Results 61 to 70 of about 84,634 (222)
Word sense disambiguation: a survey
, 2015 In this paper, we made a survey on Word Sense Disambiguation (WSD). Near about in all major languages around the world, research in WSD has been conducted upto different extents.
Pal, Alok Ranjan, Saha, Diganta
core +1 more source
Evaluation of Linguistic Features for Word Sense Disambiguation with Self-Organized Document Maps [PDF]
, 2004 Word sense disambiguation automatically determines the appropriate senses of a word in context. We have previously shown that self-organized document maps have properties similar to a large-scale semantic structure that is useful for word sense ...
Linden, Krister
core +1 more source
SensEmBERT: Context-Enhanced Sense Embeddings for Multilingual Word Sense Disambiguation
AAAI Conference on Artificial Intelligence, 2020 Contextual representations of words derived by neural language models have proven to effectively encode the subtle distinctions that might occur between different meanings of the same word.
Bianca Scarlini +2 more
semanticscholar +1 more source
Multi-feature Word Sense Disambiguation Based on Dependency Parsing Analysis [PDF]
Jisuanji gongcheng, 2017 Word Sense Disambiguation(WSD) plays an important role in machine translation,information retrieval and speech semantic recognition.In order to improve the quality of disambiguation and refine the feature,a multi-feature granularity WSD scheme is ...
SHI Zhaopeng,ZOU Xuxi,XIANG Runzhao
doaj +1 more source
Biomedical Word Sense Disambiguation Based on Graph Attention Networks
IEEE Access, 2022 Biomedical words have many semantics. Biomedical word sense disambiguation (WSD) is an important research issue in biomedicine field. Biomedical WSD refers to the process of determining meanings of ambiguous word according to its context.
Chun-Xiang Zhang +2 more
doaj +1 more source
SupWSD: a flexible toolkit for supervised word sense disambiguation [PDF]
, 2017 In this demonstration we present SupWSD, a Java API for supervised Word Sense Disambiguation (WSD). This toolkit includes the implementation of a state-of-the-art supervised WSD system, together with a Natural Language Processing pipeline for ...
DELLI BOVI, Claudio +2 more
core +1 more source
Incorporating Glosses into Neural Word Sense Disambiguation [PDF]
Annual Meeting of the Association for Computational Linguistics, 2018 Word Sense Disambiguation (WSD) aims to identify the correct meaning of polysemous words in the particular context. Lexical resources like WordNet which are proved to be of great help for WSD in the knowledge-based methods.
Fuli Luo +4 more
semanticscholar +1 more source
Leveraging Word-Formation Knowledge for Chinese Word Sense Disambiguation
Conference on Empirical Methods in Natural Language Processing, 2021 In parataxis languages like Chinese, word meanings are constructed using specific wordformations, which can help to disambiguate word senses. However, such knowledge is rarely explored in previous word sense disambiguation (WSD) methods.
Hua Zheng +6 more
semanticscholar +1 more source
Word Sense Disambiguation: A Unified Evaluation Framework and Empirical Comparison
Conference of the European Chapter of the Association for Computational Linguistics, 2017 Word Sense Disambiguation is a long-standing task in Natural Language Processing, lying at the core of human language understanding. However, the evaluation of automatic systems has been problematic, mainly due to the lack of a reliable evaluation ...
Roberto Navigli +2 more
semanticscholar +1 more source
Learning to Learn to Disambiguate: Meta-Learning for Few-Shot Word Sense Disambiguation [PDF]
Findings, 2020 The success of deep learning methods hinges on the availability of large training datasets annotated for the task of interest. In contrast to human intelligence, these methods lack versatility and struggle to learn and adapt quickly to new tasks, where ...
Nithin Holla +3 more
semanticscholar +1 more source