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Disambiguation of Medical Abbreviations in French with Supervised Methods
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In: Studies in Health Technology and Informatics ; https://hal.archives-ouvertes.fr/hal-03335532 ; Studies in Health Technology and Informatics, 2021, ⟨10.3233/shti210171⟩ (2021)
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| 2 |
Italian Sense Inventory
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Poli, Francesca. - : Università di Pisa, 2021. : Istituto di Linguistica Computazionale “A. Zampolli” - Consiglio Nazionale delle Ricerche (ILC-CNR), 2021
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| 3 |
Word Sense Disambiguation Using Prior Probability Estimation Based on the Korean WordNet
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In: Electronics; Volume 10; Issue 23; Pages: 2938 (2021)
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Abstract:
Supervised disambiguation using a large amount of corpus data delivers better performance than other word sense disambiguation methods. However, it is not easy to construct large-scale, sense-tagged corpora since this requires high cost and time. On the other hand, implementing unsupervised disambiguation is relatively easy, although most of the efforts have not been satisfactory. A primary reason for the performance degradation of unsupervised disambiguation is that the semantic occurrence probability of ambiguous words is not available. Hence, a data deficiency problem occurs while determining the dependency between words. This paper proposes an unsupervised disambiguation method using a prior probability estimation based on the Korean WordNet. This performs better than supervised disambiguation. In the Korean WordNet, all the words have similar semantic characteristics to their related words. Thus, it is assumed that the dependency between words is the same as the dependency between their related words. This resolves the data deficiency problem by determining the dependency between words by calculating the χ2 statistic between related words. Moreover, in order to have the same effect as using the semantic occurrence probability as prior probability, which is used in supervised disambiguation, semantically related words of ambiguous vocabulary are obtained and utilized as prior probability data. An experiment was conducted with Korean, English, and Chinese to evaluate the performance of our proposed lexical disambiguation method. We found that our proposed method had better performance than supervised disambiguation methods even though our method is based on unsupervised disambiguation (using a knowledge-based approach).
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Keyword:
data mining; information extraction; knowledge-based model; Korean WordNet; word sense disambiguation
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URL: https://doi.org/10.3390/electronics10232938
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| 4 |
A Knowledge-Based Sense Disambiguation Method to Semantically Enhanced NL Question for Restricted Domain
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In: Information ; Volume 12 ; Issue 11 (2021)
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| 5 |
Improving the Performance of Vietnamese&ndash ; Korean Neural Machine Translation with Contextual Embedding
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In: Applied Sciences ; Volume 11 ; Issue 23 (2021)
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| 6 |
NERWS: Towards Improving Information Retrieval of Digital Library Management System Using Named Entity Recognition and Word Sense
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In: Big Data and Cognitive Computing ; Volume 5 ; Issue 4 (2021)
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| 7 |
SemEval-2021 Task 2: Multilingual and Cross-lingual Word-in-Context Disambiguation (MCL-WiC) ...
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| 8 |
SemEval-2021 Task 2: Multilingual and Cross-lingual Word-in-Context Disambiguation (MCL-WiC) ...
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| 9 |
Semantically-oriented text planning for automatic summarization
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In: TDX (Tesis Doctorals en Xarxa) (2021)
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| 10 |
FlauBERT: Unsupervised Language Model Pre-training for French
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In: Proceedings of the 12th Language Resources and Evaluation Conference ; LREC ; https://hal.archives-ouvertes.fr/hal-02890258 ; LREC, 2020, Marseille, France (2020)
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| 11 |
FlauBERT : Unsupervised Language Model Pre-training for French ; FlauBERT : des modèles de langue contextualisés pré-entraînés pour le français
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In: Actes de la 6e conférence conjointe Journées d'Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Volume 2 : Traitement Automatique des Langues Naturelles ; 6e conférence conjointe Journées d'Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Volume 2 : Traitement Automatique des Langues Naturelles ; https://hal.archives-ouvertes.fr/hal-02784776 ; 6e conférence conjointe Journées d'Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Volume 2 : Traitement Automatique des Langues Naturelles, Jun 2020, Nancy, France. pp.268-278 (2020)
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| 12 |
Disambiguation of abbreviations from the medical domain. ; La désambiguisation des abréviations du domaine médical
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In: Actes de la 6e conférence conjointe Journées d'Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Volume 3 : Rencontre des Étudiants Chercheurs en Informatique pour le TAL ; 6e conférence conjointe Journées d'Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Volume 3 : Rencontre des Étudiants Chercheurs en Informatique pour le TAL ; https://hal.archives-ouvertes.fr/hal-02786196 ; 6e conférence conjointe Journées d'Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Volume 3 : Rencontre des Étudiants Chercheurs en Informatique pour le TAL, Jun 2020, Nancy, France. pp.151-163 ; https://jep-taln2020.loria.fr/ (2020)
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| 13 |
Joint Neural Models of Word Sense Disambiguation and Machine Translation ; Modèles neuronaux joints de désambiguïsation lexicale et de traduction automatique
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In: https://tel.archives-ouvertes.fr/tel-03027723 ; Informatique et langage [cs.CL]. Université Grenoble Alpes, 2020. Français (2020)
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| 14 |
Joint Neural Models of Word Sense Disambiguation and Machine Translation ; Modèles neuronaux joints de désambiguïsation lexicale et de traduction automatique
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In: https://tel.archives-ouvertes.fr/tel-03033118 ; Intelligence artificielle [cs.AI]. Université Grenoble Alpes [2020-.], 2020. Français. ⟨NNT : 2020GRALM032⟩ (2020)
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| 16 |
UPC: An Open Word-Sense Annotated Parallel Corpora for Machine Translation Study
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In: Applied Sciences ; Volume 10 ; Issue 11 (2020)
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| 17 |
The STEM-ECR Dataset: Grounding Scientific Entity References in STEM Scholarly Content to Authoritative Encyclopedic and Lexicographic Sources ...
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| 18 |
An Evaluation Benchmark for Testing the Word Sense Disambiguation Capabilities of Machine Translation Systems ...
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| 19 |
An Evaluation Benchmark for Testing the Word Sense Disambiguation Capabilities of Machine Translation Systems ...
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| 20 |
An Evaluation Benchmark for Testing the Word Sense Disambiguation Capabilities of Machine Translation Systems ...
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