Addressing the gap between current language models and key-term-based clustering (2023)
Cabral, Eric Macedo 
; Rezaeipourfarsangi, Sima ; Oliveira, Maria Cristina Ferreira de ; Milios, Evangelos E ; Minghim, Rosane
Source: Proceedings. Conference titles: ACM Symposium on Document Engineering - DocEng. Unidade: ICMC
Subjects: PROCESSAMENTO DE LINGUAGEM NATURAL, RECONHECIMENTO DE TEXTO, REDES NEURAIS, VISUALIZAÇÃO
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CABRAL, Eric Macedo et al. Addressing the gap between current language models and key-term-based clustering. 2023, Anais.. New York: ACM, 2023. Disponível em: https://doi.org/10.1145/3573128.3604900. Acesso em: 17 nov. 2024.APA
Cabral, E. M., Rezaeipourfarsangi, S., Oliveira, M. C. F. de, Milios, E. E., & Minghim, R. (2023). Addressing the gap between current language models and key-term-based clustering. In Proceedings. New York: ACM. doi:10.1145/3573128.3604900NLM
Cabral EM, Rezaeipourfarsangi S, Oliveira MCF de, Milios EE, Minghim R. Addressing the gap between current language models and key-term-based clustering [Internet]. Proceedings. 2023 ;[citado 2024 nov. 17 ] Available from: https://doi.org/10.1145/3573128.3604900Vancouver
Cabral EM, Rezaeipourfarsangi S, Oliveira MCF de, Milios EE, Minghim R. Addressing the gap between current language models and key-term-based clustering [Internet]. Proceedings. 2023 ;[citado 2024 nov. 17 ] Available from: https://doi.org/10.1145/3573128.3604900
