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Found 8 papers, 4 papers with code
Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunities
The term life sciences refers to the disciplines that study living organisms and life processes, and include chemistry, biology, medicine, and a range of other related disciplines.
NeSy4VRD: A Multifaceted Resource for Neurosymbolic AI Research using Knowledge Graphs in Visual Relationship Detection
NeSy4VRD is a multifaceted resource designed to support the development of neurosymbolic AI (NeSy) research.
Language Model Analysis for Ontology Subsumption Inference
Investigating whether pre-trained language models (LMs) can function as knowledge bases (KBs) has raised wide research interests recently.
Results of SemTab 2022
SemTab 2022 was the fourth edition of the Semantic Web Challenge on Tabular Data to Knowledge Graph Matching, successfully collocated with the 21st International Semantic Web Conference (ISWC) and the 17th Ontology Matching (OM) Workshop.
Ranked #2 on
Cell Entity Annotation
on ToughTables-WD
Query-based Industrial Analytics over Knowledge Graphs with Ontology Reshaping
Industrial analytics that includes among others equipment diagnosis and anomaly detection heavily relies on integration of heterogeneous production data.
Machine Learning-Friendly Biomedical Datasets for Equivalence and Subsumption Ontology Matching
Ontology Matching (OM) plays an important role in many domains such as bioinformatics and the Semantic Web, and its research is becoming increasingly popular, especially with the application of machine learning (ML) techniques.
Prediction of Adverse Biological Effects of Chemicals Using Knowledge Graph Embeddings
Furthermore, we have implemented a fine-tuning architecture that adapts the knowledge graph embeddings to the effect prediction task and leads to better performance.
Dividing the Ontology Alignment Task with Semantic Embeddings and Logic-based Modules
Large ontologies still pose serious challenges to state-of-the-art ontology alignment systems.
