A Decision Tree of Bigrams is an Accurate Predictor of Word Sense [PDF]
arXiv, 2001 This paper presents a corpus-based approach to word sense disambiguation where a decision tree assigns a sense to an ambiguous word based on the bigrams that occur nearby. This approach is evaluated using the sense-tagged corpora from the 1998 SENSEVAL word sense disambiguation exercise.
arxiv
A metaheuristic with a neural surrogate function for Word Sense Disambiguation
Machine Learning with Applications, 2022 Word Sense Disambiguation (WSD) is one of the earliest problems in natural language processing which aims to determine the correct sense of words in context.
Azim Keshavarzian Nodehi +1 more
doaj
WORD SENSE DISAMBIGUATION USING FUZZY SEMANTIC-BASED STRING SIMILARITY MODEL
Malaysian Journal of Computing, 2018 Sentences are the language of human communication. This communication medium is so fluid that words and meaning can have many interpretations by readers.
Amir Abd-Rashid, Shuzlina Abdul-Rahman, Nor Nadiah Yusof, Azlinah Mohamed
doaj +1 more source
Is Word Sense Disambiguation just one more NLP task? [PDF]
arXiv, 1999 This paper compares the tasks of part-of-speech (POS) tagging and word-sense-tagging or disambiguation (WSD), and argues that the tasks are not related by fineness of grain or anything like that, but are quite different kinds of task, particularly becuase there is nothing in POS corresponding to sense novelty.
arxiv
A Systematic Analysis of Various Word Sense Disambiguation Approaches
Advances in Distributed Computing and Artificial Intelligence JournalThe process of finding the correct sense of a word in context is known as word sense disambiguation (WSD). In the field of natural language processing, WSD has become a growing research area.
Chandra Ganesh +3 more
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What is word sense disambiguation good for? [PDF]
Proc. Natural Language Processing Pacific Rim Symposium. Phuket,
Thailand. December 1997. Pp 209--214., 1997 Word sense disambiguation has developed as a sub-area of natural language processing, as if, like parsing, it was a well-defined task which was a pre-requisite to a wide range of language-understanding applications. First, I review earlier work which shows that a set of senses for a word is only ever defined relative to a particular human purpose, and ...
arxiv
Comparative Experiments on Disambiguating Word Senses: An Illustration of the Role of Bias in Machine Learning [PDF]
arXiv, 1996 This paper describes an experimental comparison of seven different learning algorithms on the problem of learning to disambiguate the meaning of a word from context. The algorithms tested include statistical, neural-network, decision-tree, rule-based, and case-based classification techniques.
arxiv
Random Walks for Knowledge-Based Word Sense Disambiguation
Computational Linguistics, 2021 Eneko Agirre +2 more
doaj +1 more source
deepBioWSD: effective deep neural word sense disambiguation of biomedical text data. [PDF]
J Am Med Inform Assoc, 2019 Pesaranghader A +3 more
europepmc +1 more source
Biomedical word sense disambiguation with bidirectional long short-term memory and attention-based neural networks. [PDF]
BMC Bioinformatics, 2019 Zhang C, Biś D, Liu X, He Z.
europepmc +1 more source