Publication
Comparing Unsupervised Algorithms to Construct Argument Graphs
Mirko Lenz; Lorik Dumani; Premtim Sahitaj
In: Joint Proceedings of Workshops, Tutorials and Doctoral Consortium. German Conference on Artificial Intelligence (KI-2022), located at 45th German Conference on Artificial Intelligence, Virtual Event, Trier, Germany, CEUR Workshop Proceedings, Vol. 3457, CEUR, 2022.
Abstract
Computational argumentation has gained considerable attention in recent years. Various areas have been addressed, such as extracting arguments from natural language texts into a structured form in order to store them in an argument base, determining stances for arguments with respect to topics, determination of inferences from statements, and much more. After so much progress has been made in the isolated tasks, in this paper we address the next level and aim to advance the automatic generation of argument graphs. To this end, we investigate various unsupervised methods for constructing the graphs and measure the performance with different metrics on three different datasets. Our implementation is publicly available on GitHub under the permissive MIT license.