AI Bibliography
AI Bibliography |
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Galassi, A., Kersting, K., Lippi, M., Shao, X., & Torroni, P. (2020). Neural-symbolic argumentation mining: An argument in favor of deep learning and reasoning. Frontiers in big Data, 2, 52. |
| Resource type: Journal Article BibTeX citation key: Galassi2020 View all bibliographic details  |
Categories: Artificial Intelligence, Biological Science, Cognitive Science, Complexity Science, Computer Science, Decision Theory, General, Neuroscience Subcategories: Augmented cognition, Decision making, Deep learning, Human decisionmaking, Machine learning, Neurosymbolic Creators: Galassi, Kersting, Lippi, Shao, Torroni Publisher: Collection: Frontiers in big Data |
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| Abstract |
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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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