Results 91 to 100 of about 84,634 (222)
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
doaj
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
core +2 more sources
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
core +1 more source
Improving Word Sense Disambiguation with Translations
Conference on Empirical Methods in Natural Language Processing, 2020 It has been conjectured that multilingual information can help monolingual word sense disambiguation (WSD). However, existing WSD systems rarely consider multilingual information, and no effective method has been proposed for improving WSD by generating ...
Yixing Luan +3 more
semanticscholar +1 more source
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
doaj +2 more sources
Word sense disambiguation criteria: a systematic study
, 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
core +2 more sources
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
semanticscholar +1 more source
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
doaj +1 more source
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
doaj +1 more source
Selective Sampling for Example-based Word Sense Disambiguation
, 1998 This paper proposes an efficient example sampling method for example-based word sense disambiguation systems. To construct a database of practical size, a considerable overhead for manual sense disambiguation (overhead for supervision) is required.
Fujii, Atsushi +3 more
core +1 more source