图书情报工作 ›› 2020, Vol. 64 ›› Issue (1): 93-104.DOI: 10.13266/j.issn.0252-3116.2020.01.012

• 图书情报与档案管理前沿热点专辑 • 上一篇    下一篇

基于知识元的学术论文内容创新性智能化评价研究

李贺1, 杜杏叶1,2,3   

  1. 1. 吉林大学管理学院 长春 130002;
    2. 中国科学院文献情报中心 北京 100190;
    3. 中国科学院大学经济与管理学院图书情报与档案管理系 北京 100190
  • 收稿日期:2019-12-11 出版日期:2020-01-05 发布日期:2020-01-05
  • 通讯作者: 杜杏叶(ORCID:0000-0001-5016-0561),副研究馆员,副编审,硕士生导师,博士,通讯作者,E-mail:duxy@mail.las.ac.cn
  • 作者简介:李贺(ORCID:0000-0001-8847-3619),教授,博士生导师。
  • 基金资助:
    本文系国家自然科学基金面上项目"基于图模型的多源异构在线产品评论数据融合与知识发现研究"(项目编号:71974075)研究成果之一。

Research on Intelligent Evaluation for the Content Innovation of Academic Papers

Li He1, Du Xingye1,2,3   

  1. 1. School of Management Jilin University, Changchun 130022;
    2. National Science Library, Chinese Academy of Sciences, Beijing 100190;
    3. Department of Library, Information and Archives Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190
  • Received:2019-12-11 Online:2020-01-05 Published:2020-01-05

摘要: [目的/意义] 创新性是对学术论文质量最基本的要求,是学术论文的灵魂,是学术论文评价的核心。知识元是学术论文基本组成单元。基于知识元理论和机器学习相关理论与算法,从学术论文内容层面研究计算机如何智能化地进行创新性评价及其实现过程与方法。[方法/过程] 首先,构建学术论文的研究问题、理论、方法、结论4个知识元本体,接着提出基于知识元的学术论文创新性判断模型。其次,根据学术论文研究特点,构建理论与方法机器分类模型及知识元的抽取规则与抽取方法,建立规则库和知识语料库。最后,基于语义相似度计算方法,根据判断规则和相关权重对学术论文4个维度的创新性进行评分。[结果/结论] 基于知识元抽取的学术论文创新性评分系统的实证结果表明,该智能化评价方法具有一定的可行性,可为学术论文内容创新性智能化评价系统的最终实现提供方法借鉴。

关键词: 学术论文, 知识元, 内容创新性, 智能评价

Abstract: [Purpose/significance] Innovation is the key factor of academic paper evaluation. Based on the knowledge element theory and machine learning theory and algorithm, this paper studies how to intelligently evaluate the innovation of academic papers from the content of paper.[Method/process] Firstly, we constructed 4 knowledge element ontologies of academic papers including ‘research problem ontology’, ‘theory ontology’, ‘method ontology’ and ‘conclusion ontology’, and proposed the model of innovation evaluation. Secondly, we put forward the rules of knowledge element extraction. Word2vec and naive Bayes were used to classify the innovation of theories and methods of academic papers, and SVM model was used to build the rule base of knowledge element extraction. At last, on the basis of the construction of knowledge Meta base of academic papers, we proposed the basic methods of intelligent evaluation of research questions, theories, methods and conclusions of academic papers. We also constructed the process of intelligent evaluation of innovation of academic papers.[Result/conclusion] The feasibility of the methods is verified by the experiment and could provide the references for the realization of intelligently evaluation of academic paper.

Key words: academic papers evaluation, knowledge element, content innovation, intelligent evaluation

中图分类号: