| SOM聚类技术在读者行为分析中的应用 |
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| 引用本文： | 马芳.SOM聚类技术在读者行为分析中的应用[J].数字图书馆论坛,2014(6):63-67. |
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| 作者姓名： | 马芳 |
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| 作者单位： | 烟台工程职业技术学院图书馆,烟台264006 |
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| 摘 要： | 随着数字图书馆技术的发展，图书馆每天产生大量的数据，针对这些海量数据，采用数据挖掘技术中的自组织映射神经网络（SOM）算法，根据读者借阅行为特征对读者进行聚类，得到不同阅读兴趣和需求的读者群，并通过测试验证该算法是有效可行的。
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| 关 键 词： | 数据挖掘 RFM模型 SOM聚类 |
User Behavior Analysis in University Library by SOM |
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| MA Fang.User Behavior Analysis in University Library by SOM[J].Digital Library Forum,2014(6):63-67. |
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| Authors: | MA Fang |
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| Institution: | MA Fang (Library, Yantai Engineering and Technology College, Yantai 264006, China ) |
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| Abstract: | With the development of digital library technology, library produces a large number of data every day. Based on these data, using the algorithm of Self Organization Map （SOM） in data mining technology, clustering readers according to their borrowing behavior, we classify different reading interest and demand of readers. Through the validation, the algorithm proves feasible and effective. |
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| Keywords: | Data mining RFM model SOM clustering |
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