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Human-Computer Cloud for Decision Support: Main Ontological Models and Dynamic Resource Network Configuration

  • Alexander Smirnov
  • Tatiana Levashova
  • Nikolay Shilov
  • Andrew Ponomarev
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 874)

Abstract

Information processing systems utilizing the input received from human contributors are currently gaining popularity. One of the problems relevant to most of these systems is that they need a large number of contributors to function properly, while collecting this number of contributors may require significant effort and time. In the ongoing research, this problem is addressed by adaptation of cloud computing resource management principles to human-computer systems. The proposed human-computer cloud environment relies heavily on the use of ontologies for both resource discovery and automatic decision support workflow composition. This paper describes the set of main ontological models of the proposed human-computer cloud. Namely, the ontological model of the cloud environment, ontological model of the decision support system based on this environment and the ontology-based mechanism for workflow construction. The paper also illustrates the principles of dynamic workflow construction by an example from e-Tourism domain.

Keywords

Cloud computing Crowdsourcing Crowd computing Human-in-the-Loop Human factors Ontologies Decision support 

Notes

Acknowledgements

The research is funded by the Russian Science Foundation (project # 16-11-10253).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Alexander Smirnov
    • 1
  • Tatiana Levashova
    • 1
  • Nikolay Shilov
    • 1
  • Andrew Ponomarev
    • 1
  1. 1.SPIIRASSt. PetersburgRussia

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