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,...
Saved in:
主要作者: | SOH, Jerrold Tsin Howe |
---|---|
格式: | text |
語言: | English |
出版: |
Institutional Knowledge at Singapore Management University
2024
|
主題: | |
在線閱讀: | 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 |
標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
機構: | Singapore Management University |
語言: | English |
相似書籍
-
TOWARDS A GENERAL APPROACH FOR COMPUTER-ASSISTED ANALYSIS OF LEGAL DECISIONS: IN DOMAIN NAME DISPUTES, DOES THE PANELIST MATTER?
由: JERROLD SOH TSIN HOWE
出版: (2018) -
A network analysis of the Singapore court of appeal's citations to precedent
由: SOH, Jerrold Tsin Howe
出版: (2019) -
Legal topic classification: A comparative study of text classifiers on Singapore Supreme Court judgments
由: SOH, Jerrold Tsin Howe, et al.
出版: (2019) -
Towards a general framework for empirical legal analysis: In domain name disputes, do panelists matter?
由: SOH, Jerrold
出版: (2018) -
Advanced Fundamentals of Appellate Advocacy in a Moot Court
由: CHEN, Siyuan
出版: (2012)