Argumentation placement recommendation and relevancy assessment in an intelligent argumentation system

Author

Nian Liu

Abstract

"Argumentation is a critical process for many social activities that need collaborative intelligence. Existing intelligent argumentation systems allow multiple stakeholders from distributed geographical locations to share their opinions and contribute to a decision making process. In the current system, a stakeholder needs to read all the existing arguments posted by other stakeholders before contributing his/her own ideas/arguments. However, when information accumulates and an argumentation network becomes considerably large, it will cost tremendous time and effort for the stakeholder to read and comprehend all existing arguments. In this paper, we propose methods to implement a argument placement recommendation component built into an intelligent argumentation system. The recommendation component can automatically assist a stakeholder to better understand the current state of an argumentation by summarizing and identifying a subset of existing arguments that are relevant to the stakeholder. Thus, our proposed work will allow a stakeholder to efficiently and effectively express his/her thoughts in an intelligent argumentation system. We also empirically evaluate the effectiveness of the proposed recommendation component, and the emperical results indicate that it is effective"--Abstract, page iii.

Advisor(s)

Jiang, Wei

Committee Member(s)

Liu, Xiaoqing Frank
Lin, Dan

Department(s)

Computer Science

Degree Name

M.S. in Computer Science

Publisher

Missouri University of Science and Technology

Publication Date

Spring 2013

Pagination

vii, 27 pages

Note about bibliography

Includes bibliographical references (pages 23-26).

Rights

© 2013 Nian Liu, All rights reserved.

Document Type

Thesis - Restricted Access

File Type

text

Language

English

Subject Headings

Reasoning -- Computer simulationLogic -- Computer simulationArtificial intelligenceGroupware (Computer software)

Thesis Number

T 10329

Print OCLC #

861334424

Electronic OCLC #

908848870

Recommended Citation

Liu, Nian, "Argumentation placement recommendation and relevancy assessment in an intelligent argumentation system" (2013). Masters Theses. 5993.
https://scholarsmine.mst.edu/masters_theses/5993