2016
DOI: 10.14569/ijacsa.2016.070106
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Automatic Approach for Word Sense Disambiguation Using Genetic Algorithms

Abstract: Abstract-Word sense disambiguation (WSD) is a significant field in computational linguistics as it is indispensable for many language understanding applications. Automatic processing of documents is made difficult because of the fact that many of the terms it contain ambiguous. Word Sense Disambiguation (WSD) systems try to solve these ambiguities and find the correct meaning. Genetic algorithms can be active to resolve this problem since they have been effectively applied for many optimization problems. In th… Show more

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Cited by 3 publications
(2 citation statements)
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“…In the field of WSD, three main strategies are commonly employed: knowledge-based methods, machine learning algorithms, and unsupervised methods [9]. Knowledge-based methods rely on linguistic resources such as dictionaries to determine word meanings.…”
Section: Literature Reviewmentioning
confidence: 99%
“…In the field of WSD, three main strategies are commonly employed: knowledge-based methods, machine learning algorithms, and unsupervised methods [9]. Knowledge-based methods rely on linguistic resources such as dictionaries to determine word meanings.…”
Section: Literature Reviewmentioning
confidence: 99%
“…GA works on a number of candidate solutions, called population, and contains multiple coding for the parameter specified at the same time [11]. To resolve image clustering, the population was started using 50 chromosomes of equal length in two different ways:…”
Section: Population Representation and Initializationmentioning
confidence: 99%