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Machine Learning-Friendly Biomedical Datasets for Equivalence and Subsumption Ontology Matching. (arXiv:2205.03447v2 [cs.AI] UPDATED)
cs.LG updates on arXiv.org arxiv.org
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.
Although the Ontology Alignment Evaluation Initiative (OAEI) represents an
impressive effort for the systematic evaluation of OM systems, it still suffers
from several limitations including limited evaluation of subsumption mappings,
suboptimal reference mappings, and limited support for the evaluation of
ML-based systems. To tackle these limitations, we …
ai arxiv biomedical datasets learning machine machine learning ontology