7 papers
Aligning Biomedical Texts and Knowledge Graphs: A Systematic Comparison of Lightweight Alignment Strategies
Artem Bisliouk, Elizaveta Nosova, Heiko Paulheim +2
Biomedical knowledge exists in two complementary but distinct forms: unstructured scientific literature and structured knowledge graphs (KGs). Aligning them is essential for knowle…
Integrating Meta-Features with Knowledge Graph Embeddings for Meta-Learning
Antonis Klironomos, Ioannis Dasoulas, Francesco Periti +4
The vast collection of machine learning records available on the web presents a significant opportunity for meta-learning, where past experiments are leveraged to improve performan…
Improving Knowledge Graph Embeddings through Contrastive Learning with Negative Statements
Rita T. Sousa, Heiko Paulheim
Knowledge graphs represent information as structured triples and serve as the backbone for a wide range of applications, including question answering, link prediction, and recommen…
Bio-KGvec2go: Serving up-to-date Dynamic Biomedical Knowledge Graph Embeddings
Hamid Ahmad, Heiko Paulheim, Rita T. Sousa
Knowledge graphs and ontologies represent entities and their relationships in a structured way, having gained significance in the development of modern AI applications. Integrating…
Knowledge Graph Completion for Action Prediction on Situational Graphs -- A Case Study on Household Tasks
Mariam Arustashvili, Jörg Deigmöller, Heiko Paulheim
Knowledge Graphs are used for various purposes, including business applications, biomedical analyses, or digital twins in industry 4.0. In this paper, we investigate knowledge grap…
Analysing semantic data storage in Distributed Ledger Technologies for Data Spaces
Juan Cano-Benito, Andrea Cimmino, Sven Hertling +2
Data spaces are emerging as decentralised infrastructures that enable sovereign, secure, and trustworthy data exchange among multiple participants. To achieve semantic interoperabi…