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1
Word Sense Induction with Attentive Context Clustering
In: https://hal.archives-ouvertes.fr/hal-03586559 ; 2022 (2022)
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Word Sense Induction with Attentive Context Clustering
In: https://hal.inria.fr/hal-03586559 ; 2022 (2022)
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3
Word Sense Induction with Attentive Context Clustering
In: https://hal.archives-ouvertes.fr/hal-03586559 ; 2022 (2022)
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4
Event/Nonevent Noun Disambiguation Test Set ...
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5
Event/Nonevent Noun Disambiguation Test Set ...
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6
Russian Event Noun Disambiguation Test Set (6X200) ...
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7
Russian Event Noun Disambiguation Test Set (6X200) ...
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8
Multi-sense Embeddings through a Word Sense Disambiguation Process
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9
Crowdsourcing lexical semantic judgements from bilingual dictionary users
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10
Uso de representaciones vectoriales de las palabras para la detección de dobles sentidos (puns)
Carrasco Gómez, Pascual Andrés. - : Universitat Politècnica de València, 2017
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11
Unsupervised all-words sense distribution learning
Bennett, Andrew. - 2016
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12
Word Sense Disambiguation Based on Large Scale Polish CLARIN Heterogeneous Lexical Resources
In: Cognitive Studies | Études cognitives; No 15 (2015); 269-292 ; 2392-2397 (2015)
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13
Translation of keywords between English and Swedish ; Översättning av nyckelord mellan engelska och svenska
Klein Rosmar, Sander; Ahmady, Tobias. - : KTH, Data- och elektroteknik, 2014
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14
ABSTRACT Long Tail in Weighted Lexical Networks
In: http://hal.inria.fr/docs/00/81/62/36/PDF/COGALEX2012-ML-v4.pdf (2013)
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15
Désambiguisation de sens par modèles de contextes et son application à la Recherche d’Information
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16
Désambiguisation de sens par modèles de contextes et son application à la Recherche d’Information
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17
SemEval-2010 Task 2: Cross-Lingual Lexical Substitution
In: Association for Computational Linguistics (ACL) Workshop on Semantic Evaluations (SemEval), 2010, Uppsala, Sweden (2010)
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18
Word sense disambiguation: a survey
In: http://www.dsi.uniroma1.it/~navigli/pubs/ACM_Survey_2009_Navigli.pdf (2009)
Abstract: Word sense disambiguation (WSD) is the ability to identify the meaning of words in context in a computational manner. WSD is considered an AI-complete problem, that is, a task whose solution is at least as hard as the most difficult problems in artificial intelligence. We introduce the reader to the motivations for solving the ambiguity of words and provide a description of the task. We overview supervised, unsupervised, and knowledge-based approaches. The assessment of WSD systems is discussed in the context of the Senseval/Semeval campaigns, aiming at the objective evaluation of systems participating in several different disambiguation tasks. Finally, applications, open problems, and future directions are discussed.
Keyword: Algorithms; Categories and Subject Descriptors; Experimentation; I.2.4 [Artificial Intelligence; I.2.7 [Artificial Intelligence; Knowledge Representation Formalisms and Methods General Terms; lexical ambiguity; lexical semantics; Measurement; Natural Language Processing—Text analysis; Performance Additional Key Words and Phrases; semantic annotation ACM Reference Format; sense annotation; Word sense disambiguation; word sense discrimination; WSD
URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.153.8457
http://www.dsi.uniroma1.it/~navigli/pubs/ACM_Survey_2009_Navigli.pdf
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19
Regular Polysemy in WordNet
In: ISSN: 0175-1336 ; Journal for language technology and computational linguistics ; https://hal.archives-ouvertes.fr/hal-00611244 ; Journal for language technology and computational linguistics, GSCL (Gesellschaft für Sprachtechnologie und Computerlinguistik) 2009, 24 (2), pp.5-18 (2009)
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20
The Treatment of Word Sense Inventories in the ‘LACELL WSD Project’
In: International Journal of English Studies; Vol. 9 No. 3 (2009): Special Issue; 21-38 ; International Journal of English Studies; Vol. 9 Núm. 3 (2009): Special Issue; 21-38 ; 1989-6131 ; 1578-7044 (2009)
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