基于多标签分类的科技文献学科交叉研究性质识别

Identifying Interdisciplinary Sci-Tech Literature Based on Multi-Label Classification

【目的】识别科技文献的学科交叉研究性质,为挖掘学科交叉前沿问题提供支撑。【方法】将学科领域专家提供的科技文献已有学科标签,与文本分类算法预测的科技文献学科标签相结合,共同识别学科交叉科技文献。【结果】相较于直接基于模型预测,本文提出的识别学科交叉科技文献的方法F1指标从0.23提升到0.45。【局限】模型识别学科交叉研究性质科技文献的召回率指标较低。【结论】通过关注不同学科间科技文献被分类错误的数据,判断科技文献的学科交叉研究性质,是值得进一步关注的研究方向。

[Objective] This paper tries to identify interdisciplinary sci-tech literature, aiming to find emerging interdisciplinary issues. [Methods] We combined the discipline labels of sci-tech literature provided by specialists with labels predicted by text classification algorithms to find interdisciplinary studies. [Results] The F1 value of the proposed method reached 0.45, which was 0.22 higher than those of the model-based predictions.[Limitations] The model had low recall values for identifying the interdisciplinary sci-tech research.[Conclusions] The paper effectively addresses the classification issues of interdisciplinary sci-tech literature,which merits more studies in the future.