Fuzzy C-means Clustering Based Polarization Assessment in Intelligent Argumentation System for Collaborative Decision Support
Abstract
Intelligent argumentation system facilitates stakeholders to exchange rationale of the stakeholders through arguments. In argumentation process, stakeholders tend to polarize on their opinions and form polarization groups. A method [1] was developed earlier to identify polarization groups, however, polarization groups tend to overlap to a certain degree and each stakeholder may be a member of multiple polarization groups to varied degrees. Quantifying stakeholders' membership in multiple polarization groups in argumentation for collaborative decision making is not addressed earlier. We present an approach using fuzzy clustering algorithm to address this issue and evaluate the approach using an argumentation tree built by twenty four stakeholders.
Recommended Citation
R. S. Arvapally et al., "Fuzzy C-means Clustering Based Polarization Assessment in Intelligent Argumentation System for Collaborative Decision Support," Proceedings of the 2013 IEEE 37th Annual Computer Software and Applications Conference (COMPSAC), pp. 59 - 64, Institute of Electrical and Electronics Engineers (IEEE), Jan 2013.
The definitive version is available at https://doi.org/10.1109/COMPSAC.2013.12
Meeting Name
2013 IEEE 37th Annual Computer Software and Applications Conference (COMPSAC) (2013: Jul. 22-26, Kyoto, Japan)
Department(s)
Electrical and Computer Engineering
Second Department
Computer Science
International Standard Book Number (ISBN)
978-0769549866
International Standard Serial Number (ISSN)
0730-3157
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2013 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jan 2013
