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基于论文属性的加权共词模型探讨
Research in the Weighted Co-word Analysis Based on the Attributes of Articles
查看参考文献9篇
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文摘
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本文在分析共词研究现状的基础上，对论文属性在分析中的影响、作用进行了探讨，发现目前共词分析方法中没有考虑论文属性对共词分析所产生的影响问题，进而构建基于论文属性的加权共词分析模型。模型构建之后，利用加权后的Jaccard系数来计算关键词之间的距离。在案例分析部分，作者将被引次数作为论文属性的综合衡量指标代表来具体实现文中所讨论的加权共词模型，并从网络上下载了数据，对数据进行共词分析和加权共词分析，并对二者的分析结果进行了对比分析，验证了加权共词模型的可行性。文章的最后，提出了加权共词模型需要进一步研究的问题。 |
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其他语种文摘
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In this paper, based on the current situation of co-word analysis, the author tries to discuss the influences and the functions of articles＇ attributes in the analysis and finds that no one considers the influences of the articles＇ attributes upon co-word analysis. And then, the author models the weighted co-word analysis based on the attributes of articles. After building up the model of weighted co-word analysis, the author calculates the distances between keywords by weighted Jaccard Index. In the section of case study, the author takes the cited times as the attribute of article to implement the model of weighted co-word, and download the data from Internet, and then analyses the data by co-word model and the weighted co-word model individually. After that the author compares the results of the two methods to validate the weighted co-word model. At last, the un-touched and advanced researches related to the weighted co-word analysis are listed out in the paper. |
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来源
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情报学报
,2008,27(1):89-92 【核心库】
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关键词
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共词
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共词分析
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加权共词分析
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被引次数
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地址
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1.
中国科学院文献情报中心, 北京, 100080
2.
中国科学院研究生院, 北京, 100049
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语种
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中文 |
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文献类型
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研究性论文 |
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ISSN
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1000-0135 |
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学科
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社会科学总论 |
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文献收藏号
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CSCD:3221362
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参考文献 共
9
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