Graduate School and Research Center in Digital Sciences

Explainable fact checking with probabilistic answer set programming

Papotti, Paolo

GFAIH 2019, Invited Talk at Global Forum on AI for Humanity, 28-30 October 2019, Paris, France

A challenge in fact checking is the ability to provide explanations for the claim validation. We present a computational method that uses reference information to verify claims and explain its assessments. Our solution exploits existing formal representation of knowledge to generate interpretable explanations for the fact checking decisions.

Bibtex

Title:Explainable fact checking with probabilistic answer set programming
Type:Talk
Language:English
City:Paris
Country:FRANCE
Date:
Department:Data Science
Eurecom ref:6047
Copyright: © EURECOM. Personal use of this material is permitted. The definitive version of this paper was published in GFAIH 2019, Invited Talk at Global Forum on AI for Humanity, 28-30 October 2019, Paris, France and is available at :
Bibtex: @talk{EURECOM+6047, year = {2019}, title = {{E}xplainable fact checking with probabilistic answer set programming}, author = {{P}apotti, {P}aolo}, number = {EURECOM+6047}, month = {10}, institution = {Eurecom} address = {{P}aris, {FRANCE}}, url = {http://www.eurecom.fr/publication/6047} }
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