Assamese Word Sense Disambiguation using Cuckoo Search Algorithm

In communication, textual data are a vital attribute. In all languages, ambiguous or polysemous words' meaning changes depending on the context in which they are used. The ability to determine the ambiguous word's correct meaning is a Know-distill challenging task in natural language processing (NLP). Word sense disambiguation (WSD) is an NLP process to analyze and determine the correct meaning of polysemous words in a text. WSD is a computational linguistics task that automatically identifies the polysemous word's set of senses. Based on the context some word comes into view, WSD recognizes and tags the word to its correct priori known meaning. Semitic languages like Arabic have even more significant challenges than other languages since Arabic lacks diacritics, standardization, and a massive shortage of available resources.Recently, many approaches and techniques have been suggested to solve word ambiguity dilemmas in many different ways and several languages. In this review paper, an extensive survey of research works is presented, seeking to solve Arabic word sense disambiguation with the existing AWSD datasets.

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A comprehensive review on Arabic word sense disambiguation for natural language processing applications

Kaddoura

Ahmed

Hemanth

2022

WIREs Data Min & Knowl

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Assamese Word Sense Disambiguation using Cuckoo Search Algorithm

Cited by 3 publications

References 6 publications

A comprehensive review on Arabic word sense disambiguation for natural language processing applications

A comprehensive review on Arabic word sense disambiguation for natural language processing applications

Climbing Keyboard: A Tilt-Based Selection Keyboard Entry for Virtual Reality

‘What’s the word? That’s the word!’: linguistic features of Filipino queer language

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