Abstract
This is an extension from a selected paper from JSAI2019. This paper proposes an approach that aims to extract the discussion structure from large-scale text-based online discussions. The ultimate goal is to develop an automated facilitation agent that is able to extract discussion structures from large-scale online discussions. Towards this end, we adopt the issue-based information system (IBIS), as a suitable format for structuring online discussions. In this context, we model the task of extracting an IBIS structure as it consists of node extraction and link extraction. Towards this end, a deep neural network based approach is employed in order to perform these two extraction subtasks. In order to evaluate the proposed approach, a set of experiments has been conducted on the data collected from the discussions in the online discussion support system called D-Agree. The experimental results show that the proposed approach is efficient for extracting online discussion structures.
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This work was supported by JST CREST Grant Number JPMJCR15E1, Japan.
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Suzuki, S. et al. (2020). Extraction of Online Discussion Structures for Automated Facilitation Agent. In: Ohsawa, Y., et al. Advances in Artificial Intelligence. JSAI 2019. Advances in Intelligent Systems and Computing, vol 1128. Springer, Cham. https://doi.org/10.1007/978-3-030-39878-1_14
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DOI: https://doi.org/10.1007/978-3-030-39878-1_14
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