Book recommendation system has been developed rapidly due to the Web technology and library modernization, which provide a new way for the librarians to acquire the readers’ demands. However, existing recommendation systems can’t supply enough information for readers to decide whether to recommend a book or not, and they don’t analyze the recommendation information. Some systems also lack of a feedback mechanism for readers, which would hurt their enthusiasm. In order to solve these problems, we designed a novel book recommendation system. Readers will be redirected to the recommendation pages when they can’t find the required book through the library bibliographic retrieval system. The recommendation pages contain all the essential and expanding book information for readers to refer to. Readers can recommend a book on these pages, and the recommendation data will be analyzed by the recommendation system to make scientific purchasing decision. We proposed two formulas to compute the book value and copy number respectively based on the recommendation data. The application of the recommendation system shows that both the recommended book utilization and readers’ satisfaction were greatly increased.
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