Title

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.

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.

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