Collaborative filtering recommendation systems in digital library have faced the problem of sparse user ratings. To solve the problem, a computing method of group interest trend degree has been proposed and used into the prediction of vacant values in user-item matrix. The experimental results show that the algorithm can efficiently improve recommendation quality.
马丽. 基于群体兴趣偏向度的数字图书馆协同过滤技术研究*[J]. 现代图书情报技术, 2007, 2(10): 19-22.
Ma Li. Study on Digital Library Collaborative Filtering Technology Based on Group Interest Trend Degree. New Technology of Library and Information Service, 2007, 2(10): 19-22.
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