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Exploration of consumer preference based on deep learning neural network model in the immersive marketing environment
The study intends to increase the marketing quantity of various commodities and promote the comprehensive development of the market. The study first discusses the principle and current situation of the emerging Immersive Marketing. Then, it analyzes the Deep Learning (DL) Neural Network (NN) model....
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9067676/ https://www.ncbi.nlm.nih.gov/pubmed/35507570 http://dx.doi.org/10.1371/journal.pone.0268007 |
_version_ | 1784700057054871552 |
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author | Zheng, Qiang Ding, Qingshan |
author_facet | Zheng, Qiang Ding, Qingshan |
author_sort | Zheng, Qiang |
collection | PubMed |
description | The study intends to increase the marketing quantity of various commodities and promote the comprehensive development of the market. The study first discusses the principle and current situation of the emerging Immersive Marketing. Then, it analyzes the Deep Learning (DL) Neural Network (NN) model. Finally, a Personalized Recommendation System (PRS) is designed based on the Immersive Marketing environment using the Graph Neural Network (GNN) model. The proposed PRS based on the Immersive Graph Neural Network (IGNN) model has reflected higher advantages over other recommendation systems. The experiment results suggest that Immersive Marketing can fully reflect commodities’ essential attributes and characteristics, improve users’ shopping experience, and promote sales. Meanwhile, the IGNN-based PRS reported here gives users an elevated and immersive shopping experience and entertainment process. Lastly, the model comparison finds that the proposed IGNN outperforms other models. The optimal model parameters are verified as P@20 and R@20 to gain the highest composite index values. In particular, parameter R@20 gives the model a better performance over P@20. The study provides technical references for improving the marketing process of various commodities and entertainment products and contributes to marketing technology development. |
format | Online Article Text |
id | pubmed-9067676 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-90676762022-05-05 Exploration of consumer preference based on deep learning neural network model in the immersive marketing environment Zheng, Qiang Ding, Qingshan PLoS One Research Article The study intends to increase the marketing quantity of various commodities and promote the comprehensive development of the market. The study first discusses the principle and current situation of the emerging Immersive Marketing. Then, it analyzes the Deep Learning (DL) Neural Network (NN) model. Finally, a Personalized Recommendation System (PRS) is designed based on the Immersive Marketing environment using the Graph Neural Network (GNN) model. The proposed PRS based on the Immersive Graph Neural Network (IGNN) model has reflected higher advantages over other recommendation systems. The experiment results suggest that Immersive Marketing can fully reflect commodities’ essential attributes and characteristics, improve users’ shopping experience, and promote sales. Meanwhile, the IGNN-based PRS reported here gives users an elevated and immersive shopping experience and entertainment process. Lastly, the model comparison finds that the proposed IGNN outperforms other models. The optimal model parameters are verified as P@20 and R@20 to gain the highest composite index values. In particular, parameter R@20 gives the model a better performance over P@20. The study provides technical references for improving the marketing process of various commodities and entertainment products and contributes to marketing technology development. Public Library of Science 2022-05-04 /pmc/articles/PMC9067676/ /pubmed/35507570 http://dx.doi.org/10.1371/journal.pone.0268007 Text en © 2022 Zheng, Ding https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Zheng, Qiang Ding, Qingshan Exploration of consumer preference based on deep learning neural network model in the immersive marketing environment |
title | Exploration of consumer preference based on deep learning neural network model in the immersive marketing environment |
title_full | Exploration of consumer preference based on deep learning neural network model in the immersive marketing environment |
title_fullStr | Exploration of consumer preference based on deep learning neural network model in the immersive marketing environment |
title_full_unstemmed | Exploration of consumer preference based on deep learning neural network model in the immersive marketing environment |
title_short | Exploration of consumer preference based on deep learning neural network model in the immersive marketing environment |
title_sort | exploration of consumer preference based on deep learning neural network model in the immersive marketing environment |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9067676/ https://www.ncbi.nlm.nih.gov/pubmed/35507570 http://dx.doi.org/10.1371/journal.pone.0268007 |
work_keys_str_mv | AT zhengqiang explorationofconsumerpreferencebasedondeeplearningneuralnetworkmodelintheimmersivemarketingenvironment AT dingqingshan explorationofconsumerpreferencebasedondeeplearningneuralnetworkmodelintheimmersivemarketingenvironment |