employee from 01.01.2016 until now
Saint Petersburg, St. Petersburg, Russian Federation
student
g. Sankt-Peterburg, St. Petersburg, Russian Federation
employee
g Sankt-Peterburg, St. Petersburg, Russian Federation
UDC 004
UDC 33
CSCSTI 20.00
Russian Classification of Professions by Education 38.00.00
Russian Classification of Professions by Education 09.00.00
Russian Library and Bibliographic Classification 3
Russian Trade and Bibliographic Classification 6
The article presents the use of K-Means cluster analysis within an intelligent decision support system for grouping project management options, as well as the formation of selection recommendations for the end user based on the clustering results. In addition, various options for performing cluster analysis are shown, as well as the impact of these options on the final results. The practical utility of the system for analyzing projects whose implementation depends on multiple variable components and requires a detailed analysis of options by group to select suitable ones for various scenarios and limit options is demonstrated.
decision support systems, cluster analysis, recommender system, project management, big data analysis, application of machine learning methods in economics
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