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Product recommendation using deep learning in computer vision

Recently, recommendation models have gained popularity due to their effectiveness in improving customer satisfaction and deriving sales. However, current product recommendation models have a drawback: they lack personalized and targeted advertisements for individual users. Consequently, the recommen...

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Main Authors:	Mogan, Sharvinteraan Carberry, Zuriani, Mustaffa, Mohd Herwan, Sulaiman, Ernawan, Ferda
Format:	Conference or Workshop Item
Language:	English English
Published:	Institute of Electrical and Electronics Engineers Inc. 2023
Subjects:	QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General)
Online Access:	http://umpir.ump.edu.my/id/eprint/40341/1/Product%20recommendation%20using%20deep%20learning%20in%20computer%20vision.pdf http://umpir.ump.edu.my/id/eprint/40341/2/Product%20recommendation%20using%20deep%20learning%20in%20computer%20vision_ABS.pdf http://umpir.ump.edu.my/id/eprint/40341/ https://doi.org/10.1109/ICSECS58457.2023.10256332
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spelling	my.ump.umpir.403412024-04-16T04:12:33Z http://umpir.ump.edu.my/id/eprint/40341/ Product recommendation using deep learning in computer vision Mogan, Sharvinteraan Carberry Zuriani, Mustaffa Mohd Herwan, Sulaiman Ernawan, Ferda QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General) Recently, recommendation models have gained popularity due to their effectiveness in improving customer satisfaction and deriving sales. However, current product recommendation models have a drawback: they lack personalized and targeted advertisements for individual users. Consequently, the recommendations provided are random and not tailored to users' preferences. This limitation negatively impacts the system's ability to deliver relevant and personalized advertisements, leading to reduced user engagement and potentially lower conversion rates. Moreover, the absence of personalized advertisements can result in user dissatisfaction as they may receive recommendations that are irrelevant or not aligned with their interests and needs. To address these challenges, this study proposed a targeted product recommendation model using Deep Learning (DL) techniques in computer vision. The study utilizes the dataset of human images obtained from the Kaggle website, which includes details such as gender, class, and age. Findings of the study demonstrated a high level of accuracy in product recommendations, indicating the potential for significant improvements in addressing the issues. In conclusion, the proposed method achieves good accuracy in predicting the gender and age, and provides appropriate product recommendations based on these features. Institute of Electrical and Electronics Engineers Inc. 2023 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/40341/1/Product%20recommendation%20using%20deep%20learning%20in%20computer%20vision.pdf pdf en http://umpir.ump.edu.my/id/eprint/40341/2/Product%20recommendation%20using%20deep%20learning%20in%20computer%20vision_ABS.pdf Mogan, Sharvinteraan Carberry and Zuriani, Mustaffa and Mohd Herwan, Sulaiman and Ernawan, Ferda (2023) Product recommendation using deep learning in computer vision. In: 8th International Conference on Software Engineering and Computer Systems, ICSECS 2023 , 25-27 August 2023 , Penang. pp. 263-267. (192961). ISBN 979-835031093-1 https://doi.org/10.1109/ICSECS58457.2023.10256332
institution	Universiti Malaysia Pahang Al-Sultan Abdullah
building	UMPSA Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaysia Pahang Al-Sultan Abdullah
content_source	UMPSA Institutional Repository
url_provider	http://umpir.ump.edu.my/
language	English English
topic	QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General)
spellingShingle	QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General) Mogan, Sharvinteraan Carberry Zuriani, Mustaffa Mohd Herwan, Sulaiman Ernawan, Ferda Product recommendation using deep learning in computer vision
description	Recently, recommendation models have gained popularity due to their effectiveness in improving customer satisfaction and deriving sales. However, current product recommendation models have a drawback: they lack personalized and targeted advertisements for individual users. Consequently, the recommendations provided are random and not tailored to users' preferences. This limitation negatively impacts the system's ability to deliver relevant and personalized advertisements, leading to reduced user engagement and potentially lower conversion rates. Moreover, the absence of personalized advertisements can result in user dissatisfaction as they may receive recommendations that are irrelevant or not aligned with their interests and needs. To address these challenges, this study proposed a targeted product recommendation model using Deep Learning (DL) techniques in computer vision. The study utilizes the dataset of human images obtained from the Kaggle website, which includes details such as gender, class, and age. Findings of the study demonstrated a high level of accuracy in product recommendations, indicating the potential for significant improvements in addressing the issues. In conclusion, the proposed method achieves good accuracy in predicting the gender and age, and provides appropriate product recommendations based on these features.
format	Conference or Workshop Item
author	Mogan, Sharvinteraan Carberry Zuriani, Mustaffa Mohd Herwan, Sulaiman Ernawan, Ferda
author_facet	Mogan, Sharvinteraan Carberry Zuriani, Mustaffa Mohd Herwan, Sulaiman Ernawan, Ferda
author_sort	Mogan, Sharvinteraan Carberry
title	Product recommendation using deep learning in computer vision
title_short	Product recommendation using deep learning in computer vision
title_full	Product recommendation using deep learning in computer vision
title_fullStr	Product recommendation using deep learning in computer vision
title_full_unstemmed	Product recommendation using deep learning in computer vision
title_sort	product recommendation using deep learning in computer vision
publisher	Institute of Electrical and Electronics Engineers Inc.
publishDate	2023
url	http://umpir.ump.edu.my/id/eprint/40341/1/Product%20recommendation%20using%20deep%20learning%20in%20computer%20vision.pdf http://umpir.ump.edu.my/id/eprint/40341/2/Product%20recommendation%20using%20deep%20learning%20in%20computer%20vision_ABS.pdf http://umpir.ump.edu.my/id/eprint/40341/ https://doi.org/10.1109/ICSECS58457.2023.10256332
_version_	1822924223524372480
score	13.232414

Product recommendation using deep learning in computer vision

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