基于大模型的高校圖書館個性化資源推薦系統(tǒng)構(gòu)建與實踐研究

打開文本圖片集

Research on the Construction and Practice of University Library Personalized Resource Recommendation System Based on Large Models

NiuYue，Hao Baoquan， Zhao Zhiyan

AbstractIn the digitalage，universitylibraries are facing new challenges.The personalized resource recommendation system can acurately push information based onuser interests，habits，and needs，improving resourceutilization and experience.This paper proposes a recommendation system architecture based on large models，covering user profiling， resource indexing，and intelligentrecommendation.Thesystemutilizes temporalandmultimodalanalysis tocharacterize interests，and builds indexes withdeep understanding oflarge models tooptimize performance.In terms of deployment， explore cloud and localized applications，and demonstrate the effectiveness through caseanalysis.Compared to traditional methods，this system can accurately capture requirements and dynamically adjust strategies.The paper also discusses itsadvantages such as intellgenceand automation，analyzes risks such as privacy securityand content reliability，and looks forward tothedevelopmenttrendofpersonalizedrecommendationsystems insmart libraries， providing reference forthe application of artificial intelligence in the field of knowledge services.

KeywordsSmartlibray.Pesonalizedresourcerecommendation.Largelanguagemodel.Userprofiling.Resourcesemanticindexing

0 引言

在數(shù)字化和信息爆炸的時代，高校圖書館的職能已從傳統(tǒng)的文獻存儲與借閱服務(wù)拓展為知識傳播、學(xué)術(shù)研究支持及學(xué)習(xí)資源整合的智能化服務(wù)。（剩余11304字）