Semantic Web - ISWC 2024

Semantic Web - ISWC 2024

23rd International Semantic Web Conference, Baltimore, MD, USA, November 11-15, 2024, Proceedings, Part III

Palmonari, Matteo; Demartini, Gianluca; Cheng, Gong; Skaf-Molli, Hala; Ferranti, Nicolas; Hernandez, Daniel; Hose, Katja; Acosta, Maribel; Hogan, Aidan

Springer International Publishing AG

12/2024

500

Mole

9783031778469

Pré-lançamento - envio 15 a 20 dias após a sua edição

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.- Resource Track.



.- SparkKG-ML: A Library to Facilitate end-to-end Large-scale Machine Learning over Knowledge Graphs in Python.



.- KROWN: A Benchmark for RDF Graph Materialisation.



.- KGHeartBeat: a Knowledge Graph Quality Assessment Tool.



.- InstructIE: A Bilingual Instruction-based Information Extraction Dataset.



.- Diachronical geometry without polygons: the extended HHT ontology for heterogeneous geometrical representations.



.- CimpleKG: A Continuously Updated Knowledge Graph on Misinformation, Factors and Fact-Checks.



.- AutoRDF2GML: Facilitating RDF Integration in Graph Machine Learning.



.- SciHyp: A Fine-grained Dataset Describing Hypotheses and Their Components from Scientific Articles.



.- The ICS-SEC KG: An Integrated Cybersecurity Resource for Industrial Control Systems.



.- Data Privacy Vocabulary (DPV) - Version 2.0.



.- In-Use Track.



.- Developing Application Profiles for Enhancing Data and Workflows in Cultural Heritage Digitisation Processes.



.- Intelligent Urban Traffic Management via Semantic Interoperability across Multiple Heterogeneous Mobility Data Sources.



.- Quality in Color: Using Knowledge Graphs for Enhanced Quality Control in an Automotive Paintshop.



.- UFEL: a By-design Understandable and Frugal Entity Linking System for French Microposts.



.- Leveraging Knowledge Graphs for Earth System Dataset Discovery.



.- Semantic and technically interoperable data exchange in the Flanders Smart Data Space.



.- Integrating Large Language Models and Knowledge Graphs for Extraction and Validation of Textual Test Data.



.- Increasing the Accuracy of LLM Question-Answering Systems on SQL Databases with Ontologies.
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