Research on architecture design and core strategy of intelligent recommendation system for electronic literature resources in colleges and universities
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Research on architecture design and core strategy of intelligent recommendation system for electronic literature resources in colleges and universities
Journal on CommunicationsVol. 45, Issue Z2, Pages: 160-167(2024)
作者机构:
西北农林科技大学网络与教育技术中心,陕西 咸阳 712100
作者简介:
基金信息:
Shaanxi Province Natural Science Basic Research Program(2023-JC-YB-489)
HU Guoqiang.Research on architecture design and core strategy of intelligent recommendation system for electronic literature resources in colleges and universities[J].Journal on Communications,2024,45(Z2):160-167.
HU Guoqiang.Research on architecture design and core strategy of intelligent recommendation system for electronic literature resources in colleges and universities[J].Journal on Communications,2024,45(Z2):160-167. DOI: 10.11959/j.issn.1000-436x.2024240.
Research on architecture design and core strategy of intelligent recommendation system for electronic literature resources in colleges and universities
In order to facilitate teachers and students to quickly locate the required literature resources in the massive electronic literature
improve the efficiency of electronic literature resource utilization
and achieve personalized and accurate literature recommendation services
a university electronic literature resource intelligent recommendation system was designed. Firstly the problems existing in the implementation of the intelligent recommendation system for university electronic literature were analyzed using the literature method. On these problems
a university electronic literature resource intelligent recommendation system was designed
which includes a data collection layer
a data mining layer
a recommendation brain layer
an application service layer
an information standardization system
and a security and operation maintenance system. Finally
the core strategies and algorithms of the system were introduced. Practical application in our university has shown that the system can recommend electronic literature resources of interest to users and provide reference for the implementation of personalized electronic literature intelligent recommendation systems in other universities.
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