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posted on 06.03.2020, 06:05 by Andrea Galassi, Kristian Kersting, Marco Lippi, Xiaoting Shao, Paolo Torroni

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.

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