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Лінгвістичний процесор для пошуку та опрацювання кримінально значимої інформації в неструктурованих масивах

Лінгвістичний процесор для пошуку та опрацювання кримінально значимої інформації в неструктурованих масивах

Abstract

В статті запропонована модель лінгвістичного процесора для пошуку та опрацювання кримінально значимої інформації з неструктурованих текстових масивів з використанням статистичних методів виділення коллокацій та латентно-семантичного аналіза. In the article the model of linguistic processor is offered for a search and selection criminally of meaningful information from the unstructured text arrays with the use of statistical methods of selection of collotions and latently-semantic analysis.

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Keywords

модель, linguistic processor, collocation, латентно-семантичний аналіз, інформаційний прстір, latent-semantic analysis, коллокація, criminally relevant information, statistical methods

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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.
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    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