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Literature Citation Contribution Analysis Based on the Topic Model
Received date: 2012-11-23
Revised date: 2013-01-09
Online published: 2013-02-20
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.
Key words： Labeled-LDA; topic model; citation analysis; full-text extraction
Zhang Jinsong , Chen Yan , Liu Xiaozhong . Literature Citation Contribution Analysis Based on the Topic Model[J]. Library and Information Service, 2013 , 57(04) : 120 -124,137 . DOI: 10.7536/j.issn.0252-3116.2013.04.021
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