Discovering significant topics from legal decisions with selective inference
We propose and evaluate an automated pipeline for discovering significant topics from legal decision texts by passing features synthesized with topic models through penalized regressions and post-selection significance tests. The method identifies case topics significantly correlated with outcomes,...
محفوظ في:
المؤلف الرئيسي: | |
---|---|
التنسيق: | text |
اللغة: | English |
منشور في: |
Institutional Knowledge at Singapore Management University
2024
|
الموضوعات: | |
الوصول للمادة أونلاين: | https://ink.library.smu.edu.sg/sol_research/4433 https://ink.library.smu.edu.sg/context/sol_research/article/6391/viewcontent/Discovering_significant_topics_from_legal_decisions_with_selective_inference_pvoa_cc_by.pdf |
الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
المؤسسة: | Singapore Management University |
اللغة: | English |
كن أول من يترك تعليقا!