Benchmarking Session-based and Session-aware Recommender Systems for Jusbrasil
Marcos Aurélio Domingues, Edleno Silva de Moura, Leandro Balby Marinho, Altigran Soares da Silva · 2022
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.