现代情报
現代情報
현대정보
Journal of Modern Information
2009年
8期
185~187
,共null页
数据挖掘 关联规则 智能分析 聚类分析 决策树
數據挖掘 關聯規則 智能分析 聚類分析 決策樹
수거알굴 관련규칙 지능분석 취류분석 결책수
data mining; association rule; intelligent analysis; cluster analysis; decision tree;
本文给出一种高校图书馆智能分析应用数据挖掘的思路和模式,以江苏广播电视大学图书馆为实例,详细分析了读者关联挖掘、图书动态聚类分析、读者特征细分挖掘在图书管理中的具体应用,经实施表明,数据挖掘的结果合理,可以帮助图书馆的决策者进行优化管理。
本文給齣一種高校圖書館智能分析應用數據挖掘的思路和模式,以江囌廣播電視大學圖書館為實例,詳細分析瞭讀者關聯挖掘、圖書動態聚類分析、讀者特徵細分挖掘在圖書管理中的具體應用,經實施錶明,數據挖掘的結果閤理,可以幫助圖書館的決策者進行優化管理。
본문급출일충고교도서관지능분석응용수거알굴적사로화모식,이강소엄파전시대학도서관위실례,상세분석료독자관련알굴、도서동태취류분석、독자특정세분알굴재도서관리중적구체응용,경실시표명,수거알굴적결과합리,가이방조도서관적결책자진행우화관리。
This paper provided an idea and a model of using data mining on the intelligent analysis for university libraries.Taking Jiangsu radio and television university library as an example,the readers related analysis of mining,cluster analysis of dynamic books,the detailed mining based on reader s features in the library were carried out.Practical calculations showed that the results of such data mining were reasonable.It may help the decision-makers to optimize the managements of libraries.
