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基于图卷积网络的表格隶属关系抽取

张宇童 李启元 刘树衎

张宇童,李启元,刘树衎. 基于图卷积网络的表格隶属关系抽取[J]. 北京航空航天大学学报,2024,50(4):1308-1315 doi: 10.13700/j.bh.1001-5965.2022.0382
引用本文: 张宇童,李启元,刘树衎. 基于图卷积网络的表格隶属关系抽取[J]. 北京航空航天大学学报,2024,50(4):1308-1315 doi: 10.13700/j.bh.1001-5965.2022.0382
ZHANG Y T,LI Q Y,LIU S K. Tabular subordination relation extraction based on graph convolutional networks[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(4):1308-1315 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0382
Citation: ZHANG Y T,LI Q Y,LIU S K. Tabular subordination relation extraction based on graph convolutional networks[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(4):1308-1315 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0382

基于图卷积网络的表格隶属关系抽取

doi: 10.13700/j.bh.1001-5965.2022.0382
基金项目: 湖北省自然科学基金(2018CFC800)
详细信息
    通讯作者:

    E-mail:liusk@seu.edu.cn

  • 中图分类号: TP183

Tabular subordination relation extraction based on graph convolutional networks

Funds: Natural Science Foundation of Hubei Province (2018CFC800)
More Information
  • 摘要:

    针对表格识别与分析领域中表内单元格间隶属关系抽取问题,定义表格隶属关系抽取任务,结合表格与图结构的相似性,给出表内单元格的图表示方法,并提出一种基于图卷积网络(GCN)的表格隶属关系抽取模型。所提模型通过GCN对表内单元格及其邻近格进行特征的聚合,预测单元格间是否存在隶属关系,实现关系抽取。为验证所提模型的有效性,标注中文表单Rel-forms及英文表格Rel-SciTSR 这2个数据集。通过实验,在上述2类数据集及联合数据集上F1分数分别达到98.61%、96.55%、97.05%,验证所提模型在此2个数据集上的有效性,并分别分析文本内容、坐标信息、单元格属性及格间相对方向等不同因素对隶属关系抽取实验结果的影响。

     

  • 图 1  2类表格数据的隶属关系定义及抽取过程

    Figure 1.  Definition and extraction of subordination relation in two types of tabular data

    图 2  GCN的传播方式

    Figure 2.  Dissemination mode of GCN

    图 3  GCN工作流程

    Figure 3.  GCN flowchart

    图 4  本文模型

    Figure 4.  The proposed model

    图 5  Rel-SciTSR数据集样例

    Figure 5.  Sample images from dataset of Rel-SciTSR

    图 6  Rel-forms数据集样例

    Figure 6.  Sample images from dataset of Rel-forms

    图 7  正确率变化趋势

    Figure 7.  Change trend of accuracy

    图 8  正确率及损失变化趋势

    Figure 8.  Change trend of accuracy and loss

    表  1  文本特征关系抽取结果

    Table  1.   Result of relation extraction in text feature

    数据集 正确率/%
    Rel-SciTSR 86.46
    Rel-forms 91.76
    Rel-SciTSR+ Rel-forms 88.93
    下载: 导出CSV

    表  2  隶属关系抽取结果

    Table  2.   Result of subordination relation extraction

    特征 P R F1
    数据集① 数据集② 数据集③ 数据集① 数据集② 数据集③ 数据集① 数据集② 数据集③
    Po 97.51 93.59 95.05 95.19 93.96 95.56 96.34 93.77 95.30
    Po+Cl 98.16 95.88 96.93 97.90 95.65 96.67 98.03 95.76 96.80
    Po+Cl+Rd 98.82 96.49 97.18 98.40 96.61 96.93 98.61 96.55 97.05
     注:①论文表格数据集Rel-SciTSR;②表单类数据集Rel-forms;③联合数据集Rel-SciTSR+ Rel-forms。
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-05-18
  • 录用日期:  2022-08-12
  • 网络出版日期:  2022-09-14
  • 整期出版日期:  2024-04-29

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