This repository is an extension of GEval.
This repository contains a (software) evaluation framework to perform evaluation and comparison on RDF-star graph embedding techniques.
If you want to run the tools, install Jupyter and run it on your host.
jupyter notebook
Example of Classification Task
run evaluation_rdfstar2vec.ipynb
Example of interpretation of the results
run tutorial_results_interpretation/results_interpretation_rdf-star2vec.py.ipynb
The implemented tasks are:
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Machine Learning
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Semantic tasks
The gold standard datasets for evaluation were created from KGRC-RDF-star. Please see here.
The framework is tested to work with Python 3.8.3.
The required dependencies are: Numpy==1.14.0, Pandas==0.22.0, Scikit-learn==0.19.2, Scipy==1.1.0, H5py==2.8.0, unicodecsv==0.14.1
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The Apache license applies to the extended source code. The CC BY 4.0 applies to the gold standard datasets. The license of the original software can be found here. For source datasets, please check the license information here.