| K-means聚类算法在高校图书馆读者群细分中的应用研究 |
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| 引用本文： | 刘敏.K-means聚类算法在高校图书馆读者群细分中的应用研究[J].中国科教创新导刊,2010(22):254-254. |
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| 作者姓名： | 刘敏 |
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| 作者单位： | 贵州大学计算机科学与信息学院,贵州贵阳,550025;贵阳学院教师教育学院,贵州贵阳,550003 |
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| 摘 要： | K-means算法是聚类分析中的重要算法。运用K-means算法依据高校图书馆读者的借阅行为、借阅习惯等方面的明显差异,把读者划分成若干个读者群,找出不同读者类群的需求特点,重新配置服务资源,为图书馆充分获取读者信息、制定策略提供理论和方法指导。
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| 关 键 词： | K-means算法 图书馆 读者群细分 |
Clustering Methods in Data Mining |
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| Liu Min.Clustering Methods in Data Mining[J].China Education Innocation Herald,2010(22):254-254. |
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| Authors: | Liu Min |
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| Institution: | Liu Min 1 .Guizhou University, School of Computer Science and Information,Guiyang,Guizhou,550025,China 2.Guiyang University of Teacher Education,Guiyang, Guizhou,550003,China |
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| Abstract: | The K-means algorithm is in the cluster analysis important algorithm. K-means algorithm is based on the use of College Library＇s borrowing behavior, lending significant difference in the areas of customs,the reader is divided into a number of readers to identify the needs of different groups of characteristics of the reader,re-allocation of resources and full access for the library readers information,develop strategies to provide theoretical and methodological guidance. |
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| Keywords: | K-means algorithm Library Reader group segmentation |
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