Benchmarking Session-based and Session-aware Recommender Systems for Jusbrasil

  • Marcos Aurélio Domingues UEM / UFAM / Jusbrasil
  • Edleno Silva de Moura UFAM / Jusbrasil
  • Leandro Balby Marinho UFCG
  • Altigran da Silva UFAM

Resumo


In this paper, we present a benchmark of several session-based, session-based with reminders and session-aware recommender systems that can be used to improve legal document recommendation in Jusbrasil, the largest legal search engine in Brazil. We focus this benchmark on the logged users, and the results show that some recommender systems can achieve gains of accuracy of around 19% with respect to the current recommender system adopted by Jusbrasil.
Palavras-chave: legal document recommendation, session-based recommender systems, reminders, session-aware recommender systems

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Publicado
07/11/2022
DOMINGUES, Marcos Aurélio; MOURA, Edleno Silva de; MARINHO, Leandro Balby; SILVA, Altigran da. Benchmarking Session-based and Session-aware Recommender Systems for Jusbrasil. In: WEBMEDIA IN PRACTICE - SIMPÓSIO BRASILEIRO DE SISTEMAS MULTIMÍDIA E WEB (WEBMEDIA), 28. , 2022, Curitiba. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2022 . p. 145-148. ISSN 2596-1683. DOI: https://doi.org/10.5753/webmedia_estendido.2022.WiP02.