INTRODUCTION & OBJECTIVES

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.