MODEL IDENTIFICATION OF PROPERTIES OF ERRORS IN DATA PROCESSING TECHNOLOGY

The recognition problem is solved on the basis of the properties of the statistical classification structure errors, referred to as defects. Classification is performed by agglomerative cluster analysis on Euclidean metric. Experimental clustering carried out by varying the time and cost of finding...

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Main Author: George N. Isaev
Format: Article
Language:English
Published: Plekhanov Russian University of Economics 2016-05-01
Series:Открытое образование (Москва)
Subjects:
Online Access:https://openedu.rea.ru/jour/article/view/10
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author George N. Isaev
author_facet George N. Isaev
author_sort George N. Isaev
collection DOAJ
description The recognition problem is solved on the basis of the properties of the statistical classification structure errors, referred to as defects. Classification is performed by agglomerative cluster analysis on Euclidean metric. Experimental clustering carried out by varying the time and cost of finding and eliminating defects. We identified three major classes of defects – for accuracy, completeness and timeliness of the data. The analysis of each class of defects in their parameters, the weight value, the causes and others. In view of the identification of the properties of defects solved the problem of improving the quality of information systems.
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issn 1818-4243
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publisher Plekhanov Russian University of Economics
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spelling doaj-art-f4e5b247b40045cc915b6d30aabbd4b12025-08-20T03:01:02ZengPlekhanov Russian University of EconomicsОткрытое образование (Москва)1818-42432079-59392016-05-0101545910.21686/1818-4243-2016-1-54-599MODEL IDENTIFICATION OF PROPERTIES OF ERRORS IN DATA PROCESSING TECHNOLOGYGeorge N. Isaev0The Russian state university of tourism and serviceThe recognition problem is solved on the basis of the properties of the statistical classification structure errors, referred to as defects. Classification is performed by agglomerative cluster analysis on Euclidean metric. Experimental clustering carried out by varying the time and cost of finding and eliminating defects. We identified three major classes of defects – for accuracy, completeness and timeliness of the data. The analysis of each class of defects in their parameters, the weight value, the causes and others. In view of the identification of the properties of defects solved the problem of improving the quality of information systems.https://openedu.rea.ru/jour/article/view/10recognition of the properties of the errorthe cluster analysis modelthe processing of datasources of errorerror recoveryinformation systems
spellingShingle George N. Isaev
MODEL IDENTIFICATION OF PROPERTIES OF ERRORS IN DATA PROCESSING TECHNOLOGY
Открытое образование (Москва)
recognition of the properties of the error
the cluster analysis model
the processing of data
sources of error
error recovery
information systems
title MODEL IDENTIFICATION OF PROPERTIES OF ERRORS IN DATA PROCESSING TECHNOLOGY
title_full MODEL IDENTIFICATION OF PROPERTIES OF ERRORS IN DATA PROCESSING TECHNOLOGY
title_fullStr MODEL IDENTIFICATION OF PROPERTIES OF ERRORS IN DATA PROCESSING TECHNOLOGY
title_full_unstemmed MODEL IDENTIFICATION OF PROPERTIES OF ERRORS IN DATA PROCESSING TECHNOLOGY
title_short MODEL IDENTIFICATION OF PROPERTIES OF ERRORS IN DATA PROCESSING TECHNOLOGY
title_sort model identification of properties of errors in data processing technology
topic recognition of the properties of the error
the cluster analysis model
the processing of data
sources of error
error recovery
information systems
url https://openedu.rea.ru/jour/article/view/10
work_keys_str_mv AT georgenisaev modelidentificationofpropertiesoferrorsindataprocessingtechnology