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基于图模型的关键词提取算法研究

叶子诚1,2,闫桂英1,2   

  1. 1.中国科学院数学与系统科学研究院,北京 100190;2.中国科学院大学,北京 100049
  • 出版日期:2018-04-25 发布日期:2021-06-25

叶子诚, 闫桂英. 基于图模型的关键词提取算法研究[J]. 系统科学与数学, 2021, 41(4): 967-975.

YE Zicheng, YAN Guiying. Study on Keyword Extraction Algorithm Based on Graphical Model[J]. Journal of Systems Science and Mathematical Sciences, 2021, 41(4): 967-975.

Study on Keyword Extraction Algorithm Based on Graphical Model

YE Zicheng1,2 ,YAN Guiying1,2   

  1. 1. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190; 2. University of Chinese Academy of Sciences, Beijing 100049
  • Online:2018-04-25 Published:2021-06-25
自动抽取关键词技术应用广泛. 文章将文本抽象成一个图模型, 结合经典的TF-IDF算法和TextRank算法, 利用图上的随机游走算法实现排序. 以互联网上的新闻文本为数据进行了实验, 结果显示该算法效果较传统的关键词提取算法更优.
Keyword automatic extraction algorithm has wide application. This paper abstracts the text into a graphical model, combines classical TF-IDF algorithm and TextRank algorithm and uses the random walk algorithm on the graph to rank the nodes. Experiment is conducted based on the news text data form Internet. The results show that the algorithm has better effect than that of traditional keyword extraction algorithm.
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