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ZENODO
Article . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
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Концепция использования больших данных в современных системах электронной коммерции

Концепция использования больших данных в современных системах электронной коммерции

Abstract

Статья посвящена изучению и анализу концепции применения больших данных в системах электронной коммерции. В статье освещаются текущие проблемы и ограничения, с которыми сталкиваются компании при использовании больших данных в сфере электронной коммерции. В работе рассматривается сложность анализа и интерпретации больших данных. Также освещаются вопросы конфиденциальности, безопасности, внедрения и поддержания инфраструктуры для обработки больших данных в системах электронной коммерции. Основываясь на проведенном анализе, в статье предлагаются рекомендации и методы улучшения использования больших данных в электронной коммерции с целью повышения эффективности и конкурентоспособности компаний.

Keywords

электронная коммерция, большие данные, IDEF0, машинное обучение, программное обеспечение, концепция, нейросети

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green