现代情报2024，Vol.44Issue(1)：48-56,108,10.DOI:10.3969/j.issn.1008-0821.2024.01.005
面向投稿选刊的学术论文多标签分类研究
Research on Multi-label Classification of Academic Papers for Periodical Selection
摘要
Abstract
[Purpose/Significance]The academic paper submission is faced with the problems of journal selection di-versity and re-submission,this paper studies the use of machine learning technology to give multi-label recommendations for periodical submission based on the content of the academic paper.[Method/Process]Papers from 8 CSSCI journals in the field of information science in recent 20 years were selected as samples,TextCNN,TextRNN,and pre-trained lan-guage model BERT were used for experiments,and the experimental effects under different feature combinations and multi-label setting strategies were compared.[Result/Conclusion]Multi-label classification can reflect the suitability of articles for different periodical,and the pre-trained language model BERT performs best,with F1 reaching 68.99%.关键词
投稿选刊/多标签分类/深度学习/自然语言处理Key words
periodical selection/multi-label classification/deep learning/natural language learning分类
社会科学引用本文复制引用
江天明,郑国杰,王晴,曹高辉..面向投稿选刊的学术论文多标签分类研究[J].现代情报,2024,44(1):48-56,108,10.基金项目
中国博士后科学基金面上项目"基于深度语义挖掘的引文推荐可解释性研究"(项目编号:2021M701367) （项目编号:2021M701367）
中央高校基本科研业务费项目"基于机器学习的引文推荐可解释性研究"(项目编号:CCNU21XJ020)、"开源跨模态科技情报知识组织与智能分析"(项目编号:CCNU22QN016). （项目编号:CCNU21XJ020）
