Data di Pubblicazione:
2022
Citazione:
AMICA: An Argumentative Search Engine for COVID-19 Literature / Lippi, M.; Antici, F.; Brambilla, G.; Cisbani, E.; Galassi, A.; Giansanti, D.; Magurano, F.; Rosi, A.; Ruggeri, F.; Torroni, P.. - In: IJCAI. - ISSN 1045-0823. - (2022), pp. 5932-5935. ( 31st International Joint Conference on Artificial Intelligence, IJCAI 2022 Vienna, AUSTRIA JUL 23-29, 2022).
Abstract:
AMICA is an argument mining-based search engine, specifically designed for the analysis of scientific literature related to COVID-19. AMICA retrieves scientific papers based on matching keywords and ranks the results based on the papers' argumentative content. An experimental evaluation conducted on a case study in collaboration with the Italian National Institute of Health shows that the AMICA ranking agrees with expert opinion, as well as, importantly, with the impartial quality criteria indicated by Cochrane Systematic Reviews.
Tipologia CRIS:
Relazione in Atti di Convegno
Elenco autori:
Lippi, M.; Antici, F.; Brambilla, G.; Cisbani, E.; Galassi, A.; Giansanti, D.; Magurano, F.; Rosi, A.; Ruggeri, F.; Torroni, P.
Link alla scheda completa:
Titolo del libro:
IJCAI International Joint Conference on Artificial Intelligence
Pubblicato in: