JOURNAL ARTICLE

Word Sense Disambiguation by using domain knowledge

Abstract

Over the decades, lot of studies had been carried out to suggest different approaches for Word Sense Disambiguation (WSD) process. From times to times, different approaches had been suggested to define the sense of a polysemous word. In this paper, a WSD approach with the domain knowledge will be discussed. In this approach, by using Wordnet, domains of each single word will be defined and a process of defining the best domain to be assigned to that particular word will be carried out. A method of calculating the weight of each domain to its corresponding word will be discussed. According to the weight assigned to each domain, the sense of the ambiguous word will be identified.

Keywords:
WordNet Word-sense disambiguation Computer science Word (group theory) Natural language processing Domain (mathematical analysis) Artificial intelligence Process (computing) SemEval Linguistics Mathematics

Metrics

9
Cited By
2.35
FWCI (Field Weighted Citation Impact)
17
Refs
0.91
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Natural Language Processing Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Topic Modeling
Physical Sciences →  Computer Science →  Artificial Intelligence
Semantic Web and Ontologies
Physical Sciences →  Computer Science →  Artificial Intelligence

Related Documents

JOURNAL ARTICLE

Domain Adaptation using Word Embeddings for Word Sense Disambiguation

Kanako KomiyaMinoru SasakiHiroyuki ShinnouManabu Okumura

Journal:   Journal of Natural Language Processing Year: 2018 Vol: 25 (4)Pages: 463-480
JOURNAL ARTICLE

Domain Driven Word Sense Disambiguation

S Deeksha

Journal:   International Journal for Research in Applied Science and Engineering Technology Year: 2020 Vol: 8 (7)Pages: 1479-1482
BOOK-CHAPTER

Word Sense Disambiguation Using WordNet Semantic Knowledge

Ningning GaoWanli ZuoYaokang DaiWei Lv

Advances in intelligent systems and computing Year: 2014 Pages: 147-156
© 2026 ScienceGate Book Chapters — All rights reserved.