The increasing number of available collaborative tools and their extensive use in many organizational activities has constantly raised the complexity of collaboration engineering. It presumes the design of group decision processes, supported by a wide-range of groupware tools, in an ill-structured, dynamic, and open environment. As many of these processes are recurring by nature, the development of a shared repository to store the collective knowledge and experiences of group decision process designs became a core research topic of collaboration engineering in last few years. The paper presents a human–computer interaction engineering approach to design a software prototype that provides personalized, contextual and actionable recommendations for this problem. The approach emphasizes the computational aspects of collective intelligence, inspired from the stigmergic system designs, to structure these recommendations based on the collective knowledge that reflects not only the design space per se, but the collective experience in exploiting it as well. It is demonstrated by (1) detailing the engineering issues of an implemented prototype for the group decision process design; and (2) explaining its functionalities through a representative set of interaction scenarios. The paper covers the methodological, theoretical and practical aspects of engineering the above mentioned issues.
In Neurocomputing - Bridging Machine learning and Evolutionary Computation (BMLEC) Computational Collective Intelligence
Springer International Publishing
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