学术文本词汇功能识别

doi:10.3772/j.issn.1000-0135.2022.07.006

情报学报

2022, Vol. 41

Issue (7): 720-732 DOI: 10.3772/j.issn.1000-0135.2022.07.006

情报技术与应用

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学术文本词汇功能识别

罗卓然^1,2, 陆伟^1,2, 蔡乐^1,2, 程齐凯^1,2

1.武汉大学信息管理学院，武汉 430072
2.武汉大学信息检索与知识挖掘研究所，武汉 430072

Application of Lexical Functions in Novelty Measurement of Academic Papers

Luo Zhuoran^1,2, Lu Wei^1,2, Cai Le^1,2, Cheng Qikai^1,2

1.School of Information Management, Wuhan University, Wuhan 430072
2.Information Retrieval and Knowledge Mining Laboratory, Wuhan University, Wuhan 430072

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摘要为进一步挖掘学术论文新颖性的丰富内涵，本文以组合创新理论为基础，开展了基于词汇功能的学术论文新颖性度量研究。以ACM（Association for Computing Machinery）Digital Library收录的论文为数据，提出了面向CS（computer science）领域进一步预训练的词汇新颖性计算方法和基于语义相似度的问题-方法组合新颖度计算流程，分别计算了问题词、方法词、问题-方法组合和论文的语义新颖性，并将本文语义新颖性计算方法与已有的词频共现新颖性计算方法进行了对比。研究结果表明，ACM Digital Library收集的论文在研究方法和研究问题上创新度均较高，相较于已有的论文新颖性计算方法，本文提出的方法能从语义层面捕获更为精细的新颖性差异。

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	罗卓然
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关键词 ：新颖性度量, 词汇功能, 问题-方法组合, 预训练模型

收稿日期: 2021-07-27

基金资助:国家社会科学基金重大项目“基于认知计算的学术论文评价理论与方法研究”（17ZDA292）。

作者简介: 罗卓然，女，1993年生，博士研究生，主要研究领域为创新评价、数据挖掘，E-mail：zoraluo@whu.edu.cn；陆伟，男，1974年生，教授，博士生导师，主要研究领域为信息检索与可视化、数据智能与创新评价、AI人机协同等；蔡乐，男，1998年生，硕士研究生，主要研究领域为数据挖掘、深度学习；程齐凯，男，1989年生，副教授，主要研究领域为信息检索、科技情报分；

引用本文:

罗卓然, 陆伟, 蔡乐, 程齐凯. 学术文本词汇功能识别[J]. 情报学报, 2022, 41(7): 720-732.
Luo Zhuoran, Lu Wei, Cai Le, Cheng Qikai. Application of Lexical Functions in Novelty Measurement of Academic Papers. 情报学报, 2022, 41(7): 720-732.

链接本文:

https://qbxb.istic.ac.cn/CN/10.3772/j.issn.1000-0135.2022.07.006 或 https://qbxb.istic.ac.cn/CN/Y2022/V41/I7/720

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