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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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Presentation for ICLP2020: Presentation
A. Galassi, K. Kersting, M. Lippi, X. Shao, and P. Torroni, "Neural-Symbolic Argumentation Mining: An Argument in Favor of Deep Learning and Reasoning," in Frontiers on Big Data, vol. 2, Jan. 2020. DOI: 10.3389/fdata.2019.00052