Publikationen

Disclaimer:

IEEE Copyright Notice

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

ACM Copyright Notice

These are the authors' versions of the work. The copyright is with ACM. They are posted here by permission of ACM for your personal use. Not for redistribution. See individual publication details for information on the publication of the definitive versions.

Springer-Verlag LNCS Copyright Notice

The copyright of these contributions has been transferred to Springer-Verlag Berlin Heidelberg New York. The copyright transfer covers the exclusive right to reproduce and distribute the contribution, including reprints, translations, photographic reproductions, microform, electronic form (offline, online), or any other reproductions of similar nature. Online available from Springer-Verlag LNCS series.

Work that appeared before the 1st of September 2003 was published while the authors were with the Lehrstuhl Praktische Informatik IV at the University of Mannheim.

Structure or Content? Towards Assessing Argument Relevance

Author(s): Marc Feger, Jan Steimann, Christian Meter
Title: Structure or Content? Towards Assessing Argument Relevance
Published: In Proceedings, September 2020
Keyword(s): argument relevance, pagerank
Abstract: In this paper, we provide a detailed analysis of PageRank to determine the relevance of arguments along with content- and knowledge-based methods from the field of natural language processing. We do not only show how the cross-linking of arguments is only slightly involved in the recognition of relevance, we rather show how basic common knowledge and reader-involving methods outperform the purely structure-related PageRank. The methods we propose are based on the latest research and correlate strongly with human awareness regarding the relevance of arguments. Altogether, we show that PageRank does not fully capture the relevance of arguments and must be extended by a contextual level in order to take concepts of natural language into account at the web level, as they are unavoidably involved in argumentation.
Bib entry: [BibTeX]
Download: [PDF] [XML] [YML]
Verantwortlich für den Inhalt: