Emotion classification based on text using Convolutional Neural Network / Mohammad Zulkarnain Moahmmed Ayub

This project not only contributes to the evolving landscape of natural language processing but also highlights the significance of leveraging advanced technologies, such as CNN, for emotion analysis. The findings of this research provide valuable insights into the potential of AI-driven models in un...

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Main Author:	Moahmmed Ayub, Mohammad Zulkarnain
Format:	Thesis
Language:	English
Published:	2024
Subjects:	Neural networks (Computer science)
Online Access:	https://ir.uitm.edu.my/id/eprint/96322/1/96322.pdf
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id	my-uitm-ir.96322
record_format	uketd_dc
spelling	my-uitm-ir.963222024-06-04T07:20:34Z Emotion classification based on text using Convolutional Neural Network / Mohammad Zulkarnain Moahmmed Ayub 2024 Moahmmed Ayub, Mohammad Zulkarnain Neural networks (Computer science) This project not only contributes to the evolving landscape of natural language processing but also highlights the significance of leveraging advanced technologies, such as CNN, for emotion analysis. The findings of this research provide valuable insights into the potential of AI-driven models in understanding and categorizing emotions, paving the way for future advancements in sentiment analysis and emotion recognition. The endeavor emphasizes the critical role of responsible AI applications, especially in deciphering the intricate nuances of human emotions through textual data. 2024 Thesis https://ir.uitm.edu.my/id/eprint/96322/ https://ir.uitm.edu.my/id/eprint/96322/1/96322.pdf text en public degree Universiti Teknologi MARA, Terengganu College of Computing, Informatics and Media Tan, Gloria Jennis
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Tan, Gloria Jennis
topic	Neural networks (Computer science)
spellingShingle	Neural networks (Computer science) Moahmmed Ayub, Mohammad Zulkarnain Emotion classification based on text using Convolutional Neural Network / Mohammad Zulkarnain Moahmmed Ayub
description	This project not only contributes to the evolving landscape of natural language processing but also highlights the significance of leveraging advanced technologies, such as CNN, for emotion analysis. The findings of this research provide valuable insights into the potential of AI-driven models in understanding and categorizing emotions, paving the way for future advancements in sentiment analysis and emotion recognition. The endeavor emphasizes the critical role of responsible AI applications, especially in deciphering the intricate nuances of human emotions through textual data.
format	Thesis
qualification_level	Bachelor degree
author	Moahmmed Ayub, Mohammad Zulkarnain
author_facet	Moahmmed Ayub, Mohammad Zulkarnain
author_sort	Moahmmed Ayub, Mohammad Zulkarnain
title	Emotion classification based on text using Convolutional Neural Network / Mohammad Zulkarnain Moahmmed Ayub
title_short	Emotion classification based on text using Convolutional Neural Network / Mohammad Zulkarnain Moahmmed Ayub
title_full	Emotion classification based on text using Convolutional Neural Network / Mohammad Zulkarnain Moahmmed Ayub
title_fullStr	Emotion classification based on text using Convolutional Neural Network / Mohammad Zulkarnain Moahmmed Ayub
title_full_unstemmed	Emotion classification based on text using Convolutional Neural Network / Mohammad Zulkarnain Moahmmed Ayub
title_sort	emotion classification based on text using convolutional neural network / mohammad zulkarnain moahmmed ayub
granting_institution	Universiti Teknologi MARA, Terengganu
granting_department	College of Computing, Informatics and Media
publishDate	2024
url	https://ir.uitm.edu.my/id/eprint/96322/1/96322.pdf
_version_	1804889985251278848

Emotion classification based on text using Convolutional Neural Network / Mohammad Zulkarnain Moahmmed Ayub

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