基于改进RFM聚类的高校图书馆用户画像研究

Research on User Portrait of University Library Based on Improved RFM Clustering

用户画像技术作为实现精准营销及服务的有效工具,在很多领域已经得到广泛验证和应用,也为高校图书馆的精准服务提供了新的思路。文章以某高校图书馆的读者信息和行为数据为例,引入并改进客户细分领域中的RFM模型,对读者群体进行聚类细分,同时建立了具有不同行为特征的图书馆读者群体的用户画像。最后,提出了基于改进RFM聚类的高校图书馆用户画像构建方法,以期为高校图书馆用户描述和精准服务提供参考。

As an effective tool for realizing precise marketing and service,user portrait technology has been widely verified and applied in many fields,which also provides a new idea for accurate services of university libraries.Therefore,taking the data of readers’information and behavior of a university library as an example,the paper introduces and improves the RFM model in the field of users segmentation,and subdivides the reader groups.Then,it establishes user portrait of reader groups of libraries with different behavior characteristics.Finally,it proposes a method of constructing user portrait of university libraries with the improvement of RFM clustering,hoping to provide reference for user description and accurate services of university libraries.