基于协同过滤算法的高校图书馆图书推荐系统研究

Research of Personalized Book Recommender System of University Library Based on Collaborative Filter

针对当前高校图书馆主动式图书推荐服务存在的对服务对象信息需求挖掘、分析不足的问题,提出构建基于协同过滤算法的个性化图书推荐系统。通过引入读者专业、角色、学历、借阅记录等影响和反映读者信息需求的因素构建读者特征模型,基于该模型采用优化的协同过滤算法挖掘读者信息需求并产生个性化图书推荐信息,并通过实验证明该方法的有效性和实用性。

Aiming at the disadvantages of insufficient mining and analysis of readers＇ information needs existing in the active book recommendation service of university library, the paper brings forward a construction of personalized book recommender system based on collaborative filter. The system imports the factors of faculty, role, education and the readers＇ records of visiting the reading rooms to construct the reader＇ s characteristic model. By mining and analyzing the characteristic model which uses optimized collaboration filter algorithm, the system can produce the personalized book recommendation to reader. And the experiment proves that the system is efficient and practical.