short-paper

Hier-SPCNet: A Legal Statute Hierarchy-based Heterogeneous Network for Computing Legal Case Document Similarity

Authors:

Paheli Bhattacharya,

Kripabandhu Ghosh,

Arindam Pal,

Saptarshi GhoshAuthors Info & Claims

SIGIR '20: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval

Pages 1657 - 1660

https://doi.org/10.1145/3397271.3401191

Published: 25 July 2020 Publication History

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Abstract

Computing similarity between two legal case documents is a challenging task, for which text-based and network-based measures have been proposed in literature. All prior network-based similarity methods considered a precedent citation network among case documents only (PCNet). However, this approach misses an important source of legal knowledge - the hierarchy of legal statutes that are applicable in a given legal jurisdiction (e.g., country). We propose to augment the PCNet with the hierarchy of legal statutes, to form a heterogeneous network Hier-SPCNet. Experiments over a set of Indian Supreme Court case documents show that Hier-SPCNet enables significantly better document similarity estimation, as compared to existing approaches using PCNet. We also show that the proposed network-based method can complement text-based measures for better estimation of legal document similarity.

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Hier-SPCNet: A Legal Statute Hierarchy-based Heterogeneous Network for Computing Legal Case Document Similarity\r\nComputing similarity between two legal case documents is a challenging task, for which text-based and network-based measures have been proposed in literature. All prior network-based similarity methods considered a precedent citation network among case documents only (PCNet). However, this approach misses an important source of legal knowledge - the hierarchy of legal statutes that are applicable in a given legal jurisdiction (e.g., country). We propose to augment the PCNet with the hierarchy of legal statutes, to form a heterogeneous network Hier-SPCNet. Experiments over a set of Indian Supreme Court case documents show that Hier- SPCNet enables significantly better document similarity estimation, as compared to existing approaches using PCNet. We also show that the proposed network-based method can complement text-based measures for better estimation of legal document similarity.

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Cited By

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Zhao JGuan ZZhao WJiang YHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)Enhancing Criminal Case Matching through Diverse Legal FactorsProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657960(2379-2383)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3657960
Sun ZYu WSi ZXu JDong ZChen XXu HWen J(2024)Explainable Legal Case Matching via Graph Optimal TransportIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2023.3321935(1-14)Online publication date: 2024
https://doi.org/10.1109/TKDE.2023.3321935
Ghosh TKumar S(2024)Evaluating Transformer Models for Legal Judgement Prediction: A Comparative Study2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT61001.2024.10725043(1-4)Online publication date: 24-Jun-2024
https://doi.org/10.1109/ICCCNT61001.2024.10725043
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Index Terms

Hier-SPCNet: A Legal Statute Hierarchy-based Heterogeneous Network for Computing Legal Case Document Similarity
1. Applied computing
  1. Law, social and behavioral sciences
    1. Law
2. Information systems
  1. Information retrieval

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SIGIR '20: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval

July 2020

2548 pages

ISBN:9781450380164

DOI:10.1145/3397271

General Chairs:
Jimmy Huang
York University, Canada
,
Yi Chang
Jilin University, China
,
Xueqi Cheng
Chinese Academy of Sciences, China
,
Program Chairs:
Jaap Kamps
University of Amsterdam, Netherlands
,
Vanessa Murdock
Amazon, U.S.A.
,
Ji-Rong Wen
Renmin University of China, China
,
Yiqun Liu
Tsinghua University, China

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Published: 25 July 2020

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SIGIR '20: The 43rd International ACM SIGIR conference on research and development in Information Retrieval

July 25 - 30, 2020

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Zhao JGuan ZZhao WJiang YHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)Enhancing Criminal Case Matching through Diverse Legal FactorsProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657960(2379-2383)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3657960
Sun ZYu WSi ZXu JDong ZChen XXu HWen J(2024)Explainable Legal Case Matching via Graph Optimal TransportIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2023.3321935(1-14)Online publication date: 2024
https://doi.org/10.1109/TKDE.2023.3321935
Ghosh TKumar S(2024)Evaluating Transformer Models for Legal Judgement Prediction: A Comparative Study2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT61001.2024.10725043(1-4)Online publication date: 24-Jun-2024
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Liu YWu YZhang YSun CLu WWu FKuang KChen HDuh WHuang HKato MMothe JPoblete B(2023)ML-LJP: Multi-Law Aware Legal Judgment PredictionProceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3539618.3591731(1023-1034)Online publication date: 19-Jul-2023
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Measuring Similarity among Legal Court Case Documents

Legal case document similarity: You need both network and text

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