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Article
August 2024
Intermediate Hidden Layers for Legal Case Retrieval Representation
Database and Expert Systems ApplicationsPages 306–319https://doi.org/10.1007/978-3-031-68312-1_23
Abstract
In the world of intelligent legal systems, the process of finding relevant case documents related to a specific legal matter is known as legal case retrieval. While Pretrained Language Models (PLMs) have demonstrated impressive performance in ...
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Article
March 2024
Enhancing Legal Named Entity Recognition Using RoBERTa-GCN with CRF: A Nuanced Approach for Fine-Grained Entity Recognition
- Arihant Jain,
- Raksha Sharma
Advances in Information RetrievalPages 261–267https://doi.org/10.1007/978-3-031-56063-7_17
Abstract
Accurate identification of named entities is pivotal for the advancement of sophisticated legal Artificial Intelligence (AI) applications. However, the legal domain presents distinct challenges due to the presence of fine-grained, domain-specific ...
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research-article
December 2018
Deep Learning for Named-Entity Linking with Transfer Learning for Legal Documents
AICCC '18: Proceedings of the 2018 Artificial Intelligence and Cloud Computing ConferencePages 23–28https://doi.org/10.1145/3299819.3299846

In the legal domain it is important to differentiate between words in general, and afterwards to link the occurrences of the same entities. The topic to solve these challenges is called Named-Entity Linking (NEL). Current supervised neural networks ...
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Article
June 2006
Improving Legal Document Summarization Using Graphical Models
Proceedings of the 2006 conference on Legal Knowledge and Information Systems: JURIX 2006: The Nineteenth Annual ConferencePages 51–60

In this paper, we propose a novel idea for applying probabilistic graphical models for automatic text summarization task related to a legal domain. Identification of rhetorical roles present in the sentences of a legal document is the important text ...
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