Hostname: page-component-76fb5796d-qxdb6 Total loading time: 0 Render date: 2024-04-26T14:55:35.668Z Has data issue: false hasContentIssue false

Representing and classifying arguments on the Semantic Web

Published online by Cambridge University Press:  01 December 2011

Iyad Rahwan*
Affiliation:
Computing & Information Science, Masdar Institute of Science and Technology, Abu Dhabi, UAE Technology & Development Program, Massachusetts Institute of Technology, Cambridge, MA, USA;e-mail: irahwan@masdar.ac.ae
Bita Banihashemi*
Affiliation:
Faculty of Engineering & IT, British University in Dubai, Dubai, UAE;e-mail: bita@emirates.net.ae
Chris Reed*
Affiliation:
School of Computing, University of Dundee, Dundee, UK;e-mail: creed@computing.dundee.ac.uk
Douglas Walton*
Affiliation:
Centre for Research in Reasoning, Argumentation & Rhetoric, University of Windsor, Windsor, Ontario, Canada;e-mail: dwalton@uwindsor.ca
Sherief Abdallah*
Affiliation:
Faculty of Engineering & IT, British University in Dubai, Dubai, UAE;e-mail: bita@emirates.net.ae School of Informatics, University of Edinburgh, Edinburgh, UK;e-mail: sherief.abdallah@buid.ac.ae

Abstract

Until recently, little work has been dedicated to the representation and interchange of informal, semi-structured arguments of the type found in natural language prose and dialogue. To redress this, the research community recently initiated work towards an Argument Interchange Format (AIF). The AIF aims to facilitate the exchange of semi-structured arguments among different argument analysis and argumentation-support tools. In this paper, we present a Description Logic ontology for annotating arguments, based on a new reification of the AIF and founded in Walton's theory of argumentation schemes. We demonstrate how this ontology enables a new kind of automated reasoning over argument structures, which complements classical reasoning about argument acceptability. In particular, Web Ontology Language reasoning enables significantly enhanced querying of arguments through automatic scheme classifications, instance classification, inference of indirect support in chained argument structures, and inference of critical questions. We present the implementation of a pilot Web-based system for authoring and querying argument structures using the proposed ontology.

Type
Articles
Copyright
Copyright © Cambridge University Press 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Atkinson, K., Bench-Capon, T. J. M., McBurney, P. 2006. PARMENIDES: facilitating deliberation in democracies. Artificial Intelligence and Law 14(4), 261275.CrossRefGoogle Scholar
Baader, F., Calvanese, D., McGuinness, D., Nardi, D., Patel-Schneider, P. (eds). 2003. The Description Logic Handbook. Cambridge University Press.Google Scholar
Baroni, P., Giacomin, M. 2007. On principle-based evaluation of extension-based argumentation semantics. Artificial Intelligence 171(10–15), 675700.CrossRefGoogle Scholar
Brickley, D., Guha, R. V. 2004. RDF Vocabulary Description Language 1.0: RDF Schema. W3C Recommendation REC-rdf-schema-20040210, World Wide Web Consortium (W3C). http://www.w3.org/TR/rdf-schema/Google Scholar
Chesňevar, C. I., McGinnis, J., Modgil, S., Rahwan, I., Reed, C., Simari, G., South, M., Vreeswijk, G., Willmott, S. 2006. Towards an Argument Interchange Format. The Knowledge Engineering Review 21(4), 293316.CrossRefGoogle Scholar
Farnham, S., Chesley, H. R., McGhee, D. E., Kawal, R., Landau, J. 2000. Structured Online Interactions: Improving the Decision-Making of Small Discussion Groups. In Proceedings of the 2000 ACM conference on Computer Supported Cooperative Work. ACM Press, 299308.CrossRefGoogle Scholar
Fayyad, U., Piatetsky-shapiro, G., Smyth, P. 1996. From data mining to knowledge discovery in databases. AI Magazine 17, 3754.Google Scholar
Gordon, T. F., Prakken, H., Walton, D. 2007. The Carneades model of argument and burden of proof. Artificial Intelligence 171(10–15), 875896.CrossRefGoogle Scholar
Hand, D. J., Mannila, H., Smyth, P. 2001. Principles of Data Mining. MIT Press.Google Scholar
Horrocks, I., Patel-Schneider, P. F., Bechhofer, S., Tsarkov, D. 2005. OWL rules: a proposal and prototype implementation. Journal of Web Semantics 3(1), 2340.CrossRefGoogle Scholar
Kalfoglou, Y., Schorlemmer, M. 2003. Ontology mapping: the state of the art. Knowledge Engineering Review 18(1), 131.CrossRefGoogle Scholar
Katzav, J., Reed, C. 2004. On argumentation schemes and the natural classification of arguments. Argumentation 18(2), 239259.CrossRefGoogle Scholar
McGuinness, D. L., van Harmelen, F. 2004. OWL Web Ontology Language Overview. W3C Recommendation REC-owl-features-20040210, World Wide Web Consortium (W3C). http://www.w3.org/TR/owl-features/Google Scholar
Perelman, C., Olbrechts-Tyteca, L. 1969. The New Rhetoric: a Treatise on Argumentation. University of Notre Dame Press.Google Scholar
Pollock, J. L. 1987. Defeasible reasoning. Cognitive Science 11(4), 481518.CrossRefGoogle Scholar
Prakken, H., Sartor, G. 1997. Argument-based extended logic programming with defeasible priorities. Journal of Applied Non-Classical Logics 7(1), 2576.CrossRefGoogle Scholar
Rahwan, I. 2008. Mass Argumentation and the Semantic Web. Journal of Web Semantics 6(1), 2937.CrossRefGoogle Scholar
Rahwan, I., Banihashemi, B. 2008. Arguments in OWL: a progress report. In Proceedings of the 2nd International Conference on Computational Models of Argument (COMMA), Besnard, P., Doutre, S. & Hunter, A. (eds). IOS Press, 297310.Google Scholar
Rahwan, I., Zablith, F., Reed, C. 2007. Laying the foundations for a World Wide Argument Web. Artificial Intelligence 171(10–15), 897921.CrossRefGoogle Scholar
Reed, C., Rowe, G. 2004. Araucaria: software for argument analysis, diagramming and representation. International Journal of AI Tools 14(3–4), 961980.CrossRefGoogle Scholar
Reed, C., Walton, D. 2005. Towards a formal and implemented model of argumentation schemes in agent communication. Autonomous Agents and Multi-Agent Systems 11(2), 173188.CrossRefGoogle Scholar
Shum, S. B. 2008. Cohere: towards Web 2.0 argumentation. In Proceedings of the 2nd International Conference on Computational Models of Argument (COMMA), Hunter A. (ed.). IOS Press.Google Scholar
Stumme, G., Hotho, A., Berendt, B. (2006). Semantic Web mining: state of the art and future directions. Web Semantics: Science, Services and Agents on the World Wide Web 4(2), 124143.CrossRefGoogle Scholar
Toulmin, S. E. 1958. The Uses of Argument. Cambridge University Press.Google Scholar
van Eemeren, F. H., Grootendorst, R. F. 1992. Argumentation, Communication and Fallacies: A Pragma-Dialectical Perspective. Lawrence Erlbaum Associates.Google Scholar
Verheij, B. 2005. An argumentation core ontology as the centerpiece of a myriad of argumentation formats. Agentlink Technical Forum Group.Google Scholar
Völkel, M., Krötzsch, M., Vrandečić, D., Haller, H., Studer, R. 2006. Semantic wikipedia. In Proceedings of the 15th international conference on World Wide Web, WWW 2006. ACM Press, 585–594.Google Scholar
Walton, D. N. 1996. Argumentation Schemes for Presumptive Reasoning. Erlbaum.Google Scholar
Walton, D. N. 2006. Fundamentals of Critical Argumentation. Cambridge University Press.Google Scholar
Walton, D., Reed, C., Macagno, F. 2008. Argumentation Schemes. Cambridge University Press.CrossRefGoogle Scholar
Wells, S., Gourlay, C., Reed, C. 2009. Argument blogging. In Proceedings of the 9th International Workshop on Computational Models of Natural Argument (CMNA), Pasadena, California.Google Scholar