Elements of the regional innovation environment are currently disunited. The main obstacle to effective interaction of subjects of innovation in Russia, we believe to be a high level of innovation costs, which are mainly of a transactional nature. Modeling of processes of interaction of the main participants of innovative activity in the regional innovation system is necessary to understand at a qualitative and quantitative level the role of links between elements of the innovation environment, the impact of their interaction on the attractor zones, on the potentials of system order parameters. Increasing the interaction between all stakeholders in the innovation system is a very important mechanism for the development of innovation at various stages of the innovation process, from the emergence of the idea to the commercialization of innovation. This study is focused on obtaining new knowledge in the field of creating a methodology for multi-agent search, collecting and processing data on indicators of innovative development of enterprises, models and methods of intellectual analysis of collected data. The complex of models and methods is based for the first time on the use of a convergent model for processing big data. The article is aimed at solving fundamental scientific problems in terms of the development of methods for predictive modeling and evaluation of the parameters of innovative development of regional enterprises, the synthesis of new methods of processing and intellectual analysis of big data, methods of extracting knowledge and predicting the dynamics of regional innovation development using benchmarking approach
Keywords: interaction management, cyber-social system, multiagent approach, benchmarking, big data, intellectual analysis, region.
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