2017-CCF-BDCI-AIJudge and BDCI2017-MingLue

These are **competitors**: both are independent submissions to the same 2017 CCF BDCI legal case classification competition, implementing different approaches to the identical task of AI-based judicial case categorization.

2017-CCF-BDCI-AIJudge
49
Emerging
BDCI2017-MingLue
39
Emerging
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 23/25
Maintenance 0/25
Adoption 10/25
Maturity 8/25
Community 21/25
Stars: 185
Forks: 79
Downloads: —
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stars: 121
Forks: 38
Downloads: —
Commits (30d): 0
Language: Python
License: —
Stale 6m No Package No Dependents
No License Stale 6m No Package No Dependents

About 2017-CCF-BDCI-AIJudge

ShawnyXiao/2017-CCF-BDCI-AIJudge

2017-CCF-BDCI-让AI当法官(初赛)：7th/415 (Top 1.68%)

This project helps legal professionals or researchers quickly estimate fine categories for legal cases based on their textual descriptions. It takes raw case text as input and processes it to extract key information and linguistic patterns. The output is a predicted fine category, assisting in case assessment or legal research.

legal-tech case-prediction fine-assessment legal-document-analysis judicial-analytics

About BDCI2017-MingLue

llhthinker/BDCI2017-MingLue

BDCI2017-让AI当法官，决赛第四（4/415）https://www.datafountain.cn/competitions/277/details

This project helps legal professionals automate the classification of legal case documents. It takes raw legal texts as input and outputs predictions for the appropriate penalty level (e.g., fine amounts) and the specific legal articles or statutes that apply to the case. Legal researchers, paralegals, or judges dealing with a high volume of legal documents would find this tool useful.

legal-tech case-classification judicial-automation penalty-prediction statute-identification

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