Text-Based Clustering and Analysis of Intelligent Argumentation Data
Abstract
Argumentation is a method by which stakeholders exchange their viewpoints and rationale in the form of arguments in an organized manner in order to conduct collaborative decision making. Many online systems have been implemented in order to provide geographically distributed stakeholders with a structured method of argumentation. However, as these systems collect large amounts of arguments; it can be difficult to readily assess the major concerns which drive the discussion. This work presents a method for clustering and classifying a set of arguments, collected through an online argumentation tool, in order to model major concerns in an argumentation process. These clusters are further analyzed to provide a qualitative understanding of the influence they have on the decision making process.
Recommended Citation
E. C. Barnes and X. F. Liu, "Text-Based Clustering and Analysis of Intelligent Argumentation Data," Proceedings of the 26th International Conference on Software Engineering and Knowledge Engineering (2014, Vancouver, BC), vol. 2014-January, no. January, pp. 422 - 425, Knowledge Systems Institute Graduate School, Jul 2014.
Meeting Name
26th International Conference on Software Engineering and Knowledge Engineering (2014: Jul. 1-3, Vancouver, BC)
Department(s)
Computer Science
Keywords and Phrases
Collaborative decision making; Text clustering
International Standard Serial Number (ISSN)
2325-9000
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2014 Knowledge Systems Institute Graduate School, All rights reserved.
Publication Date
01 Jul 2014
