基于语境概念核心词提取算法研究

doi:10.3772/j.issn.1000-0135.2019.11.006

情报学报

2019, Vol. 38

Issue (11): 1177-1186 DOI: 10.3772/j.issn.1000-0135.2019.11.006

情报分析方法与技术

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基于语境概念核心词提取算法研究

石进¹, 韩进², 赵小柯¹, 刘千里¹

1.南京大学信息管理学院，南京 210023
2.南京信息工程大学计算机与软件学院，南京 210044

Research on Core Word Extraction Algorithm Based on Contextual Concept

Shi Jin¹, Han Jin², Zhao Xiaoke¹, Liu Qianli¹

1.School of Information Management, Nanjing University, Nanjing 210023
2.Col1ege of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044

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摘要当前国内外对于语境核心词提取算法的研究较少，更多的是对于关键词提取算法的研究，本文提出了一种基于语境的依存句法分析算法。首先本文证明了依存句法分析问题可以等价为如何拆分句子得到最小尺度的语境，以及求出最小尺度语境中的核心词这两个问题。为了解决这两个问题，本文提出了两种语境核心词求解方法，分别是基于熵比较与基于入度和比较的语境核心词提取算法，并基于此进一步提出了最小语境求解算法来构建依存句法树。通过采集《情报学报》2007—2018年1152篇有效的论文数据并进行测试，分别与经典的关键词提取算法TF/IDF、Text-Rank、LDA提取的关键词进行了对比，实验结果表明，本文提出的基于语境的依存句法分析算法对于关键词的提取效果良好。

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	石进
	韩进
	赵小柯
	刘千里

关键词 ：依存句法分析, 知识发现, 语境模型

收稿日期: 2018-12-10

基金资助:国家社会科学基金后期资助项目“面向国家安全的情报研究”（18FTQ00）；国家社会科学基金青年项目“意义构建视野下安全情报的弱信号研究”（15CTQ032）。

作者简介: 石进，男，1976年生，博士，副教授，主要研究方向为安全情报、大数据分析，E-mail:shijin@nju.edu.cn

引用本文:

石进, 韩进, 赵小柯, 刘千里. 基于语境概念核心词提取算法研究[J]. 情报学报, 2019, 38(11): 1177-1186.
Shi Jin, Han Jin, Zhao Xiaoke, Liu Qianli. Research on Core Word Extraction Algorithm Based on Contextual Concept. 情报学报, 2019, 38(11): 1177-1186.

链接本文:

https://qbxb.istic.ac.cn/CN/10.3772/j.issn.1000-0135.2019.11.006 或 https://qbxb.istic.ac.cn/CN/Y2019/V38/I11/1177

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