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Известия Тульского государственного университета. Технические науки
Article . 2010
Data sources: CyberLeninka - Russian open access scientific library
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Использование нереляционных моделей данных в высоконагруженных информационных приложениях

descriptionPublicationkeyboard_double_arrow_right Article 01 Jan 2010 Russian Publisher:Федеральное государственное бюджетное образовательное учреждение высшего профессионального образования «Тульский государственный университет»Journal:Известия Тульского государственного университета. Технические науки (issn: 2071-6168, Copyright policy )

Использование нереляционных моделей данных в высоконагруженных информационных приложениях

Abstract

Рассмотрен вопрос использования отличных от реляционной форм представления данных в высоконагруженных информационных приложениях. Представлена модель реализации современной иерархической формы представления данных.

Question of using no-relational data model representation in heavy loaded information applications is considered. Model of hierarchical form data representation is presented.

Keywords

ЛОГИЧЕСКАЯ МОДЕЛЬ ДАННЫХ, НАБОРЫ ДАННЫХ

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    popularity
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    influence
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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
gold