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Sense Space for Word Sense Disambiguation
2018 IEEE International Conference on Big Data and Smart Computing (BigComp), 2018Word sense disambiguation is essential for semantic analysis in many natural language-related applications, such as information retrieval, data mining, and machine translation. One of the effective models for word sense disambiguation is the word space model that represents context vectors and sense vectors in a word vector space.
Myung Yun Kang +2 more
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Malayalam word sense disambiguation
2010 IEEE International Conference on Computational Intelligence and Computing Research, 2010This paper presents an outline of our work to develop a word sense disambiguation system in Malayalam. Word sense disambiguation (WSD) is a linguistically based mechanism for automatically defining the correct sense of a word in the context. WSD is a long standing problem in computational linguistics.
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Probabilistic word sense disambiguation
Computer Speech & Language, 2004We present a theoretically motivated method for creating probabilistic word sense disambiguation (WSD) systems. The method works by composing multiple probabilistic components: such modularity is made possible by an application of Bayesian statistics and Lidstone's smoothing method. We show that a probabilistic WSD system created along these lines is a
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Arabic Word Sense Disambiguation - Survey
2017 International Conference on New Trends in Computing Sciences (ICTCS), 2017One of the central challenging and most difficult problems in Natural Language Processing is the capability to identify what a word means with respect to a context in which it comes into view. This problem is called Word Sense Disambiguation (WSD). It is ubiquitous across all languages but it has greater challenges in Semitic languages like Arabic ...
Marwah Alian +2 more
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Word sense disambiguation methods
Programming and Computer Software, 2010Word sense disambiguation is one of the key tasks of text processing. It consists in the determination of senses of words or compound terms in accordance with the context where they were used. The word sense disambiguation problem originated in the 1950s as a subtask of machine translation.
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1988
Computational lexical approaches to disambiguation divide into syntactic category assignment such as whether farm is a noun or a verb (Milne, 1986) and word sense disambiguation within syntactic category.9 The latter problem is the subject of this chapter.
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Computational lexical approaches to disambiguation divide into syntactic category assignment such as whether farm is a noun or a verb (Milne, 1986) and word sense disambiguation within syntactic category.9 The latter problem is the subject of this chapter.
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Word Sense Disambiguation Based on Word Sense Clustering
2006In this paper we address the problem of Word Sense Disambiguation by introducing a knowledge-driven framework for the disambiguation of nouns. The proposal is based on the clustering of noun sense representations and it serves as a general model that includes some existing disambiguation methods.
Henry Anaya-Sánchez +2 more
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Word Sense Disambiguation Using Wikipedia
2013This paper describes explorations in word sense disambiguation using Wikipedia as a source of sense annotations. Through experiments on four different languages, we show that the Wikipedia-based sense annotations are reliable and can be used to construct accurate sense classifiers.
Bharath Dandala +2 more
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Corpus and Word Sense Disambiguation
2018Every natural language has a large set of words, which, when these are used in a piece of text, may vary in sense denotation. It has been noted that for ages that context, where these words are found to be used, can play an explicit and active role to influence the words to deviate from the original sense to generate new senses.
Niladri Sekhar Dash, L. Ramamoorthy
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Word Sense Disambiguation Using IndoWordNet
2016Word sense disambiguation (WSD) is considered as one of the toughest problems in the field of natural language processing. IndoWordNet is a linked structure of WordNets of major Indian languages. Recently, several IndoWordNet-based WSD approaches have been proposed and implemented for Indian languages.
Sudha Bhingardive, Pushpak Bhattacharyya
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