| 一种面向图书馆新书推荐服务的广义关联规则挖掘算法 |
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| 引用本文： | 佘俊胜,黄战.一种面向图书馆新书推荐服务的广义关联规则挖掘算法[J].现代图书情报技术,2006,1(10):16-20. |
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| 作者姓名： | 佘俊胜 黄战 |
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| 作者单位： | 暨南大学计算机科学系,广州,510632 |
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| 摘 要： | 基于MMS_Cumulate和GP-Apriori算法, 提出一种针对图书馆新书推荐服务特点的广义关联规则挖掘算法MAR_LCR。不仅能挖掘出形如“读者-图书”的广义关联规则,而且还允许用户为不同的项设置不同的最小支持度。通过对候选集的产生过程进行改进,可大大压缩搜索空间。实验结果表明,MAR_LCR算法是有效的。最后,提出新书推荐模型。
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| 关 键 词： | 多最小支持度 新书推荐 图书馆 |
| 收稿时间： | 2006-06-22 |
| 修稿时间： | 2006-07-03 |
A Generalized Association Rule Mining Algorithm for Library New Book Recommendation |
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| She Junsheng,Huang Zhan.A Generalized Association Rule Mining Algorithm for Library New Book Recommendation[J].New Technology of Library and Information Service,2006,1(10):16-20. |
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| Authors: | She Junsheng Huang Zhan |
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| Institution: | Department of Computer Science, Jinan University, Guangzhou 510632, China |
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| Abstract: | Based on MMS_Cumulate algorithm and GP-Apriori algorithm,a data mining algorithm,MAR_LCR is proposed for library new book recommendation service which is capable of finding generalized association rules in the form of "reader-book" and allows the user to specify multiple minimum supports for different items.The search space is greatly cut down by improving the process of candidate generation.Experiment results show that the MAR_LCR algorithm is highly effective.Finally,a new book recommendation model is proposed. |
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| Keywords: | Generalized association rule Multiple minimum supports New book recommendation Library |
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