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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM63270
Volume:
10 |
5 |
May 2026
Pages:
1-3
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Computer Science
Malnad College of Engineering
Department of Computer Science
Malnad College of Engineering
Department of Computer Science
Malnad College of Engineering
Department of Computer Science
Malnad College of Engineering
Department of Computer Science
Malnad College of Engineering
Legal and judicial organizations generate huge amounts of information through court proceedings, legal records, crime reports, and case documents. Since most legal information is maintained in textual form, analyzing and interpreting the data becomes difficult, especially when handling large numbers of cases. Traditional systems often require manual analysis, which increases complexity and consumes significant time. The proposed Legal Case Analytics and Visualization System focuses on simplifying legal information using visualization and ana-lytical techniques. The platform transforms legal datasets into interactive visual formats such as graphs, dashboards, timelines, heatmaps, and relationship maps. These visual representations help users identify legal trends, case connections, and crime-related patterns more efficiently. The system combines visual-ization methods with analytical processing to improve legal data interpretation and accessibility. It can support legal professionals, students, researchers, and judicial authorities by providing a clearer understanding of complex legal datasets. The project also highlights the importance of visual analytics in improving legal research, analytical reasoning, and decision-making within modern judicial systems.
KEYWORDS
The proposed Legal Case Analytics and Visualization Sys-tem provides an effective approach for improving legal infor-mation analysis using visualization and analytical techniques. By transforming complex legal datasets into interactive vi-sual representations, the system simplifies interpretation and improves accessibility for users. The platform supports legal professionals, students, and researchers in understanding legal trends, case relationships, and analytical insights more effi-ciently. It also demonstrates the importance of visualization technologies in modern legal systems and highlights the role of analytical tools in improving legal research and decision-making processes.
[1] M. Sugihara, S. Takakai, K. Takamatsu, and K. Misue, “Contribution of Data Visualization to Decision-Making: A Classification of Data Visu-alization Research Based on the Characteristics of Decision Problems,” IEEE Pacific Visualization Conference, 2025. [2] Y. Sailaja et al., “Implemented Data Mining Methods for Extracting Patterns and Visualizations from Large Data Sets,” IEEE ICEC2NT Conference, 2025. [3] S. McLachlan and L. C. Webley, “Visualisation of Law and Legal Process: An Opportunity Missed,” Birmingham Law School Research Publication, 2021. [4] N. Lettieri and D. Malandrino, “Cartographies of the Legal World: Rise and Challenges of Visual Legal Analytics,” International Conference on Information Visualisation, IEEE, 2018. [5] G. Garcia-Zanabria et al., “CriPAV: Street-Level Crime Patterns Analysis and Visualization,” IEEE Transactions on Visualization and Computer Graphics, vol. 28, no. 12, 2022. [6] S. Yan and J. Jones, “Ensuring Compliance in Digital Transformation: Developing and Validating the Data Management Stage Model,” IEEE Transactions on Engineering Management, vol. 73, pp. 1402–1408, 2026. [7] L. E. Resck, J. R. Ponciano, L. G. Nonato, and J. Poco, “LegalVis: Exploring and Inferring Precedent Citations in Legal Documents,” arXiv preprint arXiv:2203.02001, 2022.
Publication Date
5/18/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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