Sentiment analysis forms part of a major component of Natural Language Processing (NLP),
even though continuous improvements in NLP are being made, word disambiguation …

Sentiment analysis is crucial for many tasks and applications. For example, it is developed
into a helpful tool for predicting market trends, monitoring social media, and being a reliable …

This study explores the use of Evolutionary Game Theory (EGT) for the task of sentiment
analysis. The proposed approach involves the use of EGT concepts to disambiguate the …

Abstract Word Sense Disambiguation (WSD) has been a basic and on-going issue since its
introduction in natural language processing (NLP) community. Its application lies in many …

This research study aimed to compare the performance of Support Vector Machine (SVM)
and Word Sense Disambiguation (WSD) in the context of sentiment analysis. The research …

In the computational linguistics the extraction of actual sense of words from text has a long
history in the field. Due to its importance in the field of sentiment analysis it is considered the …

WSD (Word Sense Disambiguation) is a common issue in Natural Language Processing
(NLP) and Machine Learning technology. In NLP, word sense disambiguation is described …

Lexical ambiguity means that a word can be interpreted as two or more meanings, such as
homonym and polysemy, and there are many cases of word sense ambiguation in words …

Word Sense Disambiguation (WSD) is a challenging field of research in natural language
processing. Enhanced WSD techniques have the potential to significantly enhance the …

This data paper introduces a comprehensive dataset tailored for word sense disambiguation
tasks, explicitly focusing on a hundred polysemous words frequently employed in Modern …