基于聚类分析与关联分析的高校图书馆读者借阅模式实证研究——以烟台大学为例  

Empirical Study of Reader Borrowing Pattern in University Library Basing on Cluster Analysis and Association Analysis: Case Study of Yantai University

作　　者：曲佳彬[1] 

机构地区：[1]烟台大学图书馆,山东烟台264005

出　　处：《情报探索》2016年第2期105-109,113,共6页Information Research

摘　　要：[目的/意义]通过数据挖掘技术发现读者的借阅模式和借阅习惯,能有效提高图书资源的利用率和图书馆的服务水平。[方法/过程]以烟台大学图书馆读者借阅记录为数据来源,选择读者借阅量、借阅图书类目、读者所属学院和读者类型作为参考变量,对读者进行聚类分析,再对已聚类的读者借阅书目进行关联挖掘。[结果/结论]聚类后的读者群组有相似的借阅模式,各个群组表现出显著的借阅特征,并与所借阅的图书类目之间存在显著关联性,据此指导图书采访工作、优化图书馆藏、推行个性化服务,可以使高校图书馆服务更加科学合理。[Purpose/significance] Using data mining to find readers’ borrowing pattern and borrowing habit will improve resource utilization and service level in library effectively.[Method/process] The paper takes reader borrowing records in Yantai University Library as data source, chooses borrowing quantity, borrowing book categories, reader’s colleges and reader’s types as reference variables, makes clustering analysis on readers and then makes association mines clustered reader borrowing catalogues. [Result/conclusion] Each clustered reader group has similar borrowing pattern, and groups show remarkable characteristics and outstanding relevance with borrowing book categories. The research results can be used in book acquisition, optimizing collection and personalized service, so as to make university library service more scientific and reasonable.

关 键 词：高校图书馆 读者借阅行为 聚类分析 关联分析 

分 类 号：G251.4[文化科学—图书馆学]