A Case-based Reasoning Approach for Automated Facilitation in Online Discussion Systems

Online discussion systems have recently attracted great attention as an enabling approach of realizing collective intelligence. During online discussions, human facilitators are introduced in order to help these discussions to proceed more efficiently and productively. However, there are a number of challenges such as human bias and time restriction that need to be solved in the human facilitator-based online discussion systems. As a result, automated facilitation becomes necessary in order to overcome these shortcomings. This paper proposes a novel approach for automated facilitation that utilizes case based reasoning (CBR) in order to imitate the human facilitator thinking style. The proposed approach works in issue based information system (IBIS) discussion style where complex problems are designed as a conversation amongst several stockholders. These stockholders, in turn, bring their expertise in order to resolve the discussion point. Experimental results show the ability of the proposed approach to improve the performance of online discussion systems, and to guide the online discussion towards consensus and towards gathering wisdom efficiently.