读者借阅多维关联规则挖掘模型的建立与分析

为深入了解高校图书馆读者对文献资源的需求规律，提取了图书馆业务数据库中的读者借阅记录，将原始数据经过预处理流程获得读者借阅事务集，以Clementine 12.0为平台，建立了读者借阅多维关联规则挖掘模型。以青岛农业大学图书馆2007-2010年间读者借阅历史数据为基础，应用所建挖掘模型实例分析了读者身份、读者专业、图书类型等之间关联关系。根据获得关联规则可以深入了解读者需求，为读者提供个性化主动服务提供理论依据。

Establishment and analysis of multi-association rule mining model of reader loan

In order to probe deeply the demand rules of college library readers, readers' loan records were extracted from working database of college library, and the readers' loan item sets were got by preprocessing the initial data. Multi-association rule mining model of reader loan was established based on Clementine 12.0. Based on the readers' loan records from working database of Qingdao Agricultural University, the associational relations among identities of reader, specialties of reader and categories of book were analyzed by using the mining model. According to the association rules which were mined, the demands for readers can be understood better, which provides theoretical foundation for offering personalized services to readers.