datasets-CNRS/ThesoTM huggingface dataset:
Apache cTAKES / Apache cTAKES
Definition: Apache cTAKES is a natural language processing system for extraction of information from electronic medical record clinical free-text.
Définition : Apache cTAKES est un système de traitement du langage naturel pour l'extraction d'informations à partir de textes libres issus de dossiers médicaux électroniques.
Broader concept: software application / application logicielle
Application field: medicine / médecine
Tasks performed: semantic role labeling§§chunking§§coreference resolution§§constituency parsing§§dependency parsing§§information extraction§§named entity recognition§§PoS tagging§§tokenization / étiquetage en rôles sémantiques§§chunking§§résolution de coréférence§§analyse en constituants§§analyse en dépendances§§extraction d'information§§reconnaissance d'entités nommées§§étiquetage morpho-syntaxique§§tokenisation
Input languages: English / anglais
Input data: .txt
Programming language: Java
Interface: desktop graphical user interface§§command-line interface / interface utilisateur graphique desktop§§interface en ligne de commande
Design country: United States / États-Unis
Licence: Apache License Version 2.0 / Apache License Version 2.0
Uses software: Apache UIMA / Apache UIMA
Reference: Savova, G. K., Masanz, J. J., Ogren, P. V., Zheng, J., Sohn, S., Kipper-Schuler, K. C., & Chute, C. G. (2010). Mayo clinical text analysis and knowledge extraction system (ctakes): Architecture, component evaluation and applications. Journal of the American Medical Informatics Association, 17(5), 507–513. https://doi.org/10.1136/jamia.2009.001560§§Ying-Chi Lin, Victor Christen, Silvio Domingos Cardoso, Marcos da Silveira, Cédric Pruski et al. Evaluating and improving annotation tools for medical forms, (2017), 12th International Conference on Data Integration in Life Sciences, Luxembourg, Luxembourg. https://doi.org/10.1007/978-3-319-69751-2_1
AraBERT / AraBERT
Definition: A BERT language model for Arabic.
Définition : Modèle de langage BERT pour l'arabe.
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: Arabic / arabe
Programming language: Python
Design country: Lebanon / Liban
Based on: BERT / BERT
Repository: https://github.com/aub-mind/arabert
Reference: Antoun, W., Baly, F., & Hajj, H. (2021). AraBERT : Transformer-based model for Arabic language understanding. arXiv:2003.00104 [cs]. http://arxiv.org/abs/2003.00104
AraGPT2 / AraGPT2
Definition: An arabic pre-trained language model.
Définition : Modèle de langage basé sur GPT-2 pré-entraîné pour la langue arabe.
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: Arabic / arabe
Programming language: Python
Design country: Lebanon / Liban
Based on: GPT-2 / GPT-2
Repository: https://github.com/aub-mind/arabert
Reference: Antoun, W., Baly, F., & Hajj, H. (2021). AraGPT2 : Pre- trained transformer for Arabic language generation. arXiv:2012.15520 [cs]. http://arxiv.org/abs/2012.15520§§Antoun, W., Baly, F., & Hajj, H. (2021). AraGPT2 : Pre-trained transformer for Arabic language generation. arXiv:2012.15520 [cs]. http://arxiv.org/abs/2012.15520
Arabela / arabela
Broader concept: natural language / langage naturel
IETF language tag: arl
ISO 639-3: arl
Arabic / arabe
Broader concept: natural language / langage naturel
IETF language tag: ar
ISO 639-1: ar
ISO 639-2: ara
ISO 639-3: ara
Aragonese / aragonais
Broader concept: natural language / langage naturel
IETF language tag: an
ISO 639-1: an
ISO 639-2: arg
ISO 639-3: arg
Argo / Argo
Definition: Argo is a workbench for building and running text-analysis solutions. It facilitates the development of custom workflows from a selection of elementary analytics.
Définition : Argo est un environnement de test pour construire et exécuter des solutions d'analyse de textes. Il facilite le développement de flux de travail personnalisés.
Broader concept: software application / application logicielle
Application field: generic / générique
Tasks performed: information retrieval§§named entity recognition§§text annotation / recherche d'information§§reconnaissance d'entités nommées§§annotation textuelle
Input languages: English / anglais
Platforms: Linux§§Windows§§macOS
Interface: web user interface / interface utilisateur web
Design country: United Kingdom / Royaume-Uni
Uses software: Apache UIMA / Apache UIMA
Reference: Rak, R., Rowley, A., Black, W., & Ananiadou, S. (2012). Argo : An integrative, interactive, text mining-based workbench supporting curation. Database, 2012. https://doi.org/10.1093/database/bas010
Armenian / arménien
Broader concept: natural language / langage naturel
IETF language tag: hy
ISO 639-1: hy
ISO 639-2: arm§§hye
ISO 639-3: axm§§hye§§hyw§§xcl
Assamese / assamais
Also known as: Asamiya / 
Broader concept: natural language / langage naturel
IETF language tag: as
ISO 639-1: as
ISO 639-2: asm
ISO 639-3: asm
astroBERT / astroBERT
Definition: A BERT language model for astronomy and astrophysics.
Définition : Modèle de langage BERT pour l'astronomie et l'astrophysique.
Broader concept: large language model / grand modèle de langue
Implements: transformer / transformeur
Input languages: English / anglais
Programming language: Python
Design country: United States / États-Unis
Licence: MIT License / licence MIT
Based on: BERT / BERT
Repository: https://huggingface.co/adsabs/astroBERT
Reference: Grezes, F., Blanco-Cuaresma, S., Accomazzi, A., Kurtz, M. J., Shapurian, G., Henneken, E., Grant, C. S., Thompson, D. M., Chyla, R., McDonald, S., Hostetler, T. W., Templeton, M. R., Lockhart, K. E., Martinovic, N., Chen, S., Tanner, C., & Protopapas, P. (2021). Building astroBERT, a language model for Astronomy & Astrophysics (arXiv:2112.00590). arXiv. https://doi.org/10.48550/arXiv.2112.00590
AstroLLaMA / AstroLLaMA
Definition: A language model for astronomy based on LLaMA 2.
Définition : Modèle de langage pour l'astronomie basé sur LLaMA 2.
Broader concept: large language model / grand modèle de langue
Implements: transformer / transformeur
Input languages: English / anglais
Programming language: Python
Design country: Australia§§China§§Poland§§Spain§§United States / Australie§§Chine§§Espagne§§Pologne§§États-Unis
Licence: MIT License / licence MIT
Based on: Llama 2 / Llama 2
Application field of: astronomy / astronomie
Repository: https://huggingface.co/universeTBD/astrollama.gguf
Reference: Dung Nguyen, T., Ting, Y.-S., Ciucă, I., O’Neill, C., Sun, Z.-C., Jabłońska, M., Kruk, S., Perkowski, E., Miller, J., Li, J., Peek, J., Iyer, K., Różański, T., Khetarpal, P., Zaman, S., Brodrick, D., Rodríguez Méndez, S. J., Bui, T., Goodman, A., … UniverseTBD. (2023). AstroLLaMA: Towards specialized foundation models in astronomy. In arXiv e-prints. https://doi.org/10.48550/arXiv.2309.06126§§Perkowski, E., Pan, R., Nguyen, T. D., Ting, Y.-S., Kruk, S., Zhang, T., O’Neill, C., Jablonska, M., Sun, Z., Smith, M. J., Liu, H., Schawinski, K., Iyer, K., & UniverseTBD, I. C. for. (2024). AstroLLaMA-chat: Scaling AstroLLaMA with conversational and diverse datasets (arXiv:2401.01916). arXiv. https://doi.org/10.48550/arXiv.2401.01916
astronomy / astronomie
Broader concept: scientific knowledge / connaissances scientifiques
Application field: AstroLLaMA / AstroLLaMA
Application field of: Galactica / Galactica
astrophysics / astrophysique
Broader concept: scientific knowledge / connaissances scientifiques
Asturian / asturien
Broader concept: natural language / langage naturel
IETF language tag: ast
ISO 639-2: ast
ISO 639-3: ast
Asuri / asuri
Broader concept: natural language / langage naturel
ISO 639-3: asr
autoencoder / autoencodeur
Also known as:  / auto-associateur§§auto-encodeur§§autoassociateur
Definition: An autoencoder is a type of artificial neural network used to learn efficient codings of unlabeled data (unsupervised learning) (Wikipedia, retrieved 07/02/2021).
Définition : Un autoencodeur est un type de réseau de neurones artificiels utilisé pour apprendre des codages efficaces de données non étiquetées (apprentissage non supervisé). (Wikipédia, récupéré le 07/02/2021).
Broader concept: Neural networks models / modèles de réseaux de neurones
Implemented by: PIXEL / PIXEL
Reference: Kramer, M. A. (1991). Nonlinear principal component analysis using autoassociative neural networks. AIChE Journal, 37(2), 233‑243. https://doi.org/10.1002/aic.690370209
Awadhi / awadhi
Also known as: Oudhi / 
Broader concept: natural language / langage naturel
IETF language tag: awa
ISO 639-2: awa
ISO 639-3: awa
Aymara / aymara
Also known as:  / aimara
Broader concept: natural language / langage naturel
IETF language tag: ay
ISO 639-1: ay
ISO 639-2: aym
ISO 639-3: aym
Azerbaijani / azéri
Also known as: Azeri§§Azeri Turkic§§Azeri Turkish / azerbaïdjanais
Broader concept: natural language / langage naturel
IETF language tag: az
ISO 639-1: az
ISO 639-2: aze
ISO 639-3: aze
BANNER / BANNER
Definition: BANNER is a system for the recognition of named entities intended primarily for biomedical texts. It uses conditional random fields as the main recognition engine and includes a wide range of the best techniques. described in recent literature.
Définition : BANNER est un système de reconnaissance d'entités nommées destiné principalement aux textes biomédicaux. Il utilise les champs aléatoires conditionnels comme principal moteur de reconnaissance et comprend un large éventail des meilleures techniques décrites dans la littérature récente.
Broader concept: Java library / librairie Java
Application field: medicine / médecine
Tasks performed: named entity recognition / reconnaissance d'entités nommées
Input languages: English / anglais
Input data: .txt
Programming language: Java
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Design country: United States / États-Unis
Licence: open source software license / licence de logiciel libre
Repository: https://sourceforge.net/projects/banner/
Reference: Leaman R. & Gonzalez G. BANNER: An executable survey of advances in biomedical named entity recognition, (2008), Pacific Symposium on Biocomputing 13:652-663 https://doi.org/10.1142/9789812776136_0062
BART / BART
Also known as: Bayesian Analogy with Relational Transformations / 
Definition: "a denoising autoencoder for pretraining sequence-to-sequence models" (Lewis et al., 2019).
Définition : « un autoencodeur de débruitage pour le préentraînement de modèles de séquence à séquence. » (Lewis et al., 2019).
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Tasks performed: word embedding / plongement lexical
Implements: denoising autoencoder§§transformer / autoencodeur débruiteur§§transformeur
Input languages: English / anglais
Programming language: Python
Design country: United States / États-Unis
Base of: BARThez§§PLBART§§mBART / BARThez§§PLBART§§mBART
Repository: https://github.com/pytorch/fairseq/tree/main/examples/bart
Reference: Lewis, M., Liu, Y., Goyal, N., Ghazvininejad, M., Mohamed, A., Levy, O., Stoyanov, V., & Zettlemoyer, L. (2019). Bart : Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension. arXiv:1910.13461 [cs, stat]. http://arxiv.org/abs/1910.13461
BARThez / BARThez
Definition: "A French sequence to sequence pretrained model." (source: https://github.com/moussaKam/BARThez)
Définition : Modèle pré-entraîné séquence à séquence pour le français.
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Implements: denoising autoencoder§§transformer / autoencodeur débruiteur§§transformeur
Input languages: French / français
Programming language: Python
Licence: Apache License Version 2.0 / Apache License Version 2.0
Based on: BART / BART
Repository: https://github.com/moussaKam/BARThez
Reference: Eddine, M. K., Tixier, A. J.-P., & Vazirgiannis, M. (2021). BARThez: A skilled pretrained french sequence-to-sequence model (arXiv:2010.12321). arXiv. http://arxiv.org/abs/2010.12321
BEHRT / BEHRT
Definition: A BERT language model for electronic health records.
Définition : Modèle de langage BERT pour les dossiers médicaux électroniques.
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
Programming language: Python
Design country: United Kingdom / Royaume-Uni
Based on: BERT / BERT
Repository: https://github.com/deepmedicine/BEHRT
Reference: Li, Y., Rao, S., Solares, J. R. A., Hassaine, A., Ramakrishnan, R., Canoy, D., Zhu, Y., Rahimi, K., & Salimi-Khorshidi, G. (2020). Behrt : Transformer for electronic health records. Scientific Reports, 10(1), 7155. https://doi.org/10.1038/s41598-020-62922-y
BERT / BERT
Also known as: Bidirectional Encoder Representations from Transformers / 
Definition: "BERT is designed to pretrain deep bidirectional representations from unlabeled text by jointly conditioning on both left and right context in all layers." (Devlin et al., 2019).
Définition : « BERT est conçu pour pré-entraîner des représentations bidirectionnelles profondes à partir de textes non étiquetés en conditionnant conjointement les contextes gauche et droit dans toutes les couches. » (Devlin et al., 2019).
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Tasks performed: word embedding / plongement lexical
Input languages: English / anglais
Programming language: Python
Design country: United States / États-Unis
Licence: Apache License Version 2.0 / Apache License Version 2.0
Base of: ALBERT§§ALeaseBERT§§ARBERT§§AlBERTo§§AlephBERT§§AraBERT§§astroBERT§§BEHRT§§BERTJapanese§§BETO§§BERT-PLI§§BERT-SentiX§§BERTimbau§§BERTje§§BERTopic§§BERTurk§§BanglaBERT§§BioBERT§§BioMedBERT§§BlueBERT§§COVID-Twitter-BERT§§CharBERT§§ClinicalBERT§§Czech-B§§DeBERTa§§FARM§§Finnish BERT§§FlauBERT§§German BERT§§GluonNLP§§GreekBERT§§HateBERT§§HeBERT§§HerBERT§§IndoBERT§§KB-BERT§§KLUE-BERT§§KM-BERT§§KR-BERT§§Kashgari§§KeyBERT§§KoBERT§§Legal-BERT§§MARBERT§§M-BERT§§MC-BERT§§MathBERT§§MobileBERT§§Mol-BERT§§MuRIL§§NetBERT§§OAG-BERT§§OpenNRE§§OuBioBERT§§ParsBERT§§PharmBERT§§PhoBERT§§ProkBERT§§ProteinBERT§§PubMedBERT§§RBERT§§RadBERT§§RoBERTa§§Romanian BERT§§ruBERT§§RxBERT§§SBERT§§SapBERT§§Slavic BERT§§Spark NLP§§Spark NLP Python§§Spark NLP Scala§§StructBERT§§TOD-BERT§§TinyBERT§§Tohoku-BERT§§Top2Vec§§UTH-BERT§§UmlsBERT§§convBERT§§DistilBERT§§entityBERT§§estBERT§§golgotha§§medBERT§§nanoBERT§§sciBERT§§spanBERT§§srBERT / ALBERT§§ALeaseBERT§§ARBERT§§AlBERTo§§AlephBERT§§AraBERT§§astroBERT§§BEHRT§§BERTJapanese§§BETO§§BERT-PLI§§BERT-SentiX§§BERTimbau§§BERTje§§BERTopic§§BERTurk§§BanglaBERT§§BioBERT§§BioMedBERT§§BlueBERT§§COVID-Twitter-BERT§§CharBERT§§ClinicalBERT§§Czech-B§§DeBERTa§§FARM§§Finnish BERT§§FlauBERT§§German BERT§§GluonNLP§§GreekBERT§§HateBERT§§HeBERT§§HerBERT§§IndoBERT§§KB-BERT§§KLUE-BERT§§KM-BERT§§KR-BERT§§Kashgari§§KeyBERT§§KoBERT§§Legal-BERT§§MARBERT§§M-BERT§§MC-BERT§§MathBERT§§MobileBERT§§Mol-BERT§§MuRIL§§NetBERT§§OAG-BERT§§OpenNRE§§OuBioBERT§§ParsBERT§§PharmBERT§§PhoBERT§§ProkBERT§§ProteinBERT§§PubMedBERT§§RBERT§§RadBERT§§RoBERTa§§Romanian BERT§§ruBERT§§RxBERT§§SBERT§§SapBERT§§Slavic BERT§§Spark NLP§§Spark NLP Python§§Spark NLP Scala§§StructBERT§§TOD-BERT§§TinyBERT§§Tohoku-BERT§§Top2Vec§§UTH-BERT§§UmlsBERT§§convBERT§§DistilBERT§§entityBERT§§estBERT§§golgotha§§medBERT§§nanoBERT§§sciBERT§§spanBERT§§srBERT
Implemented by: DeLFT / DeLFT
Repository: https://github.com/google-research/bert
Reference: Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2019). BERT : Pre-training of deep bidirectional transformers for language understanding. arXiv:1810.04805 [cs]. http://arxiv.org/abs/1810.04805
BERTJapanese / BERTJapanese
Definition: A language model based on BERT trained on Japanese texts.
Définition : Modèle de langage basé sur BERT et pré-entraîné sur des textes en japonais.
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Implements: transformer / transformeur
Input languages: Japanese / japonais
Programming language: Python
Licence: Apache License Version 2.0 / Apache License Version 2.0
Based on: BERT / BERT
Repository: https://github.com/cl-tohoku/bert-japanese§§https://huggingface.co/docs/transformers/v4.37.2/model_doc/bert-japanese
BETO / BETO
Definition: A BERT language model for Spanish.
Définition : Modèle de language BERT pour l'espagnol.
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: Spanish / espagnol
Programming language: Python
Design country: Chile / Chili
Based on: BERT / BERT
Repository: https://github.com/dccuchile/beto
Reference: Cañete J, Chaperon G, Fuentes R, Pérez J. Spanish pre-trained BERT model and evaluation data. PML4DC at CLR 2020 Addis Ababa, Ethiopia, 26 Apr. 2020; p. 1-10.
BERT-PLI / BERT-PLI
Definition: "models the paragraph-level interactions of case documents via BERT and then aggregate these interactions to infer the document relevance via a sequential modeling mechanism." (Shao et al., 2020).
Définition : « modélise les interactions au niveau des paragraphes des documents d’affaires juridiques via BERT, puis agrège ces interactions pour inférer la pertinence du document via un mécanisme de modélisation séquentielle. » (Shao et al., 2020).
Broader concept: large language model / grand modèle de langue
Application field: legal information / information légale
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: English / anglais
Programming language: Python
Design country: China§§Japan / Chine§§Japon
Licence: MIT License / licence MIT
Based on: BERT / BERT
Repository: https://github.com/sophiaalthammer/bert-pli
Reference: Shao, Y., Mao, J., Liu, Y., Ma, W., Satoh, K., Zhang, M., & Ma, S. (2020). BERT-PLI : Modeling paragraph-level interactions for legal case retrieval. Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 3501‑3507. https://doi.org/10.24963/ijcai.2020/484
BERT-SentiX / BERT-SentiX
Definition: A pre-trained language model for sentiment analysis.
Définition : Modèle de langage pré-entraîné destiné à l'analyse de sentiments.
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: English / anglais
Programming language: Python
Design country: China / Chine
Based on: BERT / BERT
Repository: https://github.com/12190143/SentiX
Reference: Zhou, J., Tian, J., Wang, R., Wu, Y., Xiao, W., & He, L. (2020). SentiX : A sentiment-aware pre-trained model for cross-domain sentiment analysis. Proceedings of the 28th International Conference on Computational Linguistics, 568‑579. https://doi.org/10.18653/v1/2020.coling-main.49
BERTimbau / BERTimbau
Definition: BERT language model for Brazilian Portuguese.
Définition : Modèle de langage BERT pour le portugais du Brésil.
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: Brazilian Portuguese / portugais du Brésil
Programming language: Python
Design country: Brazil / Brésil
Licence: free to use license / licence libre d'utilisation
Based on: BERT / BERT
Repository: https://github.com/neuralmind-ai/portuguese-bert
Reference: Souza, F., Nogueira, R., & Lotufo, R. (2020). BERTimbau : Pretrained BERT models for Brazilian Portuguese. In R. Cerri & R. C. Prati (Eds.), Intelligent Systems (p. 403‑417). Springer International Publishing. https://doi.org/10.1007/978-3-030-61377-8_28
BERTje / BERTje
Definition: A Dutch BERT model.
Définition : Modèle BERT pour le néerlandais.
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: Dutch / néerlandais
Programming language: Python
Design country: Netherlands / Pays-Bas
Licence: Apache License Version 2.0 / Apache License Version 2.0
Based on: BERT / BERT
Repository: https://github.com/wietsedv/bertje
Reference: de Vries, W., van Cranenburgh, A., Bisazza, A., Caselli, T., van Noord, G., & Nissim, M. (2019). BERTje : A Dutch BERT model. arXiv:1912.09582 [cs]. http://arxiv.org/abs/1912.09582
BERTopic / BERTopic
Definition: "BERTopic is a topic modeling technique that leverages transformers and c-TF-IDF to create dense clusters allowing for easily interpretable topics whilst keeping important words in the topic descriptions." (source: https://github.com/MaartenGr/BERTopic).
Définition : Topic modeling basé sur BERT et TF-IDF afin de créer des topiques facilement interprétables.
Broader concept: Python library / librairie Python
Application field: generic / générique
Tasks performed: topic detection§§visualization / identification de topics§§visualisation
Implements: transformer / transformeur
Input languages: English / anglais
Programming language: Python
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Design country: Netherlands / Pays-Bas
Licence: MIT License / licence MIT
Based on: BERT / BERT
Repository: https://github.com/MaartenGr/BERTopic
Reference: Grootendorst, M. (2022). BERTopic: Neural topic modeling with a class-based TF-IDF procedure (arXiv:2203.05794). arXiv. https://doi.org/10.48550/arXiv.2203.05794
BERTurk / BERTurk
Definition: A BERT model for Turkish.
Définition : Modèle BERT pour le Turc.
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: Turkish / turc
Programming language: Python
Based on: BERT / BERT
Repository: https://github.com/stefan-it/turkish-bert
BERTweet / BERTweet
Definition: A language model based on RoBERTa pre-trained on English tweets.
Définition : Modèle de langage basé sur RoBERTa pré-entraîné sur des tweets en anglais.
Broader concept: large language model / grand modèle de langue
Application field: social networks / réseaux sociaux
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: English / anglais
Programming language: Python
Platforms: Linux
Design country: United States / États-Unis
Licence: MIT License / licence MIT
Based on: RoBERTa / RoBERTa
Repository: https://github.com/VinAIResearch/BERTweet
Reference: Nguyen, D. Q., Vu, T., & Nguyen, A. T. (2020). BERTweet: A pre-trained language model for English Tweets. https://arxiv.org/abs/2005.10200v2
BIRCH algorithm / algorithme BIRCH
Also known as: Balanced Iterative Reducing and Clustering using Hierarchies / 
Broader concept: clustering algorithm / algorithme de partitionnement
Implemented by: scikit-learn / scikit-learn