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Reseach Article

Sentiment Analysis for Visuals using Natural Language Processing

by Hari Iyer, Mihir Gandhi, Sindhu Nair
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 128 - Number 6
Year of Publication: 2015
Authors: Hari Iyer, Mihir Gandhi, Sindhu Nair
10.5120/ijca2015906581

Hari Iyer, Mihir Gandhi, Sindhu Nair . Sentiment Analysis for Visuals using Natural Language Processing. International Journal of Computer Applications. 128, 6 ( October 2015), 31-35. DOI=10.5120/ijca2015906581

@article{ 10.5120/ijca2015906581,
author = { Hari Iyer, Mihir Gandhi, Sindhu Nair },
title = { Sentiment Analysis for Visuals using Natural Language Processing },
journal = { International Journal of Computer Applications },
issue_date = { October 2015 },
volume = { 128 },
number = { 6 },
month = { October },
year = { 2015 },
issn = { 0975-8887 },
pages = { 31-35 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume128/number6/22879-2015906581/ },
doi = { 10.5120/ijca2015906581 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:20:42.983988+05:30
%A Hari Iyer
%A Mihir Gandhi
%A Sindhu Nair
%T Sentiment Analysis for Visuals using Natural Language Processing
%J International Journal of Computer Applications
%@ 0975-8887
%V 128
%N 6
%P 31-35
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, the aim is to build a hybrid Word Sense Disambiguation(WSD) technique, which is acutely focused on text associated with a certain form of visual. Natural language processing helps establish a context among the data elements that are aggregated to establish a certain meaning. Analyzing transcripts of visuals being uploaded in real-time saves resources and time required to sort content based on genres or emotions. The training data lays a foundation to rate the polarities of elements, on top of which the dictionary expands as an when new content is supplied to the apparatus. Third-party intelligence is combined with the dictionary to experience growth even when the consumer usage is idle. All these entities are mutually intertwined to ensure maximum utility and output.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Natural Language Processing Third-party intelligence Training Data Polarity Word Sense Disambiguation.