What works and what does not: Classifier and feature analysis for argument mining

WS 2017 Ahmet AkerAlfred SliwaYuan MaRuishen LuiNiravkumar BoradSeyedeh ZiyaeiMina Ghobadi

This paper offers a comparative analysis of the performance of different supervised machine learning methods and feature sets on argument mining tasks. Specifically, we address the tasks of extracting argumentative segments from texts and predicting the structure between those segments... (read more)

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