| 基于二部图法的Web知识社群挖掘* |
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| 引用本文： | 任辉,周晓光,申晋.基于二部图法的Web知识社群挖掘*[J].现代图书情报技术,2007,2(4):39-42. |
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| 作者姓名： | 任辉 周晓光 申晋 |
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| 作者单位： | 1. 鲁东大学图书馆,烟台,264025
2. 山东理工大学电气与电子工程学院,淄博,255049 |
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| 基金项目： | 教育部科学技术基金研究重点项目 |
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| 摘 要： | 二部图法分析模型是将Web页的内容信息和超链接信息相结合给出的一种基于分类方法的算法，利用二部图可以求出网页的最大匹配与完全匹配，挖掘出隐含的知识社群，能更准确地实现对用户的合理定位。
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| 关 键 词： | 知识社群 Web挖掘 |
| 收稿时间： | 2006-12-28 |
| 修稿时间： | 2006-12-28 |
Excavation of Web Knowledge Association Based on Bipartite Graph |
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| Ren Hui,Zhou Xiaoguang,Shen Jin.Excavation of Web Knowledge Association Based on Bipartite Graph[J].New Technology of Library and Information Service,2007,2(4):39-42. |
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| Authors: | Ren Hui Zhou Xiaoguang Shen Jin |
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| Institution: | 1. Ludong University Library, Yantai 264025, China;2.School of Electric and Electronic Engineering, Shandong University of Technology, Zibo 255049, China |
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| Abstract: | The analysis model of bipartite graph is to combine the content information on Web page and hyper-chain information, so as to provide an algorism based on classification method. By using bipartite graph,one can work out the Website’s maximum matching and complete matching. This method can also help excavate the implicit knowledge association and locate accurately the reasonable orientation of the users. |
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| Keywords: | Bipartite graph Knowledge association Web excavation |
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