Practical examples demonstrating various ontology alignment and matching techniques using OntoAligner.
OntoAligner Pattern:
# 1. Load dataset
task = MaterialInformationMatOntoOMDataset()
dataset = task.collect(source_ontology_path="...", target_ontology_path="...", reference_matching_path="...")
# 2. Encode
encoder = ConceptParentLightweightEncoder()
encoded = encoder(source=dataset['source'], target=dataset['target'])
# 3. Align
aligner = SomeAligner()
matchings = aligner.generate(input_data=encoded)
# 4. Evaluate
metrics.evaluation_report(predicts=matchings, references=dataset['reference'])Run any example:
python fuzzy_matching.py📖 Related Resources:
- Documentation: https://ontoaligner.readthedocs.io
- PyPI: https://pypi.org/project/OntoAligner/
- Tutorial: See tutorial/ directory
- GitHub: https://github.com/sciknoworg/OntoAligner