This paper proposes a weighted book recommendation algorithm for online public access catalogues(OPAC)system,by combining collaborative filtering with feature engineering.The algorithm applies collaborative filtering to cluster users with similar interests by analyzing the borrowing history.The book recommendation index is calculated by weighted algorithm after the feature code is introduced,such as the number of books borrowed,shelf time,shelving adjacency and professional rele-vance.In addition,the solutions to the problems of cold start and sparsity are proposed.The test results show that the pro-posed algorithm realizes the complete book recommendation system and the cloud visualization construction of recommended books.
关键词
联机公共目录检索/协同过滤/特征工程/图书推荐/云图
Key words
online public access catalogue/collaborative filtering/feature engineering/book recommendation/cloud visualiza-tion
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