datasets-CNRS/ThesoTM huggingface dataset:
CogComp-NLP / CogComp-NLP
Definition: CogComp-NLP provides a suite of state-of-the-art Natural Language Processing (NLP) tools that allows you to annotate plain text inputs.
Définition : CogComp-NLP fournit une suite d'outils de traitement du langage naturel (TAL) qui permet d'annoter des entrées en plein texte.
Broader concept: Java library / librairie Java
Application field: generic / générique
Tasks performed: chunking§§coreference resolution§§dependency parsing§§lemmatization§§PoS tagging§§relation extraction§§sentence splitting§§sentiment analysis§§tokenization / chunking§§résolution de coréférence§§analyse en dépendances§§lemmatisation§§étiquetage morpho-syntaxique§§extraction de relations§§découpage de phrases§§analyse de sentiments§§tokenisation
Input languages: English / anglais
Input data: .txt
Programming language: Java
Design country: United States / États-Unis
Licence: free to use license / licence libre d'utilisation
Repository: https://github.com/CogComp/cogcomp-nlp
Colorado / colorado
Also known as: Tsachila§§Tsafiki / tsafiqui
Broader concept: natural language / langage naturel
communication / communication
Broader concept: knowledge area / domaine de connaissance
Application field of: LaMDA / LaMDA
concept extraction / extraction de concepts
Definition: A machine learning task/process that aims to identify concepts of interest in a text.
Définition : Tâche/processus de l'apprentissage automatique qui vise à repérer les concepts d'intérêt dans un texte.
Broader concept: information extraction / extraction d'information
concordance analysis / analyse de concordance
Also known as: concordancer§§concordancing / analyse des concordances§§concordancier
Definition: Task/process of generating context windows of a word in a corpus.
Définition : Tâche/processus consistant à afficher les fenêtres contextuelles d'un mot dans un corpus.
Broader concept: support operation / opération support
Implemented by: Lexi-co / Lexi-co
conditional random field / champ aléatoire conditionnel
Also known as: CRF / CRF
Definition: A classification algorithm to predict sequences taking into account contextual information.
Définition : Algorithme de classification permettant de prédire des séquences et prenant en compte les informations contextuelles.
Broader concept: classification algorithm / algorithme de classification
Implemented by: BioTagger§§CRFChunker§§ClearTK§§Entity fishing§§GROBID§§JTextPro§§JVnSegmenter / BioTagger§§CRFChunker§§ClearTK§§entity fishing§§GROBID§§JTextPro§§JVnSegmenter
Reference: Lafferty, J., McCallum, A., & Pereira, F. C. N. (n.d.). Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In International Conference on Machine Learning, 2001.
ContentMine / ContentMine
Definition: ContentMine brings together Text and data mining tools.
Définition : ContentMine rassemble des outils de fouille de textes et de données.
Broader concept: software application / application logicielle
Application field: generic / générique
Tasks performed: knowledge discovery / découverte de connaissances
Programming language: HTML§§JavaScript§§Shell
Design country:  / Royaume-Uni
Licence: free to use license / licence libre d'utilisation
contingency analysis / analyse de contingence
Broader concept: algorithm / algorithme
Implemented by: Cortext Manager / Cortext Manager
convolutional neural network / réseau de neurones convolutif
Also known as: CNN§§ConvNet / CNN§§ConvNet§§réseau de neurones à convolution§§réseau neuronal convolutif
Definition: a convolutional neural network (ConvNet) is a class of deep neural network, most commonly applied to analyze visual imagery.(Wikipedia, retrieved on 2021/07/02).
Définition : un réseau de neurones convolutifs (ConvNet) est une classe de réseau de neurones profonds, le plus souvent appliqué pour analyser l'imagerie visuelle. (Wikipedia, récupéré le 02/07/2021).
Broader concept: Neural networks models / modèles de réseaux de neurones
Implemented by: LangMoDHS§§OpenNRE§§TextAttack§§convBERT§§convBERTurk§§PyTorch-NLP / LangMoDHS§§OpenNRE§§TextAttack§§convBERT§§conBERTurk§§PyTorch-NLP
Reference: LeCun, Y., Boser, B. E., Denker, J. S., Henderson, D., Howard, R. E., Hubbard, W. E., & Jackel, L. D. (1989.). Handwritten digit recognition with a back-propagation network. Proceedings of the 2nd International Conference on Neural Information Processing Systems (pp. 396-404).§§LeCun, Y., Boser, B. E., Denker, J. S., Henderson, D., Howard, R. E., Hubbard, W. E., & Jackel, L. D. (1990). Handwritten digit recognition with a back-propagation network. In Proceedings Advances in Neural Information Processing Systems, 396‑404.§§Lecun, Y., Bottou, L., Bengio, Y., & Haffner, P. (1998). Gradient-based learning applied to document recognition. Proceedings of the IEEE, 86(11), 2278‑2324. https://doi.org/10.1109/5.726791§§Valueva, M. V., Nagornov, N. N., Lyakhov, P. A., Valuev, G. V., & Chervyakov, N. I. (2020). Application of the residue number system to reduce hardware costs of the convolutional neural network implementation. Mathematics and Computers in Simulation, 177, 232‑243. https://doi.org/10.1016/j.matcom.2020.04.031
Coptic / copte
Broader concept: natural language / langage naturel
IETF language tag: cop
ISO 639-2: cop
ISO 639-3: cop
CorEx Topic / CorEx Topic
Definition: Hierarchical topic modeling.
Définition : Modélisation hiérarchique de topiques.
Broader concept: Python library / librairie Python
Application field: generic / générique
Tasks performed: topic detection / identification de topics
Implements: hierarchical topic modeling / modèle de topiques hiérarchique
Programming language: Python
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Licence: Apache License Version 2.0 / Apache License Version 2.0
Repository: https://github.com/gregversteeg/corex_topic
Reference: Gallagher, R. J., Reing, K., Kale, D., & Steeg, G. V. (2017). Anchored correlation explanation: Topic modeling with minimal domain knowledge. Transactions of the Association for Computational Linguistics, 5(0), Article 0.
correlated topics model / modèle de topiques corrélés
Broader concept: topic modelling algorithm / algorithme de modélisation de topiques
Implemented by: lda§§revtools§§topicmodels / lda§§revtools§§topicmodels
Reference: Lafferty, J., & Blei, D. (2005). Correlated topic models. In Y. Weiss, B. Schölkopf, & J. Platt (Eds.), Advances in Neural Information Processing Systems (Vol. 18). MIT Press. https://proceedings.neurips.cc/paper/2005/file/9e82757e9a1c12cb710ad680db11f6f1-Paper.pdf
correspondence analysis / analyse factorielle des correspondances
Also known as:  / AFC
Broader concept: clustering algorithm / algorithme de partitionnement
Implemented by: Cortext Manager§§Hyperbase§§Iramuteq§§Le Trameur§§R.TeMIS§§TXM§§TextObserver§§Textable§§bibliometrix§§quanteda§§svs / Cortext Manager§§Hyperbase§§Iramuteq§§Le Trameur§§R.TeMIS§§TXM§§TextObserver§§Textable§§bibliometrix§§quanteda§§svs
Corsican / corse
Broader concept: natural language / langage naturel
IETF language tag: co
ISO 639-1: co
ISO 639-2: cos
ISO 639-3: cos
Cortext Manager / Cortext Manager
Definition: Cortext Manager proposes a full ecosystem of modeling and exploratory tools for analyzing text corpora.
Définition : Cortext Manager propose un écosystème complet d'outils de modélisation et d'exploration pour l'analyse de corpus de textes.
Broader concept: software application / application logicielle
Application field: generic / générique
Tasks performed: word embedding§§corpus analysis§§named entity recognition§§sentiment analysis§§term extraction§§topic detection§§visualization / plongement lexical§§analyse de corpus§§reconnaissance d'entités nommées§§analyse de sentiments§§extraction de termes§§identification de topics§§visualisation
Implements: contingency analysis§§correspondence analysis§§latent Dirichlet allocation§§Word2Vec / analyse de contingence§§analyse factorielle des correspondances§§allocation de Dirichlet latente§§Word2Vec
Input languages: English§§French§§German§§Spanish / anglais§§français§§allemand§§espagnol
Input data: json§§.txt§§XML§§pdf§§Microsoft Word doc§§.csv
Interface: web user interface / interface utilisateur web
Design country: France / France
Licence: free to use license / licence libre d'utilisation
cost sensitive classifier / classifieur sensible au coût
Also known as: cost sensitive classification / classification sensible au coût
Broader concept: classification algorithm / algorithme de classification
Implemented by: RWeka / RWeka
Croatian / croate
Broader concept: natural language / langage naturel
IETF language tag: hr
ISO 639-1: hr
ISO 639-2: hrv
ISO 639-3: hrv
Cuaiquer / cuaiquer
Also known as: Awa§§Awa Pit§§Coaiquer§§Cuayquer§§Kwaiker§§Kwayquer / awa pit§§coayquer§§cuayquer§§kwaiker
Broader concept: natural language / langage naturel
Czech / tchèque
Broader concept: natural language / langage naturel
IETF language tag: cs
ISO 639-1: cs
ISO 639-2: ces§§cze
ISO 639-3: ces
Czech-B / Czech-B
Definition: A BERT model for Czech.
Définition : Modèle BERT pour le tchèque.
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: Czech / tchèque
Programming language: Python
Design country: Czech Republic / République tchèque
Based on: BERT / BERT
Repository: https://github.com/kiv-air/Czert
Reference: Sido, J., Pražák, O., Přibáň, P., Pašek, J., Seják, M., & Konopík, M. (2021). Czert—Czech BERT-like model for language representation. ArXiv:2103.13031 [Cs]. http://arxiv.org/abs/2103.13031
Czert-A / Czert-A
Definition: An ALBERT-based language model for Czech.
Définition : Modèle de langage bas sur ALBERT pour le tchèque.
Broader concept: large language model / grand modèle de langue
Application field: generic / générique
Tasks performed: word embedding / plongement lexical
Implements: transformer / transformeur
Input languages: Czech / tchèque
Programming language: Python
Design country: Czech Republic / République tchèque
Based on: ALBERT / ALBERT
Repository: https://github.com/kiv-air/Czert
Reference: Sido, J., Pražák, O., Přibáň, P., Pašek, J., Seják, M., & Konopík, M. (2021). Czert—Czech BERT-like model for language representation. ArXiv:2103.13031 [Cs]. http://arxiv.org/abs/2103.13031
D-Stream / D-Stream
Broader concept: stream clustering / clustering de flux
Implemented by: Massive Online Analysis / Massive Online Analysis
DBScan / DBScan
Also known as: density-based spatial clustering / 
Definition: Clustering algorithm from the density of clusters.
Définition : Algorithme de partitionnement des données à partir de la densité des clusters.
Broader concept: clustering algorithm / algorithme de partitionnement
Implemented by: RWeka§§Texthero§§Textable§§scikit-learn / RWeka§§Texthero§§Textable§§scikit-learn
DBpedia Spotlight / DBpedia Spotlight
Definition: DBpedia Spotlight is a tool for automatically annotating mentions of DBpedia resources in text, providing a solution for linking unstructured information sources to the Linked Open Data cloud through DBpedia.
Définition : DBpedia Spotlight est un outil permettant d'annoter automatiquement les mentions des ressources DBpedia dans le texte, fournissant une solution pour relier les sources d'informations non structurées au cloud Linked Open Data via DBpedia.
Broader concept: software application / application logicielle
Application field: generic / générique
Tasks performed: information extraction§§information filtering§§named entity recognition§§text annotation§§word sense disambiguation / extraction d'information§§filtrage de l'information§§reconnaissance d'entités nommées§§annotation textuelle§§désambiguïsation du sens des mots
Input languages: Danish§§English§§French§§German§§Hungarian§§Italian§§Portuguese§§Russian§§Spanish§§Swedish§§Turkish / danois§§anglais§§français§§allemand§§hongrois§§italien§§portugais§§russe§§espagnol§§suédois§§turc
Programming language: Java§§Scala
Interface: web user interface§§application programming interface / interface utilisateur web§§interface de programmation d’application
Design country: Germany / Allemagne
Licence: Apache License Version 2.0 / Apache License Version 2.0
Repository: https://github.com/dbpedia-spotlight/dbpedia-spotlight-model
Reference: Daiber J., Jakob M., Hokamp C. & Mendes P. N. Improving efficiency and accuracy in multilingual entity extraction, (2013), In I-SEMANTICS 13. https://doi.org/10.1007/978-3-319-19773-9_38§§Mendes P. N., Jakob M., García-Silva A. & Bizer C. DBpedia Spotlight: Shedding Light on the Web of Documents, (2011), in Proceedings of the 7th International Conference on Semantic Systems 18 (Association for Computing Machinery, 2011). https://doi.org/10.1145/2063518.2063519
DISCO Builder / DISCO builder
Definition: DISCO (extracting DIstributionally related words using CO-occurrences) is a Java application that allows to retrieve the semantic similarity between arbitrary words and phrases. The similarities are based on the statistical analysis of very large text collections.
Définition : DISCO est une application Java qui permet d'extraire la similarité sémantique entre des mots et des phrases arbitraires. Les similarités sont basées sur l'analyse statistique de très grandes collections de textes.
Broader concept: Java library / librairie Java
Application field: generic / générique
Tasks performed: word embedding§§lemmatization§§tokenization / plongement lexical§§lemmatisation§§tokenisation
Input languages: Arabic§§English§§French§§German§§Russian / arabe§§anglais§§français§§allemand§§russe
Programming language: Java
Platforms: Linux§§Solaris§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Licence: CC BY 3.0 / CC BY 3.0
DKPro Core / DKPro Core
Definition: DKPro Core is a collection of software components for natural language processing (NLP) based on the Apache UIMA framework.
Définition : DKPro Core est un ensemble de composants logiciels pour le traitement du langage naturel (TAL) basé sur le framework Apache UIMA.
Broader concept: Java library / librairie Java
Tasks performed: semantic role labeling§§word embedding§§chunking§§coreference resolution§§dependency parsing§§language identification§§morphological analysis§§named entity recognition§§PoS tagging§§sentence splitting§§sentiment analysis§§stemming§§tokenization§§topic detection / étiquetage en rôles sémantiques§§plongement lexical§§chunking§§résolution de coréférence§§analyse en dépendances§§identification de la langue§§analyse morphologique§§reconnaissance d'entités nommées§§étiquetage morpho-syntaxique§§découpage de phrases§§analyse de sentiments§§racinisation§§tokenisation§§identification de topics
Implements: latent Dirichlet allocation / allocation de Dirichlet latente
Input languages: Arabic§§Basque§§Bengali§§Bulgarian§§Chinese§§Croatian§§Czech§§Danish§§Dutch§§English§§Estonian§§Finnish§§French§§Galician§§German§§Hungarian§§Italian§§Japanese§§Latin§§Mongolian§§Norwegian§§Persian§§Polish§§Portuguese§§Russian§§Slovak§§Slovenian§§Spanish§§Swahili§§Swedish§§Turkish / arabe§§basque§§bengali§§bulgare§§chinois§§croate§§tchèque§§danois§§néerlandais§§anglais§§estonien§§finnois§§français§§galicien§§allemand§§hongrois§§italien§§japonais§§latin§§mongol§§norvégien§§persan§§polonais§§portugais§§russe§§slovaque§§slovène§§espagnol§§swahili§§suédois§§turc
Programming language: Java
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Design country: Germany / Allemagne
Licence: free to use license / licence libre d'utilisation
Related: generic / générique
Repository: https://github.com/dkpro/dkpro-core
Reference: Eckart de Castilho R. and Gurevych I. A broad-coverage collection of portable NLP components for building shareable analysis pipelines, (2014), In Proceedings of the Workshop on Open Infrastructures and Analysis Frameworks for HLT (OIAF4HLT) at COLING 2014, p 1-11, Dublin, Ireland. https://doi.org/10.3115/v1/W14-5201§§Eckart de Castilho R. and Gurevych I. DKPro-UGD: A Flexible Data-Cleansing Approach to Processing User-Generated Discourse, (2009), In Online-proceedings of the First French-speaking meeting around the framework Apache UIMA, LINA CNRS UMR 6241 - University of Nantes, Nantes, France§§Gurevych I., Mühlhäuser M., Müller C., Steimle J., Weimer M. and Zesch T. , Darmstadt Knowledge Processing Repository Based on UIMA, (2007), In Proceedings of the First Workshop on Unstructured Information Management Architecture at GCSL 2007, Germany, Tübingen
Dagaare / dagaare
Broader concept: natural language / langage naturel
IETF language tag: dga
ISO 639-3: dga
Dagbani / dagbani
Also known as: Dagbanle§§Dagbanli / dagbane§§dagomba
Broader concept: natural language / langage naturel
IETF language tag: dag
ISO 639-2: nic
ISO 639-3: dag
Dangme / adangme
Also known as: Adaŋgbi§§Dangbe / adangbe§§dangme
Broader concept: natural language / langage naturel
IETF language tag: ada
ISO 639-2: ada
ISO 639-3: ada
Danish / danois
Broader concept: natural language / langage naturel
IETF language tag: da
ISO 639-1: da
ISO 639-2: dan
ISO 639-3: dan
Datumbox / Datumbox
Definition: The Datumbox Machine Learning Framework is an open-source framework written in Java which allows the rapid development of Machine Learning and Statistical applications.
Définition : Le framework d'apprentissage automatique Datumbox est un logiciel open-source écrit en Java qui permet le développement rapide d'applications d'apprentissage automatique et de statistiques.
Broader concept: Java library / librairie Java
Tasks performed: keyword extraction§§language identification§§sentiment analysis§§text categorization / extraction de mots-clés§§identification de la langue§§analyse de sentiments§§catégorisation de textes
Implements: Adaboost§§bagging§§classification algorithm§§Dirichlet process mixture model§§linear regression§§logistic regression§§maximum entropy§§naive Bayes classifier§§ordinal regression§§principal component analysis§§stepwise regression§§support vector machine§§hierarchical clustering§§k-means / Adaboost§§bagging§§algorithme de classification§§modèle de mélange de processus Dirichlet§§régression linéaire§§régression logistique§§entropie maximale§§classifieur bayésien naïf§§régression ordinale§§analyse en composantes principales§§régression pas à pas§§machine à vecteurs de support§§partitionnement hiérarchique§§k-moyennes
Programming language: Java
Interface: application programming interface / interface de programmation d’application
Design country: Greece / Grèce
Licence: Apache License Version 2.0 / Apache License Version 2.0
Related: generic / générique
Repository: https://github.com/datumbox/datumbox-framework/
DeBERTa / DeBERTa
Also known as: Decoding-enhanced BERT with disentangled attention / 
Definition: "Transformer-based neural language model DeBERTa (Decoding-enhanced BERT with disentangled attention), which improves previous state-of-the-art PLMs [Pre-trained Language Models] using two novel techniques: a disentangled attention mechanism, and an enhanced mask decoder." (He et al., 2020).
Définition : Modèle de langage neuronal basé sur un transformeur, DeBERTa (Decoding-enhanced BERT with disentangled attention), repose sur un nouveau mécanisme d'attention démêlée un décodeur de masques amélioré (He et al., 2020).
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
Licence: MIT License / licence MIT
Based on: BERT / BERT
Base of: Spark NLP§§Spark NLP Python§§Spark NLP Scala§§polyBERT / Spark NLP§§Spark NLP Python§§Spark NLP Scala§§polyBERT
Repository: https://github.com/microsoft/DeBERTa
Reference: He, P., Liu, X., Gao, J., & Chen, W. (2020). DeBERTa: Decoding-enhanced BERT with Disentangled Attention. https://arxiv.org/abs/2006.03654v1
DeLFT / DeLFT
Definition: DeLFT (Deep Learning Framework for Text) is an Open Source Keras framework for text processing, covering sequence labelling (e.g. named entity tagging) and text classification (e.g. comment classification).
Définition : DeLFT (Deep Learning Framework for Text) est un framework Keras Open Source pour le traitement de textes, couvrant l'étiquetage de séquences (par exemple, l'étiquetage d'entités nommées) et la classification de textes (par exemple, la classification de commentaires).
Broader concept: Java library§§Python library / librairie Java§§librairie Python
Application field: generic / générique
Tasks performed: word embedding§§named entity recognition§§sentiment analysis§§text categorization / plongement lexical§§reconnaissance d'entités nommées§§analyse de sentiments§§catégorisation de textes
Implements: BERT§§ELMo§§recurrent neural network§§RoBERTa§§transformer / BERT§§ELMo§§réseau de neurones récurrents§§RoBERTa§§transformeur
Input languages: English / anglais
Input data: HTML§§pdf
Programming language: Java§§Python
Platforms: Linux§§Windows§§macOS
Interface: command-line interface / interface en ligne de commande
Design country: France / France
Licence: Apache License Version 2.0 / Apache License Version 2.0
Repository: https://github.com/kermitt2/delft
decision tree / arbre de décision
Definition: "A supervised learning model composed of a set of conditions and leaves organized hierarchically." (source:https://developers.google.com/machine-learning/glossary?hl=en#d)
Définition : « Modèle d'apprentissage supervisé composé d'un ensemble de conditions et de feuilles organisées de manière hiérarchique. » (source:https://developers.google.com/machine-learning/glossary?hl=en#d).
Broader concept: classification algorithm / algorithme de classification
Implemented by: Entity fishing§§GATE§§MALLET§§RTextTools§§RWeka§§TextFlows§§TreeTagger§§scikit-learn§§Massive Online Analysis / entity fishing§§GATE§§MALLET§§RTextTools§§RWeka§§TextFlows§§TreeTagger§§scikit-learn§§Massive Online Analysis
DenStream / DenStream
Broader concept: stream clustering / clustering de flux
Implemented by: Massive Online Analysis / Massive Online Analysis
Dendi / dendi
Broader concept: Seychellois Creole / créole seychellois
IETF language tag: ddn
ISO 639-3: ddn
denoising autoencoder / autoencodeur débruiteur
Also known as: DAE / DAE
Definition: "Denoising autoencoders can be viewed either as a regularization option, or as robust autoencoders which can be used for error correction. In these architectures, the input is disrupted by some noise (e.g., additive white Gaussian noise or erasures using Dropout) and the autoencoder is expected to reconstruct the clean version of the input" (Bank et al., 2021).
Définition : « Les autoencodeurs debruiteurs peuvent être considérés soit comme une option de régularisation, soit comme des autoencodeurs robustes qui peuvent être utilisés pour la correction des erreurs. Dans ces architectures, l'entrée est perturbée par un certain bruit (par exemple, un bruit blanc gaussien additif ou par dropout) et l'autoencodeur est censé reconstruire la version propre de l'entrée » (Bank et al., 2021).
Broader concept: autoencoder / autoencodeur
Implemented by: BART§§BARThez§§PLBART§§XLM§§mBART / BART§§BARThez§§PLBART§§XLM§§mBART
Reference: Bank, D., Koenigstein, N., & Giryes, R. (2021). Autoencoders (arXiv:2003.05991). arXiv. https://doi.org/10.48550/arXiv.2003.05991§§Vincent, P., Larochelle, H., Bengio, Y., & Manzagol, P.-A. (2008). Extracting and composing robust features with denoising autoencoders. Proceedings of the 25th International Conference on Machine Learning - ICML ’08, 1096‑1103. https://doi.org/10.1145/1390156.1390294