知识发现视角下词汇历时语义挖掘与可视化研究

doi:10.3772/j.issn.1000-0135.2021.10.004

情报学报

2021, Vol. 40

Issue (10): 1052-1064 DOI: 10.3772/j.issn.1000-0135.2021.10.004

情报分析方法与技术

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知识发现视角下词汇历时语义挖掘与可视化研究

潘俊¹, 吴宗大^2,3

1.浙江科技学院理学院大数据科学系，杭州 310023
2.绍兴文理学院计算机系，绍兴 312000
3.南京大学信息管理学院，南京 210093

Diachronic Semantic Mining and Visualization of Chinese Words: A Knowledge Discovery Perspective

Pan Jun¹, Wu Zongda^2,3

1.Department of Big Data Science, School of Science, Zhejiang University of Science and Technology, Hangzhou 310023
2.Department of Computer Science and Engineering, Shaoxing University, Shaoxing 312000
3.School of Information Management, Nanjing University, Nanjing 210093

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摘要针对中文词汇历时语义的知识挖掘问题，本研究设计了一个面向知识发现的可扩展框架，该框架基于松耦合的可配置服务式架构，底层提供数据清洗、数据规范化、历时词向量训练等服务，中间层通过XML（extensible markup language）配置来定制基础数据的抽取策略并实现界面映射，顶层通过对关键服务的组合调用，构建知识发现与可视化的应用模块。以《人民日报》词汇历时语义挖掘实践为例，给出了该框架的一个具体实现，展示了历时词向量在数字人文和社会计算研究中的可能应用模式。该方法框架及其实现具有较好的通用性，通过二次开发，能灵活构建各类面向知识发现的词汇历时语义挖掘应用，并可推广到对其他历时语料的知识挖掘。

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	潘俊
	吴宗大

关键词 ：知识发现, 词向量, 表示学习, 历时语义, 人民日报

收稿日期: 2020-09-28

基金资助:教育部人文社会科学研究青年基金项目“基于知识库和大规模文本的词汇语义表示研究”（18YJCZH137）；浙江省公益技术应用研究计划项目“多源异构数据融合的农业知识服务关键技术与应用”（LGN21F020003）；浙江省高校重大人文社科攻关计划“基于语义混淆的个性化信息服务用户隐私保护策略”（2021GH017）。

作者简介: 潘俊，男，1978年生，博士，讲师，硕士生导师，研究方向为自然语言处理、机器学习；吴宗大，男，1983年生，博士后，教授，硕士生导师，研究方向为信息检索、数字图书馆，E-mail：zongda1983@163.co；

引用本文:

潘俊, 吴宗大. 知识发现视角下词汇历时语义挖掘与可视化研究[J]. 情报学报, 2021, 40(10): 1052-1064.
Pan Jun, Wu Zongda. Diachronic Semantic Mining and Visualization of Chinese Words: A Knowledge Discovery Perspective. 情报学报, 2021, 40(10): 1052-1064.

链接本文:

http://qbxb.istic.ac.cn/CN/10.3772/j.issn.1000-0135.2021.10.004 或 http://qbxb.istic.ac.cn/CN/Y2021/V40/I10/1052

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