面向机器学习的流式文档逻辑结构标注方法研究

针对采用机器学习方法识别流式文档结构时语料库稀少、语料标注复杂的问题,该文在研究文档的逻辑结构和编辑语义特征的基础上,确立流式文档逻辑结构标注体系,并提出一种三段式的半自动文档逻辑结构标注方法: 第一阶段通过机助人工实现文档元数据的分离式标注,第二阶段自动重建逻辑结构,第三阶段自动填充特征向量。实验结果表明,该文提出的文档逻辑结构标注方法能够节省人工成本、提高机器学习算法对文档结构识别的准确率与召回率,F值达到97.5%。

Annotation of Logical Structure in Re-flowable Document for Machine Learning

To construct the corpus of logical structure in re-flowable documents for machine learning, this paper proposed a three-stage semi-automatic annotation method based on the logical structure features and editing semantic features. In the first stage, document metadata is identified and annotated aided by the machine; in the second stage, the logical structure of the document is reconstructed automatically; finally, the feature vectors are automatically produced in the third stage. The experimental result shows that the proposed method can reduce manual costs, and the document corpus achieved can improve the accuracy of document structure recognition using machine learning algorithm up to 97.5% F-score.