Judicial Case Determination Methods Based on Event Tuple

Guozi Sun, Zhi Li, Huakang Li*, Xiangyu Tang

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

1 Citation (Scopus)


Judges have to consider the motives of the defendant’s side and the sequence of actions of all judicial subjects in the process of sentencing. Text analysis methods based on word vectors and deep neural networks, although they give statistically better classification results, cannot explain the causality of the actions of various subjects in the case logic. In this paper, we propose an event semantic mining algorithm that attempts to make judicial decisions from the causal logic. The method identifies the behavioral subjects in judicial documents through an entity extraction algorithm and extracts the subjects’ core behavior and motivation to achieve the construction of the underlying event tuple. By calculating the event tuple weights between different categories of cases, combined with a heap sorting algorithm, an event semantic tree is constructed for each case. Finally, a set of event tuple coding algorithm is designed to input the event semantic tree into the deep forest algorithm for inference. The experimental results show that the proposed event semantic tree construction method and event tuple coding method not only have a good case decision accuracy. It also has a good logical explanation.

Original languageEnglish
Title of host publicationWireless Algorithms, Systems, and Applications - 16th International Conference, WASA 2021, Proceedings
EditorsZhe Liu, Fan Wu, Sajal K. Das
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages13
ISBN (Print)9783030859275
Publication statusPublished - 2021
Externally publishedYes
Event16th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2021 - Nanjing, China
Duration: 25 Jun 202127 Jun 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12937 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference16th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2021


  • Case logic
  • Deep forest
  • Event tuple
  • Judicial text
  • Semantic tree

Cite this