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Word sense disambiguation criteria: a systematic study [PDF]
Proceedings of the 20th international conference on Computational Linguistics - COLING '04, 2004 This article describes the results of a systematic in-depth study of the criteria used for word sense disambiguation. Our study is based on 60 target words: 20 nouns, 20 adjectives and 20 verbs.
Audibert, Laurent
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Sense Unveiled: Enhancing Urdu Corpus for Nuanced Word Sense Disambiguation
IEEE AccessAmbiguity in word meanings presents a significant challenge in natural language processing, necessitating robust techniques for Word Sense Disambiguation (WSD).
Sarfraz Bibi +2 more
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Word Sense Disambiguation Focusing on POS Tag Disambiguation in Persian:
International Journal of Information Science and Management, 2019 The present study deals with ambiguity at word level focusing on homographs. In different languages, homographs may cause ambiguity in text processing. In Persian, the number of homographs is high due to its orthographic structure as well as its complex ...
Elham Alayiaboozar +2 more
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An Optimized Lesk-Based Algorithm for Word Sense Disambiguation
Open Computer Science, 2016 Computational complexity is a characteristic of almost all Lesk-based algorithms for word sense disambiguation (WSD). In this paper, we address this issue by developing a simple and optimized variant of the algorithm using topic composition in documents ...
Ayetiran Eniafe Festus, Agbele Kehinde
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Neural Sequence Learning Models for Word Sense Disambiguation
Conference on Empirical Methods in Natural Language Processing, 2017 Word Sense Disambiguation models exist in many flavors. Even though supervised ones tend to perform best in terms of accuracy, they often lose ground to more flexible knowledge-based solutions, which do not require training by a word expert for every ...
Alessandro Raganato +2 more
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Journal of Language ModellingWe develop a three-part approach to Verb Sense Disambiguation (VSD) in German. After considering a set of lexical resources and corpora, we arrive at a statistically motivated selection of a subset of verbs and their senses from GermaNet.
Dominik Mattern +3 more
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Toward Universal Word Sense Disambiguation Using Deep Neural Networks
IEEE Access, 2019 Traditionally, approaches based on neural networks to solve the problem of disambiguation of the meaning of words (WSD) use a set of classifiers at the end, which results in a specialization in a single set of words-those for which they were trained ...
Hiram Calvo +3 more
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Evaluating Feature Extraction Methods for Biomedical Word Sense Disambiguation [PDF]
, 2017 Evaluating Feature Extraction Methods for Biomedical WSD Clint Cuffy, Sam Henry and Bridget McInnes, PhD Virginia Commonwealth University, Richmond, Virginia, USA Introduction.
Cuffy, Clint A +2 more
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Integrating Weakly Supervised Word Sense Disambiguation into Neural Machine Translation
, 2018 This paper demonstrates that word sense disambiguation (WSD) can improve neural machine translation (NMT) by widening the source context considered when modeling the senses of potentially ambiguous words.
Henderson, James +3 more
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Lexical Chaining and Word-Sense-Disambiguation [PDF]
, 2012 Lexical chains algorithms attempt to find sequences of words in a document that are closely related semantically. Such chains have been argued to provide a good indication of the topics covered by the document without requiring a deeper analysis of the ...
Nelken, Rani, Shieber, Stuart M.
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