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.

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. (Intervento presentato al convegno 31st International Joint Conference on Artificial Intelligence, IJCAI 2022 tenutosi a Messe Wien, aut nel 2022).

AMICA: An Argumentative Search Engine for COVID-19 Literature

Lippi M.;Galassi A.;Ruggeri F.;
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.
2022
31st International Joint Conference on Artificial Intelligence, IJCAI 2022
Messe Wien, aut
2022
5932
5935
Lippi, M.; Antici, F.; Brambilla, G.; Cisbani, E.; Galassi, A.; Giansanti, D.; Magurano, F.; Rosi, A.; Ruggeri, F.; Torroni, P.
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. (Intervento presentato al convegno 31st International Joint Conference on Artificial Intelligence, IJCAI 2022 tenutosi a Messe Wien, aut nel 2022).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1308990
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