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...

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Bibliographic Details
Published in:Computational intelligence and neuroscience 2022-08, Vol.2022, p.1-10
Main Authors: Shang, Shanshan, Yu, Zikai, Geng, Aili, Xu, Xiuxiu, Ma, Huizhen, Wang, Guozhong
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Approximation
Collaboration
Collection management
Communications industry
Confidence intervals
Data mining
Data transmission
Digital twins
Digitization
Information processing
Information retrieval
Information storage and retrieval
Language
Libraries
Library resources
Mobile libraries
Optimization
Optimization models
Preferences
Public libraries
Recommender systems
Simulation
Telecommunications services industry
User satisfaction
User services
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Summary: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.
ISSN:1687-5265
1687-5273
DOI:10.1155/2022/3582719