AUTHOR=Galassi Andrea , Kersting Kristian , Lippi Marco , Shao Xiaoting , Torroni Paolo TITLE=Neural-Symbolic Argumentation Mining: An Argument in Favor of Deep Learning and Reasoning JOURNAL=Frontiers in Big Data VOLUME=2 YEAR=2020 URL=https://www.frontiersin.org/journals/big-data/articles/10.3389/fdata.2019.00052 DOI=10.3389/fdata.2019.00052 ISSN=2624-909X ABSTRACT=

Deep learning is bringing remarkable contributions to the field of argumentation mining, but the existing approaches still need to fill the gap toward performing advanced reasoning tasks. In this position paper, we posit that neural-symbolic and statistical relational learning could play a crucial role in the integration of symbolic and sub-symbolic methods to achieve this goal.