Form of presentation | Articles in international journals and collections |
Year of publication | 2020 |
Язык | русский |
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Vakhitov Galim Zaribzyanovich, author
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Bibliographic description in the original language |
Galim Vakhitov, Zulfira Enikeeva, Pavel Ustin, Nagim Davletshin, Clustering of Social Network Data by Means of Kohonen Neural
Networks / Proceedings of the International Workshop on Data Mining and Knowledge Engineering, Stavropol, Russia, October 15-16, 2020, p.128-135.
|
Annotation |
Proceedings of the International Workshop on Data Mining and Knowledge Engineering |
Keywords |
social networks, academic performance, data clustering, the Kohonen neural network
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The name of the journal |
Proceedings of the International Workshop on Data Mining and Knowledge Engineering
|
URL |
https://ceur-ws.org/Vol-2842/paper_15.pdf |
Please use this ID to quote from or refer to the card |
https://repository.kpfu.ru/eng/?p_id=273519&p_lang=2 |
Full metadata record ![](https://shelly.kpfu.ru/pdf/picture/arrow_black_right.gif) |
Field DC |
Value |
Language |
dc.contributor.author |
Vakhitov Galim Zaribzyanovich |
ru_RU |
dc.date.accessioned |
2020-01-01T00:00:00Z |
ru_RU |
dc.date.available |
2020-01-01T00:00:00Z |
ru_RU |
dc.date.issued |
2020 |
ru_RU |
dc.identifier.citation |
Galim Vakhitov, Zulfira Enikeeva, Pavel Ustin, Nagim Davletshin, Clustering of Social Network Data by Means of Kohonen Neural
Networks / Proceedings of the International Workshop on Data Mining and Knowledge Engineering, Stavropol, Russia, October 15-16, 2020, p.128-135.
|
ru_RU |
dc.identifier.uri |
https://repository.kpfu.ru/eng/?p_id=273519&p_lang=2 |
ru_RU |
dc.description.abstract |
Proceedings of the International Workshop on Data Mining and Knowledge Engineering |
ru_RU |
dc.description.abstract |
Social network user profile analysis is becoming an increasingly common source of information. In particular, the profile analysis can be used when hiring young employees. This information is poorly structured and it cannot be statistically analyzed in terms of what social network profile corresponds to a promising employee who has previously been a successful student. In this regard, we have carried out the clustering of these student profiles in the social network using the Kohonen neural network and revealed connections of the clusters with the data concerning the academic performance of students included in these clusters. |
ru_RU |
dc.language.iso |
ru |
ru_RU |
dc.subject |
social networks |
ru_RU |
dc.subject |
academic performance |
ru_RU |
dc.subject |
data clustering |
ru_RU |
dc.subject |
the Kohonen neural network
|
ru_RU |
dc.title |
Clustering of Social Network Data by Means of Kohonen Neural Networks |
ru_RU |
dc.type |
Articles in international journals and collections |
ru_RU |
|