Summary of Artificial Intelligence (ai) in Legal Data Mining, by Aniket Deroy et al.
Artificial Intelligence (AI) in Legal Data Mining
by Aniket Deroy, Naksatra Kumar Bailung, Kripabandhu Ghosh, Saptarshi Ghosh, Abhijnan Chakraborty
First submitted to arxiv on: 23 May 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes the development of an ontology to organize legal information, making it more accessible for law practitioners and enabling downstream automation tasks. Building upon ancient Greek philosophers’ concept of word ontology, scientists today describe the relationships between concepts, data, and entities. The authors draw inspiration from a previously developed ontology on Indian court cases regarding intellectual property rights (IPR). This research paves the way for collaboration between computer experts and legal experts to shape the future of legal ontologies. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper helps organize unstructured legal data so lawyers and computers can work together better. It’s like creating a dictionary that connects words, ideas, and facts. Imagine having all the information about intellectual property rights in one place, easily understandable by both humans and machines. This is what the authors are trying to achieve with their ontology. |
