一种基于系统聚类的图书馆读者细分模型

A Segmentation Model of Library Reader Based on System Clustering Algorithm

读者细分是图书馆管理中迫切需要解决的问题,"被动服务"的图书馆服务模式逐渐转向"读者驱动",所提供的个性化服务应该符合读者的实际需求,因此这种个性化服务对于目前单一的读者属性细分方式提出了更高的要求。本文采用系统聚类算法建立了图书馆读者细分模型,进而提出了四种不同的细分方式,并用图书馆流通数据对模型进行了测试,验证了该细分模型的实用性和有效性。

Reader segmentation is an imperative problem to the library management. Library services mode characterized by ＂passive service＂ has gradually transformed to ＂reader - driven＂, which requires to provide personalized service solution in accordance with the actual needs of the readers. So personalized service put up higher requirements for the currant single property division of readers, tins paper adopted system clustering algorithm to set up a reader segmentation model of library, further presented four different division methods. After the model was tested by a large number of realistic library circulation data, the practicality and validation of the model was proved.