[Objective] Service recommendation of the content of traditional digital literature resources is unable to fully exploit the user potential information demand and the ratings matrixes are always sparse. This paper provides an algorithm using collaborative filtering algorithm and association semantic link. [Methods] A recommendation algorithm for the content of digital literature resources is proposed by using the association semantic link and collaborative filtering algorithm. [Results] The experimental result shows that the algorithm can overcome the problems of the potential information needs of the users and the sparsity of the matrix. [Limitations] Lack of large-scale collection of digital resources, and the experimental cases are few. [Conclusions] The algorithm can fully exploit the users' information demand and generate the literature recommendation information. Finally, the validity and practicability of the proposed algorithm are verified by experiments.
毕强, 刘健. 数字文献资源内容服务推荐方法研究[J]. 现代图书情报技术, 2015, 31(12): 21-27.
Bi Qiang, Liu Jian. Research on the Service Recommendation of the Content of Digital Literature Resources. New Technology of Library and Information Service, DOI：10.11925/infotech.1003-3513.2015.12.04.
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