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Legal Search in Case Law and Statute Law
Julien Rossi, Evangelos Kanoulas
83 - 92
10.3233/FAIA190309
Research Article
Frontiers in Artificial Intelligence and Applications
Volume 322: Legal Knowledge and Information Systems
Abstract

In this work we describe a method to identify document pairwise relevance in the context of a typical legal document collection: limited resources, long queries and long documents. We review the usage of generalized language models, including supervised and unsupervised learning. We observe how our method, while using text summaries, overperforms existing baselines based on full text, and motivate potential improvement directions for future work.

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