Form of presentation | Conference proceedings in international journals and collections |
Year of publication | 2020 |
Язык | русский |
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Abramov Denis Aleksandrovich, author
Galeev Salavat Ildarovich, author
Zapparov Bulat Ayratovich, author
Pashina Adelya Dmitrievna, author
Feyfer Raisa Leonidovna, author
|
Bibliographic description in the original language |
ABRAMOV D. A., GALEEV S. I., ZAPPAROV B. A., PAShINA A. D., FEYFER R. L. SOZDANIE KLASSIFIKACII KLASTERIZACII
I PRORABOTANNOSTI CIFROVYKh DANNYKh
DLYa EFFEKTIVNOGO PROGNOZIROVANIYa
REGIONALNOGO RAZVITIYa// Vedecko vydavatelske centrum Sociosfera-CZ s.r.o. - 2020. - №34. - s.15-23 |
Annotation |
Vedecko vydavatelske centrum Sociosfera-CZ s.r.o. |
Keywords |
regional economics; statistics; data redistribution; data clusterization; data classi-fication; big data analytics |
The name of the journal |
Vedecko vydavatelske centrum Sociosfera-CZ s.r.o.
|
Please use this ID to quote from or refer to the card |
https://repository.kpfu.ru/eng/?p_id=240996&p_lang=2 |
Resource files | |
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Full metadata record |
Field DC |
Value |
Language |
dc.contributor.author |
Abramov Denis Aleksandrovich |
ru_RU |
dc.contributor.author |
Galeev Salavat Ildarovich |
ru_RU |
dc.contributor.author |
Zapparov Bulat Ayratovich |
ru_RU |
dc.contributor.author |
Pashina Adelya Dmitrievna |
ru_RU |
dc.contributor.author |
Feyfer Raisa Leonidovna |
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 |
АБРАМОВ Д. А., ГАЛЕЕВ С. И., ЗАППАРОВ Б. А., ПАШИНА А. Д., ФЕЙФЕР Р. Л. СОЗДАНИЕ КЛАССИФИКАЦИИ КЛАСТЕРИЗАЦИИ
И ПРОРАБОТАННОСТИ ЦИФРОВЫХ ДАННЫХ
ДЛЯ ЭФФЕКТИВНОГО ПРОГНОЗИРОВАНИЯ
РЕГИОНАЛЬНОГО РАЗВИТИЯ// Vedecko vydavatelske centrum Sociosfera-CZ s.r.o. - 2020. - №34. - с.15-23 |
ru_RU |
dc.identifier.uri |
https://repository.kpfu.ru/eng/?p_id=240996&p_lang=2 |
ru_RU |
dc.description.abstract |
Vedecko vydavatelske centrum Sociosfera-CZ s.r.o. |
ru_RU |
dc.description.abstract |
This article observes ecosystem, which creates as many data redistributions as possible in order to cluster and classify them. Conventionally, redistributions can be divided into zero, lowest, low, middle, high, and highest level of clusterization. The higher the redis-tribution of data, the more contractors are involved, both in the process of their creation and use, and thereby the multiplier effect in the regional economy increases. |
ru_RU |
dc.language.iso |
ru |
ru_RU |
dc.subject |
|
ru_RU |
dc.title |
СОЗДАНИЕ КЛАССИФИКАЦИИ КЛАСТЕРИЗАЦИИ
И ПРОРАБОТАННОСТИ ЦИФРОВЫХ ДАННЫХ
ДЛЯ ЭФФЕКТИВНОГО ПРОГНОЗИРОВАНИЯ
РЕГИОНАЛЬНОГО РАЗВИТИЯ |
ru_RU |
dc.type |
Conference proceedings in international journals and collections |
ru_RU |
|