TY - GEN
T1 - Introducing Intelligence to the Semantic Analysis of Canadian Maritime Case Law
T2 - 17th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2022
AU - Abimbola, Bola
AU - Tan, Qing
AU - Villar, José Ramón
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023
Y1 - 2023
N2 - The use of machine learning and semantic analysis in case law is the new trend in modern society. Case Based Reasoning tools are being used to analyze texts in courts to make and predict judicial decisions which are designed to base the outcomes of current court proceedings from past and or learning from the mistakes to make better decisions. Because of the accuracy and speed of this technology, researchers in the justice system have introduced Machine Learning to optimize the Case-Based Researching approach. This paper presents a study aimed to critically analyze semantic analysis in the context of machine learning and proposes a case-based reasoning information retrieval system. It will explore how CBR-IR is being used to improve legal case law information retrieval. The study covers the importance of semantic analysis. The study will discuss limitations and recommendations for improvement and future research. The study recommends that it is necessary to conduct further research in semantic analysis and how they can be used to improve information retrieval of Canadian maritime case law.
AB - The use of machine learning and semantic analysis in case law is the new trend in modern society. Case Based Reasoning tools are being used to analyze texts in courts to make and predict judicial decisions which are designed to base the outcomes of current court proceedings from past and or learning from the mistakes to make better decisions. Because of the accuracy and speed of this technology, researchers in the justice system have introduced Machine Learning to optimize the Case-Based Researching approach. This paper presents a study aimed to critically analyze semantic analysis in the context of machine learning and proposes a case-based reasoning information retrieval system. It will explore how CBR-IR is being used to improve legal case law information retrieval. The study covers the importance of semantic analysis. The study will discuss limitations and recommendations for improvement and future research. The study recommends that it is necessary to conduct further research in semantic analysis and how they can be used to improve information retrieval of Canadian maritime case law.
UR - http://www.scopus.com/inward/record.url?scp=85141727027&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-18050-7_57
DO - 10.1007/978-3-031-18050-7_57
M3 - Published Conference contribution
AN - SCOPUS:85141727027
SN - 9783031180491
T3 - Lecture Notes in Networks and Systems
SP - 587
EP - 595
BT - 17th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2022, Proceedings
A2 - García Bringas, Pablo
A2 - Pérez García, Hilde
A2 - Martinez-de-Pison, Francisco Javier
A2 - Villar Flecha, José Ramón
A2 - Troncoso Lora, Alicia
A2 - de la Cal, Enrique A.
A2 - Herrero, Alvaro
A2 - Martínez Álvarez, Francisco
A2 - Psaila, Giuseppe
A2 - Quintián, Héctor
A2 - Corchado Rodriguez, Emilio S.
Y2 - 5 September 2022 through 7 September 2022
ER -