Abstract：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.
董坤. 基于协同过滤算法的高校图书馆图书推荐系统研究[J]. 现代图书情报技术, 2011, (11): 44-47.
Dong Kun. Research of Personalized Book Recommender System of University Library Based on Collaborative Filter. New Technology of Library and Information Service, DOI：10.11925/infotech.1003-3513.2011.11.07.
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