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首页 > 过刊浏览>2020年第29卷第7期 >56-69. DOI:10.15888/j.cnki.csa.007527
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基于扩展Bcp指数的领域主题发展态势可视分析
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中国科学院“十三五”信息化专项课题(XXH13504)


Visual Analysis for Development Situation of Research Topics Based on Extended Bcp Index
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    摘要:

    通过对已发表论文的分析, 掌握研究领域的发展状况, 对研究人员具有重要意义. 面向此类需求, 提出一种基于扩展Bcp指数的领域主题发展态势可视分析方法. 首先, 从论文的标题、摘要以及作者提供的关键字中自动提取包含词组类型的关键词集合. 提取这些关键词之间的共现关系. 根据这些关键词使用LDA算法进行提取主题. 然后, 提出一种扩展Bcp指数来度量关键词的发展状态, 并据此对关键词和论文进行分类, 以确定发展状态类型. 基于此方法, 设计并实现了一个由需求驱动的领域主题发展态势可视分析工具VISExplorer. 该系统可以展现领域主题分布和发展趋势、可以按主题推荐高质量文章、可以浏览不同主题中的高产出作者和高引用作者. 最后, 以可视化领域为例, 根据1990年至2018年在可视化领域顶级会议IEEE VIS上发表的论文, 对VISExplorer进行了实际案例应用, 并通过用户反馈证明了方法的实用性和有效性.

    Abstract:

    It is of great significance for researchers to master the development of research field through the analysis of published papers. In order to meet this requirement, a visual analysis method based on extended Bcp index was proposed. First of all, keywords containing phrases are automatically extracted from the title, abstract, and author provided keywords. Then co-occurrence relationship between these keywords was extracted. According to these keywords, LDA algorithm was used to extract topics. Then, an extended Bcp index was proposed to measure the development state of keywords. Based on this method, a visual analytic tool VISExplorer was designed and implemented. VISExplorer can show the distribution and development trend of domain topics, recommend high-quality papers, and browse top authors. Finally, taking the domain of visualization as an example, VISExplorer was conducted in real cases of publications on IEEE VIS Conference from 1990 to 2018, and the usefulness and effectiveness are proved by user’s feedbacks.

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王杨,余敏槠,单桂华,田东,陆忠华.基于扩展Bcp指数的领域主题发展态势可视分析.计算机系统应用,2020,29(7):56-69

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  • 收稿日期:2019-12-23
  • 最后修改日期:2020-01-20
  • 在线发布日期: 2020-07-04
  • 出版日期: 2020-07-15
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