Results 61 to 70 of about 58,551 (288)
Interpretability in Word Sense Disambiguation using Tsetlin Machine
International Conference on Agents and Artificial Intelligence, 2021 : Word Sense Disambiguation (WSD) is a longstanding unresolved task in Natural Language Processing. The challenge lies in the fact that words with the same spelling can have completely different senses, sometimes depending on subtle characteristics of ...
Rohan Kumar Yadav +3 more
semanticscholar +1 more source
Word sense disambiguation to improve precision for ambiguous queries [PDF]
Open Computer Science, 2012 Adrian-Gabriel Chifu, Radu Tudor Ionescu
openalex +2 more sources
AMuSE-WSD: An All-in-one Multilingual System for Easy Word Sense Disambiguation
Conference on Empirical Methods in Natural Language Processing, 2021 Over the past few years, Word Sense Disambiguation (WSD) has received renewed interest: recently proposed systems have shown the remarkable effectiveness of deep learning techniques in this task, especially when aided by modern pretrained language models.
Riccardo Orlando +4 more
semanticscholar +1 more source
Using Linked Disambiguated Distributional Networks for Word Sense Disambiguation [PDF]
Proceedings of the 1st Workshop on Sense, Concept and Entity
Representations and their Applications, 2017 We introduce a new method for unsupervised knowledge-based word sense disambiguation (WSD) based on a resource that links two types of sense-aware lexical networks: one is induced from a corpus using distributional semantics, the other is manually constructed.
Alexander Panchenko +3 more
openaire +2 more sources
Annual Meeting of the Association for Computational Linguistics, 2021 Lately proposed Word Sense Disambiguation (WSD) systems have approached the estimated upper bound of the task on standard evaluation benchmarks. However, these systems typically implement the disambiguation of words in a document almost independently ...
Ming Wang, Yinglin Wang
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
Adapting BERT for Word Sense Disambiguation with Gloss Selection Objective and Example Sentences [PDF]
Findings, 2020 Domain adaptation or transfer learning using pre-trained language models such as BERT has proven to be an effective approach for many natural language processing tasks.
Boon Peng Yap +2 more
semanticscholar +1 more source
A Corpus-Based Word Sense Disambiguation For Geez Language
Ethiopian Journal of Science and Sustainable Development, 2021 In natural language processing, languages have a number of ambiguous words and solving such kind of problem for the language can help the development of word sense disambiguation using corpusbased Approach.
Amlakie Aschale Alemu, Kinde Anlay Fante
doaj +1 more source
Attention Neural Network for Biomedical Word Sense Disambiguation
Discrete Dynamics in Nature and Society, 2022 In order to improve the disambiguation accuracy of biomedical words, this paper proposes a disambiguation method based on the attention neural network. The biomedical word is viewed as the center. Morphology, part of speech, and semantic information from
Chun-Xiang Zhang +4 more
doaj +1 more source
Biomedical Word Sense Disambiguation with Word Embeddings [PDF]
, 2017 There is a growing need for automatic extraction of information and knowledge from the increasing amount of biomedical and clinical data produced, namely in textual form. Natural language processing comes in this direction, helping in tasks such as information extraction and information retrieval.
Antunes, Rui, Matos, Sérgio
openaire +2 more sources