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 / Marco Lippi and Francesco Antici and Gianfranco Brambilla and Evaristo Cisbani and Andrea Galassi and Daniele Giansanti and Fabio Magurano and Antonella Rosi and Federico Ruggeri and Paolo Torroni. - ELETTRONICO. - (2022), pp. 5932-5935. (Intervento presentato al convegno International Joint Conference on Artificial Intelligence tenutosi a Vienna nel 23/07/2022) [10.24963/ijcai.2022/857].

AMICA: An Argumentative Search Engine for COVID-19 Literature

Marco Lippi
;
Francesco Antici;Gianfranco Brambilla;Andrea Galassi;Federico Ruggeri;Paolo Torroni
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
Proceedings of the Thirty-First International Joint Conference onArtificial Intelligence {IJCAI-22}
5932
5935
AMICA: An Argumentative Search Engine for COVID-19 Literature / Marco Lippi and Francesco Antici and Gianfranco Brambilla and Evaristo Cisbani and Andrea Galassi and Daniele Giansanti and Fabio Magurano and Antonella Rosi and Federico Ruggeri and Paolo Torroni. - ELETTRONICO. - (2022), pp. 5932-5935. (Intervento presentato al convegno International Joint Conference on Artificial Intelligence tenutosi a Vienna nel 23/07/2022) [10.24963/ijcai.2022/857].
Marco Lippi and Francesco Antici and Gianfranco Brambilla and Evaristo Cisbani and Andrea Galassi and Daniele Giansanti and Fabio Magurano and Antonella Rosi and Federico Ruggeri and Paolo Torroni
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/890914
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