Hybrid recommendation system of intelligent captioning using deep learning networks

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.

Bibliografski detalji
Glavni autori:	Wasi, Ahamed Al, Fahim, Ezazul Haque, Inova, Nishat Tasnim, Fahim, Abdullah Al, Preeti, Taghrid Tahani
Daljnji autori:	Mostakim, Moin
Format:	Disertacija
Jezik:	English
Izdano:	Brac University 2024
Teme:	CNN Embedding LSTM BiLSTM Vectorization Tokenization BERT Neural networks (Computer science) Deep learning (Machine learning)
Online pristup:	http://hdl.handle.net/10361/22878

id	10361-22878
record_format	dspace
spelling	10361-228782024-05-20T21:02:37Z Hybrid recommendation system of intelligent captioning using deep learning networks Wasi, Ahamed Al Fahim, Ezazul Haque Inova, Nishat Tasnim Fahim, Abdullah Al Preeti, Taghrid Tahani Mostakim, Moin Department of Computer Science and Engineering, Brac University CNN Embedding LSTM BiLSTM Vectorization Tokenization BERT Neural networks (Computer science) Deep learning (Machine learning) This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024. Cataloged from PDF version of thesis. Includes bibliographical references (pages 53-54). This research introduces a hybrid recommendation system through sentiment analysis for Bangla long textual sentences. Social media, as a vast source of opinions, can be harnessed through sentiment analysis using deep learning techniques, overcoming language barriers and improving recommendation systems. The paper addresses challenges in Bangla sentiment analysis, such as the scarcity of datasets and linguistic nuances, proposing a model that combines LSTM, Bi-LSTM, and CNN for optimized text sequence classification. The study explores six neural network models (ANN, CNN, LSTM,Bi-LSTM,BERT,RCNN) overcoming obstacles in dataset quality and distribution. Challenges in data collection, model selection, and computational resources are discussed. The paper concludes with the acknowledgment of the evolving frontier of sentiment analysis in Bangla text, emphasizing the transformative potential with continued efforts to expand datasets and refine algorithms. Ahamed Al Wasi Ezazul Haque Fahim Nishat Tasnim Inova Abdullah Al Fahim Taghrid Tahani Preeti B.Sc in Computer Science 2024-05-20T03:11:56Z 2024-05-20T03:11:56Z ©2024 2024 Thesis ID: 21301745 ID: 17101266 ID: 18101112 ID: 19101567 ID: 19301189 http://hdl.handle.net/10361/22878 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 66 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	CNN Embedding LSTM BiLSTM Vectorization Tokenization BERT Neural networks (Computer science) Deep learning (Machine learning)
spellingShingle	CNN Embedding LSTM BiLSTM Vectorization Tokenization BERT Neural networks (Computer science) Deep learning (Machine learning) Wasi, Ahamed Al Fahim, Ezazul Haque Inova, Nishat Tasnim Fahim, Abdullah Al Preeti, Taghrid Tahani Hybrid recommendation system of intelligent captioning using deep learning networks
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.
author2	Mostakim, Moin
author_facet	Mostakim, Moin Wasi, Ahamed Al Fahim, Ezazul Haque Inova, Nishat Tasnim Fahim, Abdullah Al Preeti, Taghrid Tahani
format	Thesis
author	Wasi, Ahamed Al Fahim, Ezazul Haque Inova, Nishat Tasnim Fahim, Abdullah Al Preeti, Taghrid Tahani
author_sort	Wasi, Ahamed Al
title	Hybrid recommendation system of intelligent captioning using deep learning networks
title_short	Hybrid recommendation system of intelligent captioning using deep learning networks
title_full	Hybrid recommendation system of intelligent captioning using deep learning networks
title_fullStr	Hybrid recommendation system of intelligent captioning using deep learning networks
title_full_unstemmed	Hybrid recommendation system of intelligent captioning using deep learning networks
title_sort	hybrid recommendation system of intelligent captioning using deep learning networks
publisher	Brac University
publishDate	2024
url	http://hdl.handle.net/10361/22878
work_keys_str_mv	AT wasiahamedal hybridrecommendationsystemofintelligentcaptioningusingdeeplearningnetworks AT fahimezazulhaque hybridrecommendationsystemofintelligentcaptioningusingdeeplearningnetworks AT inovanishattasnim hybridrecommendationsystemofintelligentcaptioningusingdeeplearningnetworks AT fahimabdullahal hybridrecommendationsystemofintelligentcaptioningusingdeeplearningnetworks AT preetitaghridtahani hybridrecommendationsystemofintelligentcaptioningusingdeeplearningnetworks
_version_	1814308499598868480

Hybrid recommendation system of intelligent captioning using deep learning networks

Similar Items