Open AccessWord Sense Disambiguation Models Emerging Trends: A Comparative Analysis
Author(s) -
Nemika Tyagi,
Sudeshna Chakraborty,
. Jyotsna,
Anshuman Kumar,
Nzanzu Katasohire Romeo
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2161/1/012035
Subject(s) - ambiguity , word sense disambiguation , leverage (statistics) , computer science , semeval , natural language processing , word (group theory) , domain (mathematical analysis) , artificial intelligence , natural language , linguistics , mathematics , wordnet , mathematical analysis , philosophy , management , economics , programming language , task (project management)
Word Sense Disambiguation (WSD) arises due to the presence of ambiguity in the text during the semantic analysis of natural languages. It is a major unsolved problem in the area of Natural Language Processing (NLP) and its applications. This paper explores and reviews WSD algorithms that have contributed to, or created state-of-art solutions in recent years. Moreover, this paper also aims to analyze the recent technological trends in the domain of WSD which can give us leverage to identify the possible future trajectory of the search for better WSD solutions.