/HMN

Source code for SIGIR 2019 paper "Hierarchical Matching Network for Crime Classification"

Primary LanguagePython

HMM

Source code for SIGIR 2019 paper "Hierarchical Matching Network for Crime Classification"

Dependecies

  • tqdm==4.31.1
  • numpy==1.16.3
  • scikit-learn==0.20.3
  • jieba==0.39
  • torch==0.4.1
  • torchtext==0.3.1

Dataset

We conduct our empirical experiments on two real-world legal datasets:

  • CAIL 2018: contains criminal cases published by the Supreme People’s Court. Each case consists of two parts, i.e., fact description and corresponding judgment result (including laws, articles, and charges.
  • DPAM: comprises 40,256 criminal cases. These data are crawled from China Judgment Online2 and span from Jan.2016 to June. 2016.
Example of Dataset
{
  "text_len": 16,
  "laws": [234],
  "textIds": [2935,10,3,330,16,406,2935,1802,2,272,4328,1064,877,818,272,5455],
  "parent_class": ["侵犯公民人身"]
}

each instance contains four parts:

  • text_len: the length of fact descriptions
  • parent class: parent class
  • laws: sub class
  • textIds: the fact descriptions transformed from text to id

Usage

Reproducing the results reported in our paper, please run the code as follows:

python run.py

Citation

For more information, please refer to our paper. If our work is helpful to you, please kindly cite our paper as:

@inproceedings{DBLP:conf/sigir/WangFNYZG19,
  author    = {Pengfei Wang and
               Yu Fan and
               Shuzi Niu and
               Ze Yang and
               Yongfeng Zhang and
               Jiafeng Guo},
  editor    = {Benjamin Piwowarski and
               Max Chevalier and
               {\'{E}}ric Gaussier and
               Yoelle Maarek and
               Jian{-}Yun Nie and
               Falk Scholer},
  title     = {Hierarchical Matching Network for Crime Classification},
  booktitle = {Proceedings of the 42nd International {ACM} {SIGIR} Conference on
               Research and Development in Information Retrieval, {SIGIR} 2019, Paris,
               France, July 21-25, 2019},
  pages     = {325--334},
  publisher = {{ACM}},
  year      = {2019},
  url       = {https://doi.org/10.1145/3331184.3331223},
  doi       = {10.1145/3331184.3331223},
  timestamp = {Sun, 21 Jul 2019 17:52:47 +0200},
  biburl    = {https://dblp.org/rec/conf/sigir/WangFNYZG19.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

Reference