CAIL2019-SCM: A Dataset of Similar Case Matching in Legal Domain

By Chaojun Xiao, Haoxiang Zhong, Zhipeng Guo, Cunchao Tu, Zhiyuan Liu, Maosong Sun, Tianyang Zhang, Xianpei Han, Zhen Hu, Heng Wang and 1 more. 2019

82 citations recorded by the source corpus.

In this paper, we introduce CAIL2019-SCM, Chinese AI and Law 2019 Similar Case Matching dataset. CAIL2019-SCM contains 8,964 triplets of cases published by the Supreme People's Court of China. CAIL2019-SCM focuses on detecting similar cases, and the participants are required to check which two cases are more similar in the triplets. There are 711 teams who participated in this year's competition, and the best team has reached a score of 71.88. We have also implemented several baselines to help researchers better understand this task. The dataset and more details can be found from this https URL.

Subfields: Artificial Intelligence, General Social Sciences, Political Science and International Relations, Natural Language Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

  1. Maosong Sun
  2. Zhiyuan Liu
  3. Chaojun Xiao
  4. Cunchao Tu
  5. Haoxiang Zhong
  6. Tianyang Zhang
  7. Yunfeng Liu
  8. Jianlin Su

In General Social Sciences

  1. Maosong Sun
  2. Cunchao Tu
  3. Zhiyuan Liu
  4. Tianyang Zhang
  5. Jianlin Su
  6. Haoxiang Zhong
  7. Chaojun Xiao

In Political Science and International Relations

  1. Maosong Sun
  2. Cunchao Tu
  3. Zhiyuan Liu
  4. Chaojun Xiao
  5. Tianyang Zhang
  6. Haoxiang Zhong

In Natural Language Processing

  1. Zhiyuan Liu
  2. Maosong Sun
  3. Yunfeng Liu
  4. Cunchao Tu
  5. Tianyang Zhang
  6. Jianlin Su
  7. Haoxiang Zhong
  8. Chaojun Xiao

Citations in the corpus