| 摘 要: 随着智慧图书馆的兴起，可以对图书馆数字资源大数据进行深入挖掘利用，区域高校图书馆数字资源一站式检索必然是进一步增强馆际合作、数据挖掘、资源互享的有效平台。基于朴素贝叶斯的区域高校图书馆数字资源一站式决策算法设计了一种决策树与朴素贝叶斯模型相结合的两层模型方法，通过提取整合区域内各高校图书馆数字资源大数据的特征属性，并利用朴素贝叶斯模型进一步筛选特征属性，从而构建决策树架构，支撑区域高校图书馆数字资源一站式检索。利用基于朴素贝叶斯的区域高校图书馆数字资源一站式决策算法可以实现检索资源过程更加便捷高效，检索结果的准确率呈现翻倍式增长。 |
| 关键词: 数字资源；朴素贝叶斯；决策树；一站式 |
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中图分类号: TP312
文献标识码: A
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| 基金项目: 南通大学人文社会科学研究项目“云环境下高校图书馆数字资源高效使用的策略研究”(16w16). |
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| A One-stop Decision-making Algorithm for Digital Resources of Regional University Libraries based on Naive Bayes |
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GU Chunyan
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(Nantong University Library, Nantong 226001, China)
337927012@qq.com
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| Abstract: With the rise of smart libraries, big data of library digital resources can be deeply excavated and utilized. One-stop retrieval of digital resources in regional university libraries is bound to be an effective platform to further enhance interlibrary cooperation, data mining, and resource sharing. This paper proposes to design a two-layer model method combining decision tree and Naive Bayes model, based on Naive Bayes-based one-stop decision-making algorithm for regional university libraries' digital resources. By extracting and integrating the characteristic attributes of the digital resources big data in various university libraries in the area, and using Naive Bayes model to further filter the characteristic attributes, a decision tree structure can be constructed to support the one-stop retrieval of digital resources in the regional university libraries. The one-stop decision-making algorithm for digital resources in regional university libraries based on Naive Bayes can be realized: the process of retrieving resources is more convenient and efficient, and the accuracy of retrieval results has doubled. |
| Keywords: digital resources; Naive Bayes; decision tree; one-stop |
