ONTOCONNECT: Domain-Agnostic Ontology Alignment using Graph Embedding with Negative Sampling

J. Chakraborty, H.M. Zahera, M.A. Sherif, S.K. Bansal, in: 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA), IEEE, 2022.

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Chakraborty, Jaydeep; Zahera, Hamada M.; Sherif, Mohamed Ahmed; Bansal, Srividya K.
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2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA)
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Chakraborty J, Zahera HM, Sherif MA, Bansal SK. ONTOCONNECT: Domain-Agnostic Ontology Alignment using Graph Embedding with Negative Sampling. In: 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA). IEEE; 2022. doi:10.1109/icmla52953.2021.00155
Chakraborty, J., Zahera, H. M., Sherif, M. A., & Bansal, S. K. (2022). ONTOCONNECT: Domain-Agnostic Ontology Alignment using Graph Embedding with Negative Sampling. 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA). https://doi.org/10.1109/icmla52953.2021.00155
@inproceedings{Chakraborty_Zahera_Sherif_Bansal_2022, title={ONTOCONNECT: Domain-Agnostic Ontology Alignment using Graph Embedding with Negative Sampling}, DOI={10.1109/icmla52953.2021.00155}, booktitle={2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA)}, publisher={IEEE}, author={Chakraborty, Jaydeep and Zahera, Hamada M. and Sherif, Mohamed Ahmed and Bansal, Srividya K.}, year={2022} }
Chakraborty, Jaydeep, Hamada M. Zahera, Mohamed Ahmed Sherif, and Srividya K. Bansal. “ONTOCONNECT: Domain-Agnostic Ontology Alignment Using Graph Embedding with Negative Sampling.” In 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA). IEEE, 2022. https://doi.org/10.1109/icmla52953.2021.00155.
J. Chakraborty, H. M. Zahera, M. A. Sherif, and S. K. Bansal, “ONTOCONNECT: Domain-Agnostic Ontology Alignment using Graph Embedding with Negative Sampling,” 2022, doi: 10.1109/icmla52953.2021.00155.
Chakraborty, Jaydeep, et al. “ONTOCONNECT: Domain-Agnostic Ontology Alignment Using Graph Embedding with Negative Sampling.” 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA), IEEE, 2022, doi:10.1109/icmla52953.2021.00155.

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