基于知识图谱和读者特征的图书馆智能检索与推送研究

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分类号 G250.76  DOI10.16810/j.cnki.1672-514X.2025.06.008

Research on Library Intelligent Retrieval and Push Based on Knowledge Graph and Reader Characteristics

Liu Piaopiao， Chen Chen

AbstractTraditionalibraryretrievalsystemsoftenrelyonkeywordmatching，struggling tocaptureusers’deep-seatedneds， resulting inloweficiencyandpooruserexperience.Thisstudyanalyzesuserscenariorequirements inlibraryretrevalservices， designs theoverallframeworkandcoremodules，and integrates multi-dimensionalreadercharacteristics withknowledgegraph technology.Bycombining usersearch intent withtheknowledge graph，thesystemunderstandsand identifiesuserintentionsto deliverpersonalizedrecommendations.Theproposedmethodaccuratelyparsesretrievalintentions，achieves intellgentresource filtering and dynamicrecommendations，demonstratingsuperiorperformanceinresource discovery，result presentation，and user-centricrecommendationscomparedtotraditional services.Experimentalresultsshowsignficantimprovements inrecall rate，responsespeed，andusersatisfaction，providinganeectiveapproach for transforming libraryknowledgesrices.

KeywordsKnowledge graph.Readercharacteristics.Intelligentretrieval. Recommendersystems.Natural languageprocesing.

0 引言

随着互联网技术的飞速发展和数字资源的日益丰富，图书馆不仅需要存储海量的信息资源，更需要提供一种高效、精准的方式来帮助读者从中筛选出有价值的信息。（剩余9622字）