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Identification of Faction Groups and Leaders in Web-Based Intelligent Argumentation System

This study focuses on identifying faction groups and leaders in a Web-based intelligent argumentation system for collaborative decision support. The research employs the K-means clustering algorithm to identify faction groups based on stakeholder favorability towards alternatives. The intelligent argumentation system utilizes fuzzy inference engines for effective argument management. The study aims to enhance decision-making by identifying and evaluating faction groups and leaders.

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Identification of Faction Groups and Leaders in Web-Based Intelligent Argumentation System

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  1. Identification of faction groups and leaders in Web-based intelligent argumentation system for collaborative decision support Student: Ravi Arvapally, Computer Science Department Faculty Advisor(s): Drs. Frank Liu , Wei Jiang Computer Science Department • INTRODUCTION & OBJECTIVES • To identify the faction groups and group leaders in the Web based intelligent argumentation system. • A group of stakeholders who share a similar opinion for the given issue and exchange arguments with other stakeholders to make their opinion as the decision is called a faction group. • A stakeholder who receives the highest support from their group is called the faction leader for that group. • The favorability of each stakeholder towards the alternatives is computed and the K-means clustering algorithm is used to identify faction groups. • INTELLIGENT ARGUMENTATION SYSTEM • Intelligent Argumentation system is a Web-based application, and it is based on the Client – Server Architecture. • Participants can post their arguments using any Web browser. • The Server runs three different fuzzy inference engines for the reduction of arguments, reassessment of argument weights and for the dynamic priority assessment. • The Server takes issues, alternatives, arguments, and evidences as inputs and manages them in the argumentation tree by using the fuzzy inference engines. ARGUMENTATION DIALOG GRAPH WEB-BASED INTELLIGENT ARGUMENTATION SYSTEM FRAMEWORK FOR FACTION ASSESSMENT DATA COLLECTION AND PREPARATION IDENTIFICATION OF FACTION GROUPS USING K-MEANS CLUSTERING ALGORITHM Cluster Centroids Faction groups • IDENTIFICATION OF FACTION LEADERS • CONCLUSION • Identification of faction groups and leaders in a decision making group can assist in making more appropriate decision. • We would like to conduct an empirical study and evaluate our framework. ACKNOWLEDGEMENTS – This research is supported by the Intelligent Systems center at Missouri University of Science & Technology – Rolla.

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