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Analytical System Design to Identify the User Category of a Social Network to Offer Online Courses

Student: Makarova Inna

Supervisor: Elena Zamyatina

Faculty: Faculty of Economics, Management, and Business Informatics

Educational Programme: Information Analytics in Enterprise Management (Master)

Year of Graduation: 2019

The master's graduation qualification work on the topic “Analytical System Design to Identify the User Category of a Social Network to Offer Online Courses”. Author: Makarova Inna Valerievna Faculty of Economics, Management and Business Informatics, group IАUP-1-17 Leader: Zamyatina Elena Borisovna Candidate of Physical and Mathematical Sciences, Associate Professor The work is devoted to designing an analytical system for identifying categories of users of social networks with a view to further recommending online courses to them in their curricula. The analytical system is based on a multi-agent method with request to ontology to search for a relevant online-course. The work examines and uses data mining methods, in particular text mining, compares the effectiveness of k-means and CLOPE users' clustering methods. There are 37 sources, 18 illustrations and 5 tables, 5 applications in the work.

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