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Integrating deep learning techniques, particularly language models (LMs), with knowledge representation techniques like ontologies has raised widespread attention, urging the need of a platform that supports both paradigms.
T. Brown, B. Mann, N. Ryder, M. Subbiah, J.D. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell et al., Language models are few-shot learners, Advances in neural information processing systems
1901
Earlier work this paper cites.
J.J. Carroll, I. Dickinson, C. Dollin, D. Reynolds, A. Seaborne and K. Wilkinson, Jena: implementing the semantic web recommendations, in: Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
2004
Earlier work this paper cites.
O. Bodenreider, The unified medical language system (UMLS): integrating biomedical terminology, Nucleic acids research
2004
Earlier work this paper cites.
F. Baader, S. Brandt and C. Lutz, Pushing the EL envelope, in: Proceedings of the 19th international joint conference on Artificial intelligence
2005
Earlier work this paper cites.
K. Donnelly et al., SNOMED-CT: The advanced terminology and coding system for eHealth, Studies in health technology and informatics
2006
Earlier work this paper cites.
M. d’Aquin, A. Schlicht, H. Stuckenschmidt and M. Sabou, Ontology modularization for knowledge selection: Experiments and evaluations, in: Database and Expert Systems Applications: 18th International Conference, DEXA 2007, Regensburg, Germany, September 3-7, 2007. Proceedings 18
2007
Earlier work this paper cites.
N. Sioutos, S. de Coronado, M.W. Haber, F.W. Hartel, W.-L. Shaiu and L.W. Wright, NCI Thesaurus: a semantic model integrating cancer-related clinical and molecular information, Journal of biomedical informatics
2007
Earlier work this paper cites.
C. Rosse and J.L. Mejino Jr, The foundational model of anatomy ontology, in: Anatomy ontologies for bioinformatics: principles and practice
2008
Earlier work this paper cites.
B. Motik, B.C. Grau, I. Horrocks, Z. Wu, A. Fokoue, C. Lutz et al., OWL 2 web ontology language profiles, W3C recommendation
2009
Earlier work this paper cites.
S. Staab and R. Studer, Handbook on ontologies
2010
Earlier work this paper cites.
G. Alterovitz, M. Xiang, D.P. Hill, J. Lomax, J. Liu, M. Cherkassky, J. Dreyfuss, C. Mungall, M.A. Harris, M.E. Dolan et al., Ontology engineering, Nature biotechnology
2010
Earlier work this paper cites.
E. Jiménez-Ruiz and B. Cuenca Grau, Logmap: Logic-based and scalable ontology matching, in: The Semantic Web–ISWC 2011: 10th International Semantic Web Conference, Bonn, Germany, October 23-27, 2011, Proceedings, Part I 10
2011
Earlier work this paper cites.
M. Horridge and S. Bechhofer, The owl api: A java api for owl ontologies, Semantic web
2011
Earlier work this paper cites.
Y. Kazakov, M. Krötzsch and F. Simančík, ELK: A Reasoner for OWL EL Ontologies, System Description, University of Oxford, 2012, available from http://code.google.com/p/elk-reasoner/wiki/Publications
2012
Earlier work this paper cites.
L.M. Schriml, C. Arze, S. Nadendla, Y.-W.W. Chang, M. Mazaitis, V. Felix, G. Feng and W. Kibbe, Disease Ontology: a backbone for disease semantic integration, Nucleic Acids Research
2012
Earlier work this paper cites.
B. Glimm, I. Horrocks, B. Motik, G. Stoilos and Z. Wang, HermiT: an OWL 2 reasoner, Journal of Automated Reasoning
2014
Earlier work this paper cites.
D. Vasant, L. Chanas, J. Malone, M. Hanauer, A. Olry, S. Jupp, P.N. Robinson, H. Parkinson and A. Rath, Ordo: an ontology connecting rare disease, epidemiology and genetic data, in: Proceedings of ISMB
2014
Earlier work this paper cites.
M.A. Musen, The protégé project: a look back and a look forward, AI matters
2015
Earlier work this paper cites.
J.S. Amberger, C.A. Bocchini, F. Schiettecatte, A.F. Scott and A. Hamosh, OMIM. org: Online Mendelian Inheritance in Man (OMIM®), an online catalog of human genes and genetic disorders, Nucleic acids research
2015
Earlier work this paper cites.
M. Abadi, TensorFlow: learning functions at scale, in: Proceedings of the 21st ACM SIGPLAN International Conference on Functional Programming
2016
Earlier work this paper cites.
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A.N. Gomez, Ł. Kaiser and I. Polosukhin, Attention is all you need, Advances in neural information processing systems
2017
Cited alongside, same era.
E. Choi, M.T. Bahadori, L. Song, W.F. Stewart and J. Sun, GRAM: graph-based attention model for healthcare representation learning, in: Proceedings of the 23rd ACM SIGKDD international conference on knowledge discovery and data mining
2017
Cited alongside, same era.
J.-B. Lamy, Owlready: Ontology-oriented programming in Python with automatic classification and high level constructs for biomedical ontologies, Artificial intelligence in medicine
2017
Cited alongside, same era.
A. Gulli and S. Pal, Deep learning with Keras
2017
Cited alongside, same era.
A. Soylu, E. Kharlamov, D. Zheleznyakov, E. Jimenez-Ruiz, M. Giese, M.G. Skjæveland, D. Hovland, R. Schlatte, S. Brandt, H. Lie et al., OptiqueVQS: A visual query system over ontologies for industry, Semantic Web
Y. He, J. Chen, D. Antonyrajah and I. Horrocks, BERTMap: a BERT-based ontology alignment system, in: Proceedings of the AAAI Conference on Artificial Intelligence
2022
Later among the works it cites.
2022
Later among the works it cites.
Y. He, J. Chen, H. Dong, E. Jiménez-Ruiz, A. Hadian and I. Horrocks, Machine Learning-Friendly Biomedical Datasets for Equivalence and Subsumption Ontology Matching, in: The Semantic Web–ISWC 2022: 21st International Semantic Web Conference, Virtual Event, October 23–27, 2022, Proceedings
2022
Later among the works it cites.
M.A.N. Pour, A. Algergawy, P. Buche, L.J. Castro, J. Chen, H. Dong, O. Fallatah, D. Faria, I. Fundulaki, S. Hertling, Y. He, I. Horrocks, M. Huschka, L. Ibanescu, E. Jiménez-Ruiz, N. Karam, A. Laadhar, P. Lambrix, H. Li, Y. Li, F. Michel, E. Nasr, H. Paulheim, C. Pesquita, T. Saveta, P. Shvaiko, C. Trojahn, C. Verhey, M. Wu, B. Yaman, O. Zamazal and L. Zhou, Results of the Ontology Alignment Evaluation Initiative 2022, in: OM@ISWC
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2018
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2018
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N. Li, Z. Bouraoui and S. Schockaert, Ontology completion using graph convolutional networks, in: The Semantic Web–ISWC 2019: 18th International Semantic Web Conference, Auckland, New Zealand, October 26–30, 2019, Proceedings, Part I 18
2019
Cited alongside, same era.
A. Paszke, S. Gross, F. Massa, A. Lerer, J. Bradbury, G. Chanan, T. Killeen, Z. Lin, N. Gimelshein, L. Antiga et al., Pytorch: An imperative style, high-performance deep learning library, Advances in neural information processing systems
2019
Cited alongside, same era.
R.C. Jackson, J.P. Balhoff, E. Douglass, N.L. Harris, C.J. Mungall and J.A. Overton, ROBOT: a tool for automating ontology workflows, BMC bioinformatics
2019
Cited alongside, same era.
2019
Cited alongside, same era.
2019
Cited alongside, same era.
2019
Cited alongside, same era.
2022
Later among the works it cites.
J. Chen, Y. He, Y. Geng, E. Jiménez-Ruiz, H. Dong and I. Horrocks, Contextual semantic embeddings for ontology subsumption prediction, World Wide Web
2023
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H. Rashkin, V. Nikolaev, M. Lamm, L. Aroyo, M. Collins, D. Das, S. Petrov, G.S. Tomar, I. Turc and D. Reitter, Measuring attribution in natural language generation models, Computational Linguistics
2023
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F. Zhapa-Camacho, M. Kulmanov and R. Hoehndorf, mOWL: Python library for machine learning with biomedical ontologies, Bioinformatics
2023
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OpenAI, GPT-4 Technical Report, ArXiv
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