Cloud Framework for the Networked Expert and Analytical Tools Integration
Analytic decision support systems for public and for business applications usually have a distributed nature. We separate these systems into two distinct analytics support frames. The first frame is based on the processes of data consolidation, delivery and preprocessing. The second frame realizes decision support through the real time analysis of the expertize. The participants in the distributed decision-making system are immersed in the atmosphere of virtual reality. But the technological bridge between the distance separated participants of the decision-making process prevents the growth of the decisions quality, makes it difficult to achieve the participants agreement, especially when they are working in heterogeneous environments that require switching interfaces and software. The question is to accelerate the process of agreement achievement. It is proposed an approach that is based on the use of situational awareness, virtual collaboration and cloud computing techniques. It is proposed the new approach to make the cognitive model verification by using the analysis of Big Data. The algorithm is based on the assumption that the judgment of an interference between the factors of the cognitive model can be found in the texts of documents from Big Data. It is also provided the framework of knowledge management for the integration analytical tools in the cloud. The framework supports the targeted and sustained convergence of the decision-making processes. The basis for the structure of the framework is based on the author's method of inverse problems solving in topological spaces with the use of genetic algorithms. It is noted that the proposed approach was formed during the creating about 50 projects in the field of strategic analysis, information-analytical systems
Proceedings of the Institute for System Programming, vol. 27, issue 6, 2015, pp. 421-440.
ISSN 2220-6426 (Online), ISSN 2079-8156 (Print).
DOI: 10.15514/ISPRAS-2015-27(6)-27Full text of the paper in pdf (in Russian) Back to the contents of the volume