基于读者个性化特征的图书馆书目推荐Library bibliographic recommendation based on personalized features of readers
李萍,彭小华
摘要(Abstract)：
采用协同过滤的图书馆书目推荐方法存在冷启动以及矩阵稀疏等问题,新书目未被读者评分或少量评分无法被推荐,存在推荐命中率低以及个性化服务差的缺陷。因此,提出基于读者个性化特征的图书馆书目推荐方法,设计基于读者个性化特征的数字图书馆书目推荐模型,给出图书馆书目个性化推荐流程,采集读者特征并分析读者行为后,塑造读者兴趣个性化特征,通过兴趣模型向读者推荐书目,塑造基于读者个性化特征的读者兴趣模型,基于显式信息和隐式信息对读者兴趣模型实时更新,进化读者个性化特征本体模型。分析基于读者个性化特征的图书馆书目推荐过程,个性化推荐业务实现过程。实验结果表明,所提方法可实现图书馆书目的个性化推荐,推荐准确率和效率较高。
关键词(KeyWords)： 读者;个性化特征;图书馆书目;协同过滤;兴趣模型;推荐业务
基金项目(Foundation): 江西省高校人文社会科学研究项目:慕课背景下高校图书馆教学支持服务创新研究(TQ1512)~~
作者(Author): 李萍,彭小华
DOI: 10.16652/j.issn.1004-373x.2018.17.040
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