the International Conference, ESWC 2024 Satellite Events, held in Hersonissos, Crete, Greece during May 26–30, 2024.

The 67 papers presented were carefully reviewed and selected from 128 submissions. This year conference aimed at acknowledging recent developments in AI with a special tagline, “Fabrics of Knowledge: Knowledge Graphs and Generative AI”. To reflect this year’s special topic, the satellite events of ESWC 2024 featured a Special Track on Large Language Models for Knowledge Engineering, in addition to the poster and demo session, the PhD symposium, the industry track, project networking, and workshops and tutorials. 

Meroño Peñuela / Celino / Corcho The Semantic Web: ESWC 2024 Satellite Events jetzt bestellen!

Zielgruppe


Research

Weitere Infos & Material


.- Special Track on Large Language Models for Knowledge Engineering.

.- The Role of Generative AI in Competency Question Retrofitting.

.- Evaluating Class Membership Relations in Knowledge Graphs using Large Language Models.

.- LLMs4OM: Matching Ontologies with Large Language Models.

.- NeOn-GPT: A Large Language Model-Powered Pipeline for Ontology Learning.

.- Assessing the Evolution of LLM capabilities for Knowledge Graph Engineering in 2023.

.- Column Property Annotation using Large Language Models.

.- Can LLMs Generate Competency Questions?.

.- 12 shades of RDF: Impact of Syntaxes on Data Extraction with Language Models.

.- Validating Semantic Artifacts With Large Language Models.

.- OntoChat: a Framework for Conversational Ontology Engineering using Language Models.

.- Industry.

.- Dataset Management Powered by Semantic Web Technologies.

.- Optimizing Aerospace Product Maintenance: A Novel Multi-Modal Knowledge Graph and LLM Approach for Enhanced Decision Support.

.- LLM-based Guided Generation of Ontology Term Definitions.

.- Towards Solid-based B2B Data Value Chains.

.- Rapid Graph Generation from Job Descriptions: combining Taxonomies and LLMs.

.- FAIR Internet of Things Data: Enabling Process Optimization at Munich Airport.

.- Product Information Management Systems Powered by Knowledge Graphs.

.- Posters & Demos.

.- ArtSampo – Finnish Art on the Semantic Web.

.- Towards Semantic Annotation for Scientific Datasets.

.- A Framework for Question Answering on Knowledge Graphs Using Large Language Models.

.- KinGVisher – Knowledge Graph Visualizer.

.- Gotta Catch’em All: From Data Silos to a Knowledge Graph.

.- The Helmholtz Knowledge Graph: driving the Transition towards a FAIR Data Ecosystem in the Helmholtz Association.

.- Data Search and Discovery in RDF Sources.

.- MLSeascape: Search over Machine Learning Metadata Empowered by Knowledge Graphs.

.- SCOOP-UI: SHACL Shape Extraction in Just a Click.

.- Converter: Enhancing Interoperability in Research Data Management.

.- RDFminer: an Interactive Tool for the Evolutionary Discovery of SHACL Shapes.

.- MusicBO, an application of Text2AMR2FRED to the Musical Heritage
domain.

.- RDF2vec Embeddings for Updateable Knowledge Graphs - Reuse, don’t Retrain!.

.- Critical Path Identification in Supply Chain Knowledge Graphs with Large Language Models.

.- Observations on Bloom Filters for Traversal-Based Query Execution over Solid Pods.

.- Datatypes for Lists and Maps in RDF Literals.

.- OAEI Machine Learning Dataset for Online Model Generation.

.- Searching and analyzing cross-border multilingual legislation on the Semantic Web.

.- CLARA search engine: Linking Licensed Educational Resources.

.- A Method and a Library for Visual Data Schemas.

.- Ontogenia: Ontology Generation with Metacognitive Prompting in Large Language Models.

.- Optimizing Class Subsumption through Controlled Dynamics of n-Balls in Vector Space.

.- KGSnap!: query Knowledge Graphs by Snap!.

.- KGHeartBeat: a Knowledge Graph Quality Assessment Tool.

.- CLASS MATE: Cross-Lingual Semantic Search for Material Science driven by Knowledge Graphs.

.- When Ontologies met Knowledge Graphs: Tale of a Methodology.

.- From Liberating to Questioning Tabular Data in Documents Using Knowledge Graphs.

.- Searching and Analyzing Coin Finds with Linked Data Based Web Application.

.- PySPARQL Anything Showcase.

.- Integrating Action Robot Ontology for Enhanced Human-Robot Interaction: A NAO Robot Case Study.

.- Semantic Tool Hub: Towards A Sustainable Community-Driven Documentation of Semantic Web Tools.

.- German Tourism Knowledge Graph.

.- Finding Root Causes for Outliers in Semantically Annotated Sensor Data.

.- RMLdoc: Documenting Mapping Rules for Knowledge Graph Construction.

.- Granular Access to Policy-Governed Linked Data via Partial Server-Side Query.

.- Taking Control of Your Health Data: A Solid-based Mobile App for Wearable Data Collection and RDF Visualization.

.- Compatibility Challenges of the Current State-of-the-Art Provenance Tools.



Ihre Fragen, Wünsche oder Anmerkungen
Vorname*
Nachname*
Ihre E-Mail-Adresse*
Kundennr.
Ihre Nachricht*
Lediglich mit * gekennzeichnete Felder sind Pflichtfelder.
Wenn Sie die im Kontaktformular eingegebenen Daten durch Klick auf den nachfolgenden Button übersenden, erklären Sie sich damit einverstanden, dass wir Ihr Angaben für die Beantwortung Ihrer Anfrage verwenden. Selbstverständlich werden Ihre Daten vertraulich behandelt und nicht an Dritte weitergegeben. Sie können der Verwendung Ihrer Daten jederzeit widersprechen. Das Datenhandling bei Sack Fachmedien erklären wir Ihnen in unserer Datenschutzerklärung.