Providing Awareness of Cooperative Efficiency in Collaborative Graphics Design Systems through Reaction Mining

Abstract

Awareness of individual and group activities is critical to successful collaboration and is commonly supported in collaborative graphics design systems (CGDS). Awareness of cooperative efficiency visualized in fine granularity is valuable for finding out the bottlenecks in collaborative design process. However, little work has been done. In this paper we propose a novel intelligent cooperative efficiency evaluation mechanism via mining the reaction information. By visualizing cooperative efficiency, cooperators are enabled to concentrate on the most of controversial part of the cooperative work. Related algorithm that includes two key concepts: expectation and convergence is proposed. The mechanism and algorithm have been realized in our prototype system and are proved significantly promote the coordination efficiency.