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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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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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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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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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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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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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An Evaluation Benchmark for Testing the Word Sense Disambiguation Capabilities of Machine Translation Systems ...
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An Evaluation Benchmark for Testing the Word Sense Disambiguation Capabilities of Machine Translation Systems ...
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An Evaluation Benchmark for Testing the Word Sense Disambiguation Capabilities of Machine Translation Systems ...
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Word Sense Disambiguation Using Cosine Similarity Collaborates with Word2vec and WordNet
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In: Future Internet ; Volume 11 ; Issue 5 (2019)
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Knowledge-Based Method for Word Sense Disambiguation by Using Hindi WordNet ...
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Knowledge-Based Method for Word Sense Disambiguation by Using Hindi WordNet ...
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RUSSE'2018: Human-Annotated Sense-Disambiguated Word Contexts for Russian ...
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RUSSE'2018: Human-Annotated Sense-Disambiguated Word Contexts for Russian ...
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Crowdsourcing lexical semantic judgements from bilingual dictionary users
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A Gloss Composition and Context Clustering Based Distributed Word Sense Representation Model
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In: Entropy ; Volume 17 ; Issue 9 ; Pages 6007-6024 (2015)
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Abstract:
In recent years, there has been an increasing interest in learning a distributed representation of word sense. Traditional context clustering based models usually require careful tuning of model parameters, and typically perform worse on infrequent word senses. This paper presents a novel approach which addresses these limitations by first initializing the word sense embeddings through learning sentence-level embeddings from WordNet glosses using a convolutional neural networks. The initialized word sense embeddings are used by a context clustering based model to generate the distributed representations of word senses. Our learned representations outperform the publicly available embeddings on half of the metrics in the word similarity task, 6 out of 13 sub tasks in the analogical reasoning task, and gives the best overall accuracy in the word sense effect classification task, which shows the effectiveness of our proposed distributed distribution learning model.
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Keyword:
distributed representation; lexical semantic compositionality; natural language processing; word sense disambiguation
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URL: https://doi.org/10.3390/e17096007
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Dynamic topic adaptation for improved contextual modelling in statistical machine translation
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Methods for open information extraction and sense disambiguation on natural language text ; Methoden der Offenen Informationsextraktion und Bedeutungsdisambiguierung in Texten
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