Using Data Mining with Fuzzy Methods for the Development of the Regional Marketing Geospace Information System

  • G. Akperov ImranEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1095)


The article reviews the use of data mining specifics based on applying models with a combined architecture in the fuzzy marketing. The use of digital economy requires changing criteria and priorities. This includes the artificial intelligence deployment, which enables monitoring of a huge number of parameters of economic, political and social processes in general and in relation to a relevant region or to an economic cluster, and implementing adequate executive decision-making procedures. The review of regional economic processes reveals a connection and interaction between their individual parameters, such as the ability to operate and interact with other systems without any restrictions, with reference to geographic location, or the so called geo-interoperability. This concept is closely related to the theory of geo-information space (GIS), a phenomenon formed by System of Systems, which includes components of natural and artificial origin and has certain synergistic properties. The article reviews a number of features of the GIS approach in the study of distributed social, ecological, economic and marketing processes, including their versatility, interdisciplinarity and the possibility of using the advantages of a systematic approach in these studies. There are various approaches to assessing such properties of the marketing geospace as adaptability, self-learning, self-adjustment, and sustainable development. The article reveals the connection between the regional marketing space and emerging economic clusters.


Geo-information marketing space Marketing systems architecture Marketing information systems Interoperability Combined models 


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    Karpik, A.P., Lisitsky, D.V.: Electronic geo-space - the essence and conceptual framework. Geodesy cartogr. 5, 41–44 (2009)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Private Educational Institution of Higher Education “Southern University (IMBL)”Rostov-on-DonRussia

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