Position: Home > Articles > 高校新读者图书个性化推荐服务研究
Journal of Library and Information Science in Agriculture
2019
(5)
50-60
高校新读者图书个性化推荐服务研究
作 者：
王圣镔
单 位：
北华大学
关键词：
新读者;个性化推荐;用户冷启动;数据稀疏;聚类
摘 要：
[目的 /意义]针对阻碍高校智慧图书馆对新读者进行图书个性化推荐的用户冷启动问题,提出一种面向新读者的高校图书馆个性化推荐方法,为智慧型高校图书馆开展图书个性化推荐服务、提高新读者借阅率提供切实可行的方案.[方法 /过程]以北华大学图书馆借阅流通大数据进行数据挖掘,得出属性相似的新读者和已有读者具有相似借阅偏好的结论.然后,通过奇异值分解解决数据稀疏问题,采用基于欧氏距离的蚁群算法对新读者与已有读者聚类,搭建了新读者和已有读者之间关系的桥梁.最后将已有读者借阅的图书采取Top-N算法对新读者推荐.[结果 /结论]以2017级读者为实验对象,选取了3个学院的44名读者,用所提出的算法进行了实验检验.实验结果表明新算法推荐效果显著,操作简单可行,为后续个性化推荐工作奠定了基础.
作 者：
WANG Shengbin;Beihua University;
关键词：
new readers;;personalized recommendation;;user cold start;;data sparsity;;clustering
摘 要：
[Purpose/Significance]Aimed at the user cold start problem that prevent the university smart library from accurately recommending books to new readers, a personalized recommendation method for new college readers is proposed to provide practical solutions for carrying out personalized recommendation service and increasing new readers' borrowing rate.[Method/Process]Through data mining on borrowing circulating big data in Beihua university library, the conclusion is reached that new readers and existing readers with similar attributes have similar borrowing and reading preferences; Then, the singular value decomposition is used to solve the data sparse problem and the Euclidean distance and ant colony algorithm are used to cluster the new readers and existing readers, which building a bridge between new readers and existing readers. Finally, the Top-N algorithm is adopted to recommend the books borrowed by existing readers to new readers. [Result/Conclusion]Take the readers from grade 2017 as experiment subject, the proposed algorithm was tested on 44 readers from three academies. The results show that the proposed algorithm is effective and easy to operate, which lays a foundation for the subsequent personalized recommendation work.
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