Makrusev V.V.Russian Customs Academy, Lyubertsy, Moscow Oblast, Russian Federation makrusev@mail.ru ORCID id: not available
Sobol' A.A.Russian Customs Academy, Lyubertsy, Moscow Oblast, Russian Federation sobol_aa@bk.ru ORCID id: not available
Subject The article considers prospects for enhancing the quality of analytical activities of the Customs authorities through a cognitive approach implementation. Objectives The aim is to formulate promising areas for improving the quality of analytical work of the Customs authorities by using a cognitive approach, to develop a concept for managing the analytical activities based on knowledge. Methods The study rests on systems methodology and institutional theory. It also employs cognitive modeling techniques. Results We show the process of transferring disparate data into knowledge, consider basic methods of big data processing, and identify the most acceptable method of customs data analysis. The paper discloses the contents and elements of the cognitive approach in analytical activities of on-line monitoring centers and describes an experiment with the application of data mining technology on the basis of the Federal Customs Service of Russia. We recommend the said approach to analytical and ICT units of organizations operating in the field of customs services. Conclusions Current trends in software development, the use of electronic forms of customs documents, and continuously expanded list of analytical tools for big data processing entail the need for changing traditional approaches to information analysis to assess customs risks. The expert method should be supplemented with new, previously unused decision support tools, such as tools that enable automated big data analysis.
Keywords: big data, service-oriented customs regulation, cognitive approach, data mining, Federal Customs Service
References:
Makrusev V.V. [Service-oriented customs regulation: Ideas, institutions, governance]. Konkurentosposobnost' v global'nom mire: ekonomika, nauka, tekhnologii = Competitiveness in a Global World: Economics, Science, Technology, 2017, no. 12, part 10, pp. 1239–1242. URL: Link (In Russ.)
Makrusev V.V. [Relevant aspects of implementation of a service oriented customs administration concept]. Tamozhennoe delo = Customs Affairs, 2017, no. 2, pp. 13–17. URL: Link (In Russ.)
Bonenko T.A., Makarenko S.A., Makrusev V.V. [Comparative analysis of the strategy and the integrated program of development of FCS of Russia for the period up to 2020]. Strategii biznesa, 2017, no. 12. (In Russ.) URL: Link
Bonenko T.A., Makarenko S.A., Makrusev V.V. [Areas for customs service development after 2020]. NOVAUM.RU, 2017, no. 10. (In Russ.) URL: Link
Barsegyan A.A., Kupriyanov M.S., Stepanenko V.V., Kholod I.I. Metody i modeli analiza dannykh: OLAP i Data Mining [Data analysis methods and models: OLAP and Data Mining]. St. Petersburg, BkhV-Peterburg Publ., 2004, 336 p.
Antopol'skii A.B., Efremenko D.V. Infosfera obshchestvennykh nauk Rossii: monografiya [Infosphere of social sciences of Russia: a monograph]. Moscow, Berlin, Direkt-Media Publ., 2017, 678 p.
Paklin N.B., Oreshkov V.I. Biznes-analitika: ot dannykh k znaniyam [Business analytics: From data to knowledge]. St. Petersburg, Piter Publ., 2009, 102 p.
Han J., Kamber M., Pei J. Data Mining: Concepts and Techniques. Morgan Kaufmann, 2012, 744 p.