基于评审意见的科技论文要点识别与利用

doi:10.3772/j.issn.1000-0135.2023.05.005

情报学报

2023, Vol. 42

Issue (5): 562-574 DOI: 10.3772/j.issn.1000-0135.2023.05.005

情报技术与应用

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基于评审意见的科技论文要点识别与利用

陈翀¹, 程子佳², 王传清³, 李蕾¹

1.北京师范大学政府管理学院,北京 100875
2.中国人民大学信息资源管理学院,北京 100872
3.中国科学院文献情报中心,北京 100190

Identification and Utilization of Key Points of Scientific Papers Based on Peer Review Texts

Chen Chong¹, Cheng Zijia², Wang Chuanqing³, Li Lei¹

1.School of Government, Beijing Normal University, Beijing 100875
2.School of Information Resource Management, Renmin University of China, Beijing 100872
3.National Science Library, Chinese Academy of Sciences, Beijing 100190

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摘要科研用户查找文献往往瞄准特定任务，如寻找选题、方法、结论等，面对检索出的大量文献需要甄别要点，判断价值，这一过程既需要熟悉专业知识又耗时费力。论文评审意见中蕴含了同行专家的权威看法，包括对论文要点和参考价值的揭示，可以为满足上述需求提供有效帮助。本文以论文评审意见为对象，围绕科研活动中的典型要素定义评审意见中的要点类型，通过有监督学习方法提取评审意见所述的论文要点，不但为论文提供了结构化要点概括，还能用于辅助文献检索。本文采集《心理学报》期刊2014年年初至2020年年底发表的549篇论文及其对应的评审意见，将其中概括信息划分为概述、方法、结果和亮点4种要点类型，用SVM（support vector machine）、FastText、TextCNN（convolutional neural networks）及BiLSTM（bi-directional long short-term memory）4种方法训练分类模型并比较效果。研究结果表明，BiLSTM方法对要点识别效果最佳，在5次交叉检验中的平均识别准确率达到91%。要点中的亮点进一步分为选题、价值、方法和写作4种类型，采用SVM方法识别，F1值达到85%。作为对研究结果的应用，本文采用识别出的论文要点辅助对论文的理解，并按亮点做检索结果分类，改进了论文检索的组织与服务形式。本文创新之处在于：①提出了从评审意见中挖掘论文要点的研究问题，制定了要点类型的框架和层次；②将识别要点转化为分类问题，通过比较评价找到综合最优的识别方法；③实现了基于要点的检索结果分类组织，帮助用户理解论文并进行价值判断。

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	陈翀
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	王传清
	李蕾

关键词 ：评审意见挖掘, 要点识别, 要点分类, 论文要点, 文献检索

收稿日期: 2022-05-07

基金资助:国家社会科学基金一般项目“面向科研人员定量评价的多维学术专长识别及属性度量研究”（21BTQ065）。

作者简介: 陈翀，女，1975年生，博士，教授，硕士生导师，主要研究领域为知识组织、文本挖掘；程子佳，女，2000年生，硕士研究生，主要研究领域为文本挖掘、信息检索；王传清，男，1980年生，博士，副编审，主要研究领域为信息资源管理、期刊编辑与传播；李蕾，女，1989年生，博士，讲师，硕士生导师，主要研究领域为社会计算、信息行为、信息检索与评价，E-mail：leili@bnu.edu.cn；

引用本文:

陈翀, 程子佳, 王传清, 李蕾. 基于评审意见的科技论文要点识别与利用[J]. 情报学报, 2023, 42(5): 562-574.
Chen Chong, Cheng Zijia, Wang Chuanqing, Li Lei. Identification and Utilization of Key Points of Scientific Papers Based on Peer Review Texts. 情报学报, 2023, 42(5): 562-574.

链接本文:

https://qbxb.istic.ac.cn/CN/10.3772/j.issn.1000-0135.2023.05.005 或 https://qbxb.istic.ac.cn/CN/Y2023/V42/I5/562

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