| 基于主题模型的文献引用贡献分析 |
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| 引用本文： | 张金松,陈燕,刘晓钟.基于主题模型的文献引用贡献分析[J].图书情报工作,2013,57(4):120. |
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| 作者姓名： | 张金松 陈燕 刘晓钟 |
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| 作者单位： | 1. 大连海事大学交通运输管理学院;
2. 美国印第安纳大学布鲁明顿分校 |
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| 摘 要： | 传统引文分析方法中,文献间的相互关系通常由引用关系决定,也就是说,如果文献A引用文献B,则证明B对A有一定的贡献,然而具体的贡献值与引用原因却很难进行界定。采用主题模型的方法,将原著、引文、被引文献看作是主题模型上的概率分布,通过全文抽取的方法,对引用的原因以及引文贡献值进行分析。首先介绍研究背景与研究意义,并对基本概念进行阐述;然后介绍引文抽取方法、 利用Labeled-LDA模型建立主题模型方法等;最后通过实验部分建立基于不同主题的文献引用网络图,并利用工具使其可视化表示。
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| 关 键 词： | Labeled-LDA 主题模型 引文分析 全文抽取 |
| 收稿时间： | 2012-11-23 |
| 修稿时间： | 2013-01-09 |
Literature Citation Contribution Analysis Based on the Topic Model |
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| Zhang Jinsong,Chen Yan,Liu Xiaozhong.Literature Citation Contribution Analysis Based on the Topic Model[J].Library and Information Service,2013,57(4):120. |
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| Authors: | Zhang Jinsong Chen Yan Liu Xiaozhong |
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| Institution: | 1. Dalian Maritime University, Dalian 116026;
2. Indiana University Bloomington, Indiana USA 47408 |
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| Abstract: | In the traditional citation analysis, it assumes that the relationship between literatures is simply based on citation links. For example, if paper A cites paper B, it means that B is important for A, while it is difficult to judge the contribution and citing reason. This paper treats with the citing paper, cited paper and citation context as the probability distribution on the topics, and analyzes the citing reason and contribution by full-text extraction. Firstly, it introduces the research background and significance, as well as the basic conceptions. Secondly, some methods are illustrated for supporting the experiment, such as full-text extraction, and topic model based on Labeled-LDA. Finally, different citation graphs are established and visualized based on different topics. |
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| Keywords: | Labeled-LDA topic model citation analysis full-text extraction |
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