Information retrieval and categorization in legal: a systematic mapping of the literature
DOI:
https://doi.org/10.62059/LatArXiv.preprints.153Keywords:
Artificial intelligence, Civil law, Legal information retrieval, Automatic query expansion, Text classification algorithmsAbstract
Context: In the digital age, our lives are becoming more dynamic and the development of advanced technologies is changing the format of civil law relations. Today, the norm for legal professionals is the use of software that allows the acceleration of daily processes through the use of artificial intelligence technologies. Legal information retrieval (LIR) is an important and challenging field of artificial intelligence that deals with searching and analyzing regulations and legal texts relevant to a user's information need.
Objectives: We will identify and synthesize the main approaches, trends and advances in the application of artificial intelligence in Legal Information Retrieval. Through the review of recent research, we aim to establish a clear overview of the strategies used, the methodologies employed and the emerging focus areas.
Methods: To achieve these objectives, an exhaustive search was carried out in academic databases and repositories, selecting relevant studies published in the last twelve years. Initially, we had 2307 articles, which after applying inclusion/exclusion criteria were reduced to 354 technical articles, and after applying a final filter, 18 articles remained as a final group. To reach this final number of articles, in addition to the inclusion-exclusion criteria, the articles were subjected to a process of analysis and classification according to topics, methods and results.
Results: They reveal a growing attention to the application of artificial intelligence techniques in Legal Information Retrieval. Approaches were identified that address the understanding and improvement of the relevance of search results, as well as the automation of legal processes. In addition, a progressive adoption of natural language processing and machine learning techniques is observed.
Conclusions: A panoramic view of the intersection between artificial intelligence and Legal Information Retrieval is provided. The results underline the relevance and potential of AI techniques in the legal field, while highlighting the need for further research and integrated approaches to address the specific challenges of legal IR in a technologically dynamic world.
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