Application of WordNet for Text Analysis in Different Domains
Suyash Lakhani1, Ridhi Jhamb2, Mayank Arora3, Saravanakumar Kandasamy4
1Suyash Lakhani*, Student of VIT,Vellore, persuing B-tech, CSE department III year, Tamil Nadu.
2Ridhi Jhamb, Student of VIT,Vellore, persuing B-tech, CSE Department III year, Tamil Nadu.
3Mayank Arora, Student VIT,Vellore, persuing B-tech, CSE department III year, Tamil Nadu.
4Saravanakumar kandasamy, Teacher at VIT,Vellore, Department B-tech, CSE, Tamil Nadu.
Manuscript received on May 30, 2020. | Revised Manuscript received on June 08, 2020. | Manuscript published on June 30, 2020. | PP: 774-786 | Volume-9 Issue-5, June 2020. | Retrieval Number: E9824069520/2020©BEIESP | DOI: 10.35940/ijeat.E9824.069520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The following paper examines and illustrates various problems which occur in the field of Natural Language Processing. The solutions used in these papers use WordNet in one way or the other to enhance or improve the efficiency of the projects.WordNet can therefore be viewed as a combination and an augmentation of a word reference and a thesaurus. While it can be used by developers and programmers via a web browser, its prime use is in automatic text analysis and applications based on AI.
Keywords: Cosine sentence similarity, semantic significance, superposition effect, structural dependencies, Semantic relatedness, Ontology, Word gloss, Essence Comparison, Human similarity