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

Moahmmed Ayub, Mohammad Zulkarnain (2024) Emotion classification based on text using Convolutional Neural Network / Mohammad Zulkarnain Moahmmed Ayub. Degree thesis, Universiti Teknologi MARA, Terengganu.

Abstract

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.

Metadata

Item Type: Thesis (Degree)
Creators:
Creators
Email / ID Num.
Moahmmed Ayub, Mohammad Zulkarnain
2022953965
Contributors:
Contribution
Name
Email / ID Num.
Thesis advisor
Tan, Gloria Jennis
UNSPECIFIED
Subjects: Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science > Neural networks (Computer science)
Divisions: Universiti Teknologi MARA, Terengganu > Kuala Terengganu Campus
Programme: Bachelor of Computer Science (Hons)
Keywords: Natural Language Processing, Convolutional Neural Network, AI Applications
Date: 2024
URI: https://ir.uitm.edu.my/id/eprint/96322
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