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Intelligent Optimization Method of Resource Recommendation Service of Mobile Library Based on Digital Twin Technology
In order to improve the Resource Recommendation and sharing ability of mobile library, an intelligent optimization model of Mobile Library Resource Recommendation Service Based on digital twin technology is proposed. Build the association rule feature distribution set of mobile library resource reco...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9440791/ https://www.ncbi.nlm.nih.gov/pubmed/36065374 http://dx.doi.org/10.1155/2022/3582719 |
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author | Shang, Shanshan Yu, Zikai Geng, Aili Xu, Xiuxiu Ma, Huizhen Wang, Guozhong |
author_facet | Shang, Shanshan Yu, Zikai Geng, Aili Xu, Xiuxiu Ma, Huizhen Wang, Guozhong |
author_sort | Shang, Shanshan |
collection | PubMed |
description | In order to improve the Resource Recommendation and sharing ability of mobile library, an intelligent optimization model of Mobile Library Resource Recommendation Service Based on digital twin technology is proposed. Build the association rule feature distribution set of mobile library resource recommendation service, carry out text information retrieval in the process of Mobile Library Resource Recommendation and sharing, carry out semantic correlation feature registration according to the retrieval preference of mobile library reading user object, establish the association rule data set of mobile library reading user object preference for mobile library Resource Recommendation and sharing, carry out feature block processing, and analyze the library reader preference. Complete the collaborative filtering recommendation of Mobile Library Resource Recommendation sharing. The simulation results show that the collaborative recommendation under the intelligent optimization mode of mobile library resource recommendation service using this method has high accuracy and good confidence level, which improves the intelligent level of Mobile Library Resource Recommendation and user satisfaction. |
format | Online Article Text |
id | pubmed-9440791 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-94407912022-09-04 Intelligent Optimization Method of Resource Recommendation Service of Mobile Library Based on Digital Twin Technology Shang, Shanshan Yu, Zikai Geng, Aili Xu, Xiuxiu Ma, Huizhen Wang, Guozhong Comput Intell Neurosci Research Article In order to improve the Resource Recommendation and sharing ability of mobile library, an intelligent optimization model of Mobile Library Resource Recommendation Service Based on digital twin technology is proposed. Build the association rule feature distribution set of mobile library resource recommendation service, carry out text information retrieval in the process of Mobile Library Resource Recommendation and sharing, carry out semantic correlation feature registration according to the retrieval preference of mobile library reading user object, establish the association rule data set of mobile library reading user object preference for mobile library Resource Recommendation and sharing, carry out feature block processing, and analyze the library reader preference. Complete the collaborative filtering recommendation of Mobile Library Resource Recommendation sharing. The simulation results show that the collaborative recommendation under the intelligent optimization mode of mobile library resource recommendation service using this method has high accuracy and good confidence level, which improves the intelligent level of Mobile Library Resource Recommendation and user satisfaction. Hindawi 2022-08-27 /pmc/articles/PMC9440791/ /pubmed/36065374 http://dx.doi.org/10.1155/2022/3582719 Text en Copyright © 2022 Shanshan Shang et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Shang, Shanshan Yu, Zikai Geng, Aili Xu, Xiuxiu Ma, Huizhen Wang, Guozhong Intelligent Optimization Method of Resource Recommendation Service of Mobile Library Based on Digital Twin Technology |
title | Intelligent Optimization Method of Resource Recommendation Service of Mobile Library Based on Digital Twin Technology |
title_full | Intelligent Optimization Method of Resource Recommendation Service of Mobile Library Based on Digital Twin Technology |
title_fullStr | Intelligent Optimization Method of Resource Recommendation Service of Mobile Library Based on Digital Twin Technology |
title_full_unstemmed | Intelligent Optimization Method of Resource Recommendation Service of Mobile Library Based on Digital Twin Technology |
title_short | Intelligent Optimization Method of Resource Recommendation Service of Mobile Library Based on Digital Twin Technology |
title_sort | intelligent optimization method of resource recommendation service of mobile library based on digital twin technology |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9440791/ https://www.ncbi.nlm.nih.gov/pubmed/36065374 http://dx.doi.org/10.1155/2022/3582719 |
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