NDLI: Argument placement recommendation and relevancy assessment in an intelligent argumentation system

Content Provider	IEEE Xplore Digital Library
Author	Feng Li Nian Liu Wei Jiang Xiaoqing Liu
Copyright Year	2013
Description	Author affiliation: Dept. of Comput. Sci., Missouri Univ. of Sci. & Technol., Rolla, MO, USA (Feng Li; Nian Liu; Wei Jiang; Xiaoqing 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 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 in relevant argumentation thread. We also empirically evaluate the effectiveness of the proposed recommendation component, and the empirical results indicate it is effective according to a real dataset.
Sponsorship	IEEE Aerosp. Electron. Syst. Soc.
Starting Page	427
Ending Page	434
File Size	428650
Page Count	8
File Format	PDF
ISBN	9781467364034
e-ISBN	9781467364041
DOI	10.1109/CTS.2013.6567265
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-05-20
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	argumentation Decision making Collaboration collaborative decision making and support Vectors Mathematical model Noise measurement Artificial intelligence Collaboration enabling technologies
Content Type	Text
Resource Type	Article

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