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What is Word Sense Disambiguation

Chapter 4
Natural Language Processing for Global and Local Business
Word sense disambiguation is described as a process of recognizing the implication of a term with respect to the context of the sentence. This problem arises when the same word can have diverse meanings in various contexts.
Published in Chapter:
Sentiment Analysis as a Restricted NLP Problem
Akshi Kumar (Delhi Technological University, India) and Divya Gupta (Galgotias University, India)
Copyright: © 2021 |Pages: 32
DOI: 10.4018/978-1-7998-4240-8.ch004
Abstract
With the accelerated evolution of social networks, there is a tremendous increase in opinions by the people about products or services. While this user-generated content in natural language is intended to be valuable, its large amounts require use of content mining methods and NLP to uncover the knowledge for various tasks. In this study, sentiment analysis is used to analyze and understand the opinions of users using statistical approaches, knowledge-based approaches, hybrid approaches, and concept-based ontologies. Unfortunately, sentiment analysis also experiences a range of difficulties like colloquial words, negation handling, ambiguity in word sense, coreference resolution, which highlight another perspective emphasizing that sentiment analysis is certainly a restricted NLP problem. The purpose of this chapter is to discover how sentiment analysis is a restricted NLP problem. Thus, this chapter discussed the concept of sentiment analysis in the field of NLP and explored that sentiment analysis is a restricted NLP problem due to the sophisticated nature of natural language.
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Chapter 15
User Profiles for Personalizing Digital Libraries
The problem of determining in which sense a word having a number of distinct senses is used in a given sentence.
Published in Chapter: User Profiles for Personalizing Digital Libraries; From: Handbook of Research on Digital Libraries: Design, Development, and Impact
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Chapter 6
Machine Learning Approach for Kashmiri Word Sense Disambiguation
The task of deciding the most relevant sense of a dubious term that has numerous potential meanings or senses is called word sense disambiguation. This relevant sense of the term is decided by the surrounding words.
Published in Chapter: Machine Learning Approach for Kashmiri Word Sense Disambiguation; From: Empowering Low-Resource Languages With NLP Solutions
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Chapter 18
Effective Entity Linking and Disambiguation Algorithms for User-Generated Content (UGC)
In computational linguistics, word-sense disambiguation (WSD) is an open problem of natural language processing and ontology. WSD is identifying which sense of a word (i.e., meaning) is used in a sentence, when the word has multiple meanings.
Published in Chapter: Effective Entity Linking and Disambiguation Algorithms for User-Generated Content (UGC); From: Handbook of Research on Contemporary Perspectives on Web-Based Systems
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Chapter 7
Attempting to Model Sense Division for Word Sense Disambiguation
In computational linguistics, word sense disambiguation is the process of identifying which sense of a word—having a number of distinct senses—is used in a given sentence. For example, consider the word corn, three distinct senses of which are: ?1. Seed of any various grain, chiefly wheat, oats, rye and maize; such plants while growing ?2. Music, verse, drama, etc that is banal, sentimental or hackneyed. ?3. Small, often painful, area of hardened skin in the foot, esp on the toe ?and the sentence: ?This romantic ballad is pure corn. ?To a human it is obvious that this sentence is using the word corn in the second sense above. Although this seems obvious to a human, developing algorithms to replicate this human ability is a difficult task.
Published in Chapter: Attempting to Model Sense Division for Word Sense Disambiguation; From: Handbook of Research on Social Dimensions of Semantic Technologies and Web Services
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