Abstract
The paper describes conceptual and technological principles of the human-computer cloud, that allows to deploy and run human-based applications. It also presents two ways to build decision support services on top of the proposed cloud environment for problems where workflows are not (or cannot be) defined in advance. The first extension is represented by a decision support service leveraging task ontology to build the missing workflow, the second utilizes the idea of human-machine collective intelligence environment, where the workflow is defined in the process of a (sometimes, guided) collaboration of the participants.
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Acknowledgements
The research was funded by the Russian Science Foundation. The HCC architecture, PaaS and ontology-based decision support service based on task decomposition were developed as a part of project #Â 16-11-10253, the self-organizing environment for collective human-machine intelligence is being developed as a part of project #Â 19-11-00126.
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Smirnov, A., Shilov, N., Ponomarev, A. (2020). Human-Computer Systems for Decision Support: From Cloud to Self-organizing Environments. In: Ferguson, D., Méndez Muñoz, V., Pahl, C., Helfert, M. (eds) Cloud Computing and Services Science. CLOSER 2019. Communications in Computer and Information Science, vol 1218. Springer, Cham. https://doi.org/10.1007/978-3-030-49432-2_1
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