datasets-CNRS/ThesoTM huggingface dataset:
doc2vec R / doc2vec R
Definition: "an R package allowing to build Paragraph Vector models also known as doc2vec models." (source : https://github.com/bnosac/doc2vec)
Définition : « package R permettant de construire des modèles vectoriels de paragraphes également connus sous le nom de modèles doc2vec. » (source : https://github.com/bnosac/doc2vec)
Broader concept: R package / paquet R
Application field: generic / générique
Tasks performed: document embedding§§text clustering / plongement de documents§§partitionnement de textes
Implements: doc2vec / doc2vec
Programming language: C§§C++§§R language
Platforms: Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Design country: Belgium / Belgique
Licence: MIT License / licence MIT
Uses software: R / R
Repository: https://cran.r-project.org/web/packages/doc2vec/index.html§§https://github.com/bnosac/doc2vec
entityBERT / entityBERT
Definition: A BERT language model for clinical entities.
Définition : Modèle de langage BERT pour les entités cliniques.
Broader concept: large language model / grand modèle de langue
Application field: medicine / médecine
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: English / anglais
Design country: United States / États-Unis
Based on: BERT / BERT
Reference: Lin, C., Miller, T., Dligach, D., Bethard, S., & Savova, G. (2021). Entitybert: Entity-centric masking strategy for model pretraining for the clinical domain. Proceedings of the 20th Workshop on Biomedical Language Processing, 191–201. https://doi.org/10.18653/v1/2021.bionlp-1.21
estBERT / estBERT
Definition: A BERT language model for Estonian.
Définition : Modèle de langage BERT pour l'estonien.
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: Estonian / estonien
Design country: Estonia / Estonie
Based on: BERT / BERT
Reference: Tanvir, H., Kittask, C., Eiche, S., & Sirts, K. (2021). EstBERT : A pretrained language-Specific BERT for Estonian. Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa), 11‑19. https://aclanthology.org/2021.nodalida-main.2
farthest first clustering algorithm / algorithme farthest first
Broader concept: clustering algorithm / algorithme de partitionnement
Implemented by: RWeka / RWeka
fastText algorithm / algorithme fastText
Definition: An algorithm for word embeddings and text classification.
Définition : Algorithme pour le plongement lexical et la classification de textes.
Broader concept: Neural networks models / modèles de réseaux de neurones
Implemented by: fastText§§GluonNLP§§TextTinyR§§fastTextR / fastText§§GluonNLP§§TextTinyR§§fastTextR
flashtext / flashtext
Definition: "Extract Keywords from sentence or Replace keywords in sentences." (source: https://github.com/vi3k6i5/flashtext).
Définition : Librairie Python qui « extrait des mots-clés dans des phrases ou replace des mots-clés dans des phrases » (source : https://github.com/vi3k6i5/flashtext).
Broader concept: Python library / librairie Python
Application field: generic / générique
Tasks performed: keyword extraction / extraction de mots-clés
Input languages: English / anglais
Programming language: Python
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Design country: United Kingdom / Royaume-Uni
Licence: MIT License / licence MIT
Repository: https://github.com/vi3k6i5/flashtext
frog / forg
Definition: NLP suite for Dutch.
Définition : Outil de traitement automatique du language pour le néerlandais.
Broader concept: C++ library / librairie C++
Application field: generic / générique
Tasks performed: dependency parsing§§lemmatization§§morphological analysis§§PoS tagging§§tokenization / analyse en dépendances§§lemmatisation§§analyse morphologique§§étiquetage morpho-syntaxique§§tokenisation
Input languages: Dutch / néerlandais
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Design country: Netherlands / Pays-Bas
Licence: GNU GPL v3 / GNU GPL v3
Repository: https://github.com/LanguageMachines/frog
germaNER / germaNER
Definition: German named entity recognition tool.
Définition : Outil de reconnaissance d'entités nommées pour l'allemand.
Broader concept: Java library / librairie Java
Application field: generic / générique
Tasks performed: named entity recognition / reconnaissance d'entités nommées
Input languages: German / allemand
Programming language: Java§§Perl
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Design country: Germany / Allemagne
Licence: Apache License Version 2.0 / Apache License Version 2.0
Repository: https://github.com/tudarmstadt-lt/GermaNER
golgotha / golgotha
Definition: "provides a wrapper to Bidirectional Encoder Representations from Transformers (BERT) for language modelling and textual entailment in particular." (source: https://cran.r-project.org/web/views/NaturalLanguageProcessing.html).
Définition : Wrapper pour BERT sous R.
Broader concept: R package / paquet R
Application field: generic / générique
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Programming language: R language
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Licence: MPL v2.0 / MPL v2.0
Based on: BERT / BERT
Uses software: R / R
Repository: https://github.com/bnosac/golgotha
iTextMine / iTextMine
Definition: iTextMine is a system with an automated workflow to integrate text mining tools and relation extraction results from large-scale text processing.
Définition : iTextMine est un système doté d'un flux de travail automatisé permettant d'intégrer les outils de fouille de textes et les résultats de l'extraction de relations à partir du traitement de textes à grande échelle.
Broader concept: software application / application logicielle
Application field: generic / générique
Tasks performed: knowledge acquisition§§named entity recognition§§relation extraction / acquisition de connaissances§§reconnaissance d'entités nommées§§extraction de relations
Input languages: English / anglais
Input data: XML
Programming language: Java§§JavaScript
Interface: web user interface§§application programming interface / interface utilisateur web§§interface de programmation d’application
Design country: United States / États-Unis
Licence: CC BY 4.0 / CC BY 4.0
Reference: §§Ren, J., Li, G., Ross, K., Arighi, C., McGarvey, P., Rao, S., Cowart, J., Madhavan, S., Vijay-Shanker, K., & Wu, C. H. (2018). iTextMine : Integrated text-mining system for large-scale knowledge extraction from the literature. Database, 2018. https://doi.org/10.1093/database/bay128
jPTDP / jPTDP
Definition: "Neural network models for joint POS tagging and dependency parsing" (source: https://github.com/datquocnguyen/jPTDP).
Définition : « Modèles de réseaux de neurones pour l'analyse syntaxique de dépendance et l'étiquetage morphosyntaxique conjoints » (source: https://github.com/datquocnguyen/jPTDP).
Broader concept: Python library / librairie Python
Tasks performed: dependency parsing§§PoS tagging / analyse en dépendances§§étiquetage morpho-syntaxique
Implements: bidirectional long-short term memory / mémoire court et long terme bidirectionnelle
Input languages: Afrikaans§§Arabic§§Basque§§Bulgarian§§Catalan§§Chinese§§Church Slavonic§§Croatian§§Czech§§Danish§§Dutch§§Estonian§§Finnish§§French§§Galician§§German§§Gothic§§Greek§§Hebrew§§Hindi§§Hungarian§§Indonesian§§Irish§§Italian§§Japanese§§Korean§§Latin§§Latvian§§Northern Sámi§§Norwegian§§Persian§§Polish§§Portuguese§§Romanian§§Russian§§Serbian§§Slovak§§Slovenian§§Spanish§§Swedish§§Turkish§§Ukrainian§§Urdu§§Uyghur§§Vietnamese / afrikaans§§arabe§§basque§§bulgare§§catalan§§chinois§§slavon d'église§§croate§§tchèque§§danois§§néerlandais§§estonien§§finnois§§français§§galicien§§allemand§§gotique§§grec§§hébreu§§hindi§§hongrois§§indonésien§§irlandais§§italien§§japonais§§coréen§§latin§§letton§§same du Nord§§norvégien§§persan§§polonais§§portugais§§roumain§§russe§§serbe§§slovaque§§slovène§§espagnol§§suédois§§turc§§ukrainien§§ourdou§§ouïghour§§vietnamien
Programming language: Python
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Design country: Vietnam / Vietnam
Licence: GNU GPL v3 / GNU GPL v3
Repository: https://github.com/datquocnguyen/jPTDP
Reference: Nguyen, D. Q., & Verspoor, K. (2018). An improved neural network model for joint POS tagging and dependency parsing. Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, 81‑91. https://doi.org/10.18653/v1/K18-2008§§Nguyen, D. Q., Dras, M., & Johnson, M. (2017). A novel neural network model for joint POS tagging and graph-based dependency parsing. Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, 134‑142. https://doi.org/10.18653/v1/K17-3014
jiebaR / jiebaR
Definition: "Chinese text segmentation, keyword extraction and speech tagging For R." (source: https://cran.r-project.org/web/packages/jiebaR/index.html).
Définition : Paquet R pour la segmentation de textes, l'extraction de mots-clés et l'étiquetage morphosyntaxique pour le chinois.
Broader concept: R package / paquet R
Application field: generic / générique
Tasks performed: text segmentation§§keyword extraction§§PoS tagging / segmentation de textes§§extraction de mots-clés§§étiquetage morpho-syntaxique
Input languages: Chinese / chinois
Programming language: C++§§R language
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Licence: MIT License / licence MIT
Uses software: R / R
Repository: https://cran.r-project.org/package=jiebaR§§https://github.com/qinwf/jiebaR/issues
json / json
Broader concept: data format specification / specification du format de données
Is specified data input of: Cortext Manager§§Objectif TDM§§Penelope§§TACIT§§TextBlob§§VosViewer§§WebAnno§§quanteda / Cortext Manager§§Objectif TDM§§Penelope§§TACIT§§TextBlob§§VosViewer§§WebAnno§§quanteda
k-gram language model / modèle de langue k-grammes
Also known as:  / modèle de langage k-grammes
Broader concept: language model / modèle de langage
Implemented by: kgrams / kgrams
k-medoids / k-medoïdes
Broader concept: clustering algorithm / algorithme de partitionnement
Implemented by: TextTinyR / TextTinyR
Kalaallisut / groenlandais
Also known as: Greenlandic / 
Broader concept: natural language / langage naturel
IETF language tag: kl
ISO 639-1: kl
ISO 639-2: kal
ISO 639-3: kal
kgrams / kgrams
Definition: "Tools for training and evaluating k-gram language models in R, supporting several probability smoothing techniques, perplexity computations, random text generation and more." (source: https://cran.r-project.org/web/packages/kgrams/index.html).
Définition : « Outils pour l'entraînement et l'évaluation de modèles de langue k-grammes avec R » (source : https://cran.r-project.org/web/packages/kgrams/index.html).
Broader concept: R package / paquet R
Application field: generic / générique
Tasks performed: support operation / opération support
Implements: k-gram language model / modèle de langue k-grammes
Programming language: C++§§R language
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Licence: GNU GPL v3 / GNU GPL v3
Uses software: R / R
Repository: https://cran.r-project.org/web/packages/kgrams/index.html§§https://github.com/vgherard/kgrams
koRpus / koRpus
Definition: koRpus is a set of tools to analyze texts. It includes, amongst others, functions for automatic language detection, hyphenation, several indices of lexical diversity.
Définition : koRpus est un ensemble d'outils pour analyser des textes. Il comprend, entre autres, des fonctions de détection automatique du langage, de césure et plusieurs indices de diversité lexicale.
Broader concept: R package / paquet R
Application field: generic / générique
Tasks performed: corpus analysis§§language identification§§PoS tagging§§tokenization / analyse de corpus§§identification de la langue§§étiquetage morpho-syntaxique§§tokenisation
Input languages: Dutch§§English§§French§§German§§Italian§§Portuguese§§Russian§§Spanish§§.txt / néerlandais§§anglais§§français§§allemand§§italien§§portugais§§russe§§espagnol§§.txt
Programming language: R language
Interface: command-line interface / interface en ligne de commande
Design country: Germany / Allemagne
Licence: GNU GPL v3 / GNU GPL v3
Uses software: R§§TreeTagger / R§§TreeTagger
Repository: https://cran.r-project.org/web/packages/koRpus/index.html
lda / lda
Definition: "Implements latent Dirichlet allocation (LDA) and related models" (source: https://cran.r-project.org/web/packages/lda/index.html).
Définition : "implémente l'allocation de Dirichlet latente (LDA) et les modèles associés" (source: https://cran.r-project.org/web/packages/lda/index.html).
Broader concept: R package / paquet R
Application field: generic / générique
Tasks performed: topic detection / identification de topics
Implements: correlated topics model§§latent Dirichlet allocation / modèle de topiques corrélés§§allocation de Dirichlet latente
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Licence: GNU LGPL v3§§GNU LGPL v2.1§§GNU LGPL / GNU LGPL v3§§GNU LGPL v2.1§§GNU LGPL
Uses software: R / R
Repository: https://cran.r-project.org/web/packages/lda/index.html
lda2vec / lda2vec
Definition: "The lda2vec model tries to mix the best parts of word2vec and LDA into a single framework." (source: https://github.com/cemoody/lda2vec).
Définition : lda2vec associe Word2vec et l'allocation de Dirichlet latente dans un même framework.
Broader concept: Python library / librairie Python
Application field: generic / générique
Tasks performed: word embedding§§topic detection / plongement lexical§§identification de topics
Implements: latent Dirichlet allocation§§Word2Vec / allocation de Dirichlet latente§§Word2Vec
Programming language: Python
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Design country: United States / États-Unis
Licence: MIT License / licence MIT
Repository: https://github.com/cemoody/lda2vec
Reference: Moody, C. E. (2016). Mixing Dirichlet topic models and word embeddings to make lda2vec (arXiv:1605.02019). arXiv. https://doi.org/10.48550/arXiv.1605.02019
ldaPrototype / ldaPrototype
Definition: An R package to improve the reliability of topic modelling with latent Dirichlet allocation.
Définition : Paquet R permettant d'améliorer la fiabilité de la modélisation de topiques avec l'allocation de Dirichlet latente.
Broader concept: R package / paquet R
Application field: generic / générique
Tasks performed: topic detection / identification de topics
Implements: latent Dirichlet allocation / allocation de Dirichlet latente
Programming language: R language
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Design country: Germany / Allemagne
Licence: GNU GPL v3 / GNU GPL v3
Uses software: R / R
Repository: https://cran.r-project.org/web/packages/ldaPrototype/index.html§§https://github.com/JonasRieger/ldaPrototype
Reference: Rieger, J. (2020). ldaPrototype: A method in R to get a Prototype of multiple Latent Dirichlet Allocations. Journal of Open Source Software, 5(51), 2181. https://doi.org/10.21105/joss.02181§§Rieger, J., Jentsch, C., & Jörg, R. (2022). LDAPrototype: A Model Selection Algorithm to Improve Reliability of Latent Dirichlet Allocation [Preprint]. In Review. https://doi.org/10.21203/rs.3.rs-1486359/v1§§Rieger, J., Rahnenführer, J., & Jentsch, C. (2020). Improving Latent Dirichlet Allocation: On Reliability of the Novel Method LDAPrototype. In E. Métais, F. Meziane, H. Horacek, & P. Cimiano (Eds.), Natural Language Processing and Information Systems (Vol. 12089, pp. 118–125). Springer International Publishing. https://doi.org/10.1007/978-3-030-51310-8_11
lda Python library / librairie Python lda
Definition: Topic modeling with latent Dirichlet allocation.
Définition : Topic modeling à l'aide de l'allocation de Dirichlet latente.
Broader concept: Python library / librairie Python
Application field: generic / générique
Tasks performed: topic detection / identification de topics
Implements: latent Dirichlet allocation / allocation de Dirichlet latente
Programming language: Python
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Licence: MPL v2.0 / MPL v2.0
Repository: https://github.com/lda-project/lda
ldatuning / ldatuning
Definition: ldatuning provides metrics to estimate the best fitting number of topics in topic modeling.
Définition : ldatuning fournit des métriques pour estimer le nombre de thèmes le mieux adapté pour la modélisation de topiques.
Broader concept: R package / paquet R
Application field: generic / générique
Tasks performed: topic detection / identification de topics
Implements: latent Dirichlet allocation / allocation de Dirichlet latente
Programming language: R language
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Uses software: R / R
Repository: https://github.com/nikita-moor/ldatuning
lsa package / Paquet lsa
Definition: Isa package is an R package for latent semantic analysis.
Définition : Paquet R pour l'analyse sémantique latente.
Broader concept: R package / paquet R
Application field: generic / générique
Tasks performed: topic detection / identification de topics
Implements: latent semantic analysis / analyse sémantique latente
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Licence: GNU GPL v3§§GNU GPL v2 / GNU GPL v3§§GNU GPL v2
Uses software: R / R
Repository: https://cran.r-project.org/web/packages/lsa/index.html
mBART / mBART
Definition: "a sequence-to-sequence denoising auto-encoder pre-trained on large-scale monolingual corpora in many languages using the BART objective" (Liu et al., 2020).
Définition : Modèle de langage multilingue basé sur BART.
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Tasks performed: word embedding / plongement lexical
Implements: denoising autoencoder / autoencodeur débruiteur
Input languages: Burmese§§Chinese§§Czech§§Dutch§§English§§Estonian§§Finnish§§French§§German§§Gujarati§§Hindi§§Italian§§Japanese§§Kazakh§§Korean§§Latvian§§Lithuanian§§Nepali§§Romanian§§Russian§§Sinhala§§Spanish§§Turkish§§Vietnamese / birman§§chinois§§tchèque§§néerlandais§§anglais§§estonien§§finnois§§français§§allemand§§gujarati§§hindi§§italien§§japonais§§kazakh§§coréen§§letton§§lithuanien§§népalais§§roumain§§russe§§singhalais§§espagnol§§turc§§vietnamien
Design country: United States / États-Unis
Based on: BART / BART
Repository: https://github.com/pytorch/fairseq/tree/main/examples/mbart
Reference: Liu, Y., Gu, J., Goyal, N., Li, X., Edunov, S., Ghazvininejad, M., Lewis, M., & Zettlemoyer, L. (2020). Multilingual denoising pre-training for neural machine translation. arXiv:2001.08210 [cs]. http://arxiv.org/abs/2001.08210
mT5 / mT5
Also known as: multilingual-T5 / 
Definition: Multilingual version of T5.
Définition : Version multilingue de T5.
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: Afrikaans§§Albanian§§Amharic§§Arabic§§Armenian§§Azerbaijani§§Basque§§Belarusian§§Bengali§§Bulgarian§§Burmese§§Catalan§§Cebuano§§Chichewa§§Chinese§§Corsican§§Czech§§Danish§§Dutch§§English§§Esperanto§§Estonian§§Filipino§§Finnish§§French§§Galician§§Georgian§§German§§Greek§§Gujarati§§Haitian Creole§§Hausa§§Hawaiian§§Hebrew§§Hindi§§Hmong§§Hungarian§§Icelandic§§Igbo§§Indonesian§§Irish§§Italian§§Japanese§§Javanese§§Kannada§§Kazakh§§Khmer§§Kyrgyz§§Korean§§Kurdish§§Lao§§Latin§§Latvian§§Lithuanian§§Luxembourgish§§Macedonian§§Malagasy§§Malay§§Malayalam§§Maltese§§Marathi§§Mongolian§§Nepali§§Norwegian§§Pashto§§Persian§§Polish§§Portuguese§§Punjabi§§Romanian§§Russian§§Samoan§§Scottish Gaelic§§Serbian§§Shona§§Sindhi§§Sinhala§§Slovak§§Slovenian§§Somali§§Sotho§§Spanish§§Sundanese§§Swahili§§Swedish§§Tajik§§Tamil§§Telugu§§Turkish§§Ukrainian§§Urdu§§Uzbek§§Vietnamese§§Welsh§§West Frisian§§Xhosa§§Yiddish§§Yoruba§§Zulu§§Maori§§Thai / afrikaans§§albanais§§amharique§§arabe§§arménien§§azéri§§basque§§biélorusse§§bengali§§bulgare§§birman§§catalan§§cebuano§§chewa§§chinois§§corse§§tchèque§§danois§§néerlandais§§anglais§§espéranto§§estonien§§philippin§§finnois§§français§§galicien§§géorgien§§allemand§§grec§§gujarati§§créole haïtien§§haoussa§§hawaïen§§hébreu§§hindi§§hmong§§hongrois§§islandais§§igbo§§indonésien§§irlandais§§italien§§japonais§§javanais§§kannada§§kazakh§§khmer§§kirghize§§coréen§§kurde§§lao§§latin§§letton§§lithuanien§§luxembourgeois§§macédonien§§malgache§§malais§§malayalam§§maltais§§marathi§§mongol§§népalais§§norvégien§§pachto§§persan§§polonais§§portugais§§pendjabi§§roumain§§russe§§samoan§§gaélique écossais§§serbe§§shona§§sindhi§§singhalais§§slovaque§§slovène§§somali§§sotho du Sud§§espagnol§§soundanais§§swahili§§suédois§§tadjik§§tamoul§§télougou§§turc§§ukrainien§§ourdou§§ouzbek§§vietnamien§§gallois§§frison occidental§§xhosa§§yiddish§§yoruba§§zoulou§§maori§§thaï
Programming language: Python
Design country: United States / États-Unis
Licence: Apache License Version 2.0 / Apache License Version 2.0
Based on: T5 / T5
Repository: https://github.com/google-research/multilingual-t5
Reference: Xue, L., Constant, N., Roberts, A., Kale, M., Al-Rfou, R., Siddhant, A., Barua, A., & Raffel, C. (2020). mT5 : A massively multilingual pre-trained text-to-text transformer. https://doi.org/10.48550/arXiv.2010.11934
maptpx / maptpx
Definition: "Maximum a posteriori (MAP) estimation for topic models (i.e., Latent Dirichlet Allocation) in text analysis" (source: https://cran.rstudio.com/web/packages/maptpx/index.html).
Définition : « Estimation du maximum a posteriori pour les modèles de topiques (c’est-à-dire, l’allocation de Dirichlet latente) » (source : https://cran.rstudio.com/web/packages/maptpx/index.html).
Broader concept: R package / paquet R
Application field: generic / générique
Tasks performed: topic detection / identification de topics
Implements: latent Dirichlet allocation / allocation de Dirichlet latente
Programming language: C§§R language
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Licence: GNU GPL v3 / GNU GPL v3
Uses software: R / R
Repository: https://cran.rstudio.com/web/packages/maptpx/index.html§§https://github.com/TaddyLab/maptpx
medBERT / medBERT
Definition: A BERT language models for the medical domain.
Définition : Modèle de langage BERT pour le domaine médical.
Broader concept: large language model / grand modèle de langue
Application field: biology§§medicine / biologie§§médecine
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: English§§Japanese / anglais§§japonais
Programming language: Python
Design country: Japan / Japon
Licence: CC BY-NC-SA 4.0 / CC BY-NC-SA 4.0
Based on: BERT / BERT
Repository: https://github.com/ou-medinfo/medbertjp
Reference: Wada, S., Takeda, T., Manabe, S., Konishi, S., Kamohara, J., & Matsumura, Y. (2021). Pre-training technique to localize medical BERT and enhance biomedical BERT. arXiv:2005.07202 [cs]. http://arxiv.org/abs/2005.07202