The Design and Implementation of the Bibliographic Recommendation System Based on Maximal Frequent Patterns Mining Algorithm
基于最大频繁模式挖掘算法进行书目推荐系统的设计与实现

On the foundation of the Unicorn system in Nankai University Library, this paper introduces the design and implementation of bibliographic recommendation system based on maximal frequent patterns mining algorithm. It describes the process of analyzing the readers’ behavior patterns by fully utilizing the accumulation data collected in the Unicorn system in details, so as to offer personalized bibliographic recommendation service. By using this system, the academic library can effectively expand different service patterns to readers on available sources, and improve the efficiency of the existing automated circulation system.