Introduction published in:
Computational terminology and filtering of terminological information
Edited by Patrick Drouin, Natalia Grabar, Thierry Hamon, Kyo Kageura and Koichi Takeuchi
[Terminology 24:1] 2018
► pp. 1–6
Introduction

Computational terminology and filtering of terminological information

Introduction to the special issue

| Université de Montréal
| Université de Lille
| LIMSI-CNRS | Université Paris 13
| University of Tokyo
| Okayama University
Article outline
  • Content of this special issue
  • Acknowledgements
  • References
Published online: 31 May 2018
https://doi.org/10.1075/term.00010.dro
References
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2001 “A Neural Probabilistic Language Model.” In Advances in Neural Information Processing Systems 13, ed. by Leen, Todd K., Thomas G. Dietterich, and Volker Tresp, 932–938. Cambridge: MIT Press.Google Scholar
Bengio, Yoshua, Ducharme, Réjean, Pascal Vincent, and Christian Jauvin
2003 “A Neural Probabilistic Language Model.” Journal of Machine Learning Research 31: 1137–1155.Google Scholar
Hinton, Geoffrey E.
1986 “Learning Distributed Representations of Concepts.” In Proceedings of the Eighth Annual Conference of the Cognitive Science Society, Amherst, Massachusetts, 1–12. Hillsdale: Erlbaum.Google Scholar
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Young, Tom, Hazarika, Devamanyu, Soujanya Poria, and Erik Cambria
2017 Recent Trends in Deep Learning Based Natural Language Processing. arXiv:1708.02709v4. (http://​arxiv​.org​/abs​/1708​.02709). Accessed 8 February 2018.
Cited by

Cited by 2 other publications

No author info given
2022.  In Theoretical Perspectives on Terminology [Terminology and Lexicography Research and Practice, 23], Crossref logo
Rigouts Terryn, Ayla, Véronique Hoste & Els Lefever
2020. In no uncertain terms: a dataset for monolingual and multilingual automatic term extraction from comparable corpora. Language Resources and Evaluation 54:2 ► pp. 385 ff. Crossref logo

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