自助图书馆用户画像研究

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ResearchonUserProfilingforSelf-serviceLibraries

WangWenpeng，Han Qingxia

AbstractThis paper applies user profiling technology to self-service library services to enhance the effective alignment betweenuserdemandsand book resources.Initially，basedonthe borrowing dataof self-service libraryusers， the K-means clustering algorithm is utilized to segment the user population，identifying groups with varying borrowing preferences.Subsequently，from theresultsof theclustering analysis，four representative user borrowing preferences are derived，and a rapid user profiling model suitable for new scenarios is constructed.Furthermore，customized recommendationschemes basedon interest preferencesand complementarityare developed fordiferent user groups，and the adaptabilityof these schemes is analyzed through user satisfaction surveys. Finaly，specific measures foroptimizing self-service library services are proposed.The findings demonstrate that constructing arapid user profiling model by analyzing user borrowing preferences and providing recommendation schemes that combine interest preferences and complementarity，can significantly improve user satisfaction with self-service library services.

KeywordsSelf-service library. User profile.Personalized recommendation. K-means clustering.

0 引言

在数字化浪潮的推动下，自助图书馆作为城市阅读创新服务体系的重要组成部分，正逐渐成为知识获取与文化传播的新平台]。（剩余13688字）