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Authors: Olga V. Korableva 1 ; Viktoriya N. Mityakova 2 and Olga N. Kalimullina 3

Affiliations: 1 St. Petersburg State University, Institute of Regional Economic Studies of Russian Academy of Science, S-Petersburg, Russian Federation ; 2 St. Petersburg Electrotechnical University "LETI" (ETU), S-Petersburg, Russian Federation ; 3 The Bonch-Bruevich Saint-Petersburg State University of Telecommunications, S-Petersburg, Russian Federation

Keyword(s): Decision Support System, Innovation Activity, Potential of Economic Growth, Ontology, Semantic Search.

Abstract: Decision support systems for predicting innovation activity at the macro level are not yet widely used, and the authors have not been able to find direct analogues of such a system. The relevance of creating the system is due to the need to take into account heterogeneous structured and unstructured information, including in natural language, when predicting innovation activity. The article describes the process of designing a decision support system for predicting innovation activity, based on the system for integrating macroeconomic and statistical data (described by the authors in previous articles) by adding a module of decision-making methods. The UML diagram of use cases and the UML diagram of the components of this module, the general architecture of the prototype of the decision support system, are presented. It also describes an algorithm for predicting innovation activity and its impact on the potential for economic growth using DSS.

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Paper citation in several formats:
Korableva, O. ; Mityakova, V. and Kalimullina, O. (2020). Designing a Decision Support System for Predicting Innovation Activity. In Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-423-7; ISSN 2184-4992, SciTePress, pages 619-625. DOI: 10.5220/0009565706190625

@conference{iceis20,
author={Olga V. Korableva and Viktoriya N. Mityakova and Olga N. Kalimullina},
title={Designing a Decision Support System for Predicting Innovation Activity},
booktitle={Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2020},
pages={619-625},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009565706190625},
isbn={978-989-758-423-7},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Designing a Decision Support System for Predicting Innovation Activity
SN - 978-989-758-423-7
IS - 2184-4992
AU - Korableva, O.
AU - Mityakova, V.
AU - Kalimullina, O.
PY - 2020
SP - 619
EP - 625
DO - 10.5220/0009565706190625
PB - SciTePress

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