The Semantic Web
Description
This two-volume set LNCS 15718-15719 constitutes the refereed proceedings of the 22nd European Semantic Web Conference, ESWC 2025, held in Portoroz, Slovenia, during June 1-5, 2025.
The 45 full papers presented were carefully reviewed and selected from 155 submissions.The ESWC's Research track addresses the theoretical, analytical, and empirical aspects of the semantic web, semantic technologies, knowledge graphs and semantics on the Web in general. The In-use track focuses on contributions that reuse and apply state-of-the-art semantic technologies or resources to real-world settings. The resource track deals with resource contributions that are, on the one hand innovative or novel, and on the other hand sharable and reusable (e.g. datasets, knowledge graphs, ontologies, workflows, benchmarks, frameworks), and provide the necessary scaffolding to support the generation of scientific work and advance the state of the art.
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Content
Research: An Algebraic Foundation for Knowledge Graph Construction.- Inductive Higher Order Embeddings.- ReaLitE: Enrichment of Relation Embeddings in Knowledge Graphs using Numeric Literals.- Evaluating Approximate Nearest Neighbour Search Systems on Knowledge Graph Embeddings.- On Evaluation Metrics for Complex Matching based on Reference Alignments.- Kastor: Fine-tuned Small Language Models for Shape-based Active Relation Extraction.- Predicting the Road Ahead: A Knowledge Graph based Foundation Model for Scene Understanding in Autonomous Driving.- ANTS: Abstractive Entity Summarization in Knowledge Graphs.- Delete/Rederive with Marking for Update Streams.- Balancing Privacy and Utility: Semantic Anonymization of Time-aware Knowledge Graphs.- Training-free Score Calibration for Complex Query Decomposition.- Information-aware Entity Indexing in Knowledge Graphs to Enable Semantic Search.- Explainable Temporal Fact Validation Through Constraints Discovery in Knowledge Graphs.- Multi-dataset and transfer learning using gene expression knowledge graphs for patient diagnosis.- Robustness Evaluation of Knowledge Graph Embedding Models under Non-targeted Attacks.- Predicting clinical outcomes from patient care pathways represented with temporal knowledge graphs.- AvengER: Ensembling and Fine-Tuning LLMs for Select Prompts in Entity Resolution.- Ontology Generation using Large Language Models.- Towards Practicable Algorithms for Rewriting Graph Queries beyond DL-Lite.- Designing Hierarchies for Optimal Hyperbolic Embedding.- RDF-based Semantics for Selective Disclosure and Zero-knowledge Proofs on Verifiable Credentials.- Taxonomy Inference for Tabular Data Using Large Language Models.- GeoRDF2vec - Learning Location-Aware Entity Representations in Knowledge Graphs.- RelCheck: Improving Relation Extraction with Ontology-Guided and LLM-Based Validation.- Analyzing the Influence of Knowledge Graph Information on Relation Extraction.- Extending Shape Expressions with an inheritance mechanism.