Journal of Computer Applications ›› 2022, Vol. 42 ›› Issue (1): 78-86.DOI: 10.11772/j.issn.1001-9081.2021020267

• Artificial intelligence • Previous Articles     Next Articles

Automatic construction method of knowledge forest for electronic case files

Yincen QU, Yinliang ZHAO(), Chongchong JIU, Shuo LIU   

  1. School of Computer Science and Technology,Xi’an Jiaotong University,Xi’an Shaanxi 710049,China
  • Received:2021-02-22 Revised:2021-05-19 Accepted:2021-05-24 Online:2021-06-08 Published:2022-01-10
  • Contact: Yinliang ZHAO
  • About author:QU Yincen, born in 1996, M. S. candidate. Her research interests include natural language processing, knowledge graph.
    ZHAO Yinliang, born in 1960, Ph. D., professor. His research interests include parallel computing, machine learning.
    JIU Chongchong, born in 1997, M. S. candidate. His research interests include natural language processing.
    LIU Shuo, born in 1998, M. S. candidate. His research interests include natural language processing.
  • Supported by:
    National Key Research and Development Program of China(2018YFC0832300)


屈垠岑, 赵银亮(), 酒冲冲, 刘硕   

  1. 西安交通大学 计算机科学与技术学院,西安 710049
  • 通讯作者: 赵银亮
  • 作者简介:屈垠岑(1996—),女,四川达州人,硕士研究生,主要研究方向:自然语言处理、知识图谱
  • 基金资助:


The read of various contents of case files suffers from information overload and knowledge disorientation. To solve this problem, an automatic construction method of knowledge forest for electronic case files was proposed with the topic facet trees and the cognitive relationships between topics as the intellectualized representation of the case files. Firstly, different types of files were classified and divided into multiple fragments of single topic by the fragmentation preprocessing of the case files. Then, different information extraction methods were adopted for different fragments, and knowledge fusion was used to merge the synonymous information. After that, the topic faceted trees were constructed by combining the ontology structures and rules and the topic relationships were extracted. Finally, the topic faceted trees and the topic relationships constructed by the knowledge forest were stored in the database to realize the visualization of the knowledge forest. Experimental results show that the proposed method can display the case file information completely and accurately, organize scattered knowledge fragments together with complex case file topics, making it possible to achieve the reading file goal by selecting some case file topics and a small number of case file fragments, and alleviate the burden of complete browsing case file contents to realize the file reading task.

Key words: electronic case file, knowledge forest, information overload, knowledge disorientation, reading file



关键词: 随案电子卷宗, 知识森林, 信息过载, 知识迷航, 阅卷

CLC Number: