String processing model for knowledge-driven systems

The purpose of the work is to confirm experimentally theoretical estimates for time complexity of operations of the string processing model linked with the metric space for solving data processing problems in knowledge-driven systems including the research and comparison of the operation characteris...

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Main Author: V. P. Ivashenko
Format: Article
Language:Russian
Published: Educational institution «Belarusian State University of Informatics and Radioelectronics» 2020-10-01
Series:Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki
Subjects:
Online Access:https://doklady.bsuir.by/jour/article/view/2782
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spelling doaj-94cd3efc07f5489f90f218e68ad46a0d2021-07-28T16:19:59ZrusEducational institution «Belarusian State University of Informatics and Radioelectronics»Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki1729-76482020-10-01186334010.35596/1729-7648-2020-18-6-33-401629String processing model for knowledge-driven systemsV. P. Ivashenko0Belarusian State University of Informatics and RadioelectronicsThe purpose of the work is to confirm experimentally theoretical estimates for time complexity of operations of the string processing model linked with the metric space for solving data processing problems in knowledge-driven systems including the research and comparison of the operation characteristics of these operations with the characteristics of similar operations for the most relevant data structures. Integral and unit testing were used to obtain the results of the performed computational experiments and verify their correctness. The C \ C++ implementation of operations of the string processing model was tested. The paper gives definitions of concepts necessary for the calculation of metric features calculated over strings. As a result of the experiments, theoretical estimates of the computational complexity of the implemented operations and the validity of the choice of parameters of the used data structures were confirmed, which ensures near-optimal throughput and operation time indicators of operations. According to the obtained results, the advantage is the ability to guarantee the time complexity of the string processing operations no higher than O  at all stages of a life cycle of data structures used to represent strings, from their creation to destruction, which allows for high throughput in data processing and responsiveness of systems built on the basis of the implemented operations. In case of solving particular string processing problems and using more suitable for these cases data structures such as vector or map the implemented operations have disadvantages meaning they are inferior in terms of the amount of data processed per time unit. The string processing model is focused on the application in knowledge-driven systems at the data management level.https://doklady.bsuir.by/jour/article/view/2782strings processinglists processingstring operationconcatenationstring splittingsearching by key
collection DOAJ
language Russian
format Article
sources DOAJ
author V. P. Ivashenko
spellingShingle V. P. Ivashenko
String processing model for knowledge-driven systems
Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki
strings processing
lists processing
string operation
concatenation
string splitting
searching by key
author_facet V. P. Ivashenko
author_sort V. P. Ivashenko
title String processing model for knowledge-driven systems
title_short String processing model for knowledge-driven systems
title_full String processing model for knowledge-driven systems
title_fullStr String processing model for knowledge-driven systems
title_full_unstemmed String processing model for knowledge-driven systems
title_sort string processing model for knowledge-driven systems
publisher Educational institution «Belarusian State University of Informatics and Radioelectronics»
series Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki
issn 1729-7648
publishDate 2020-10-01
description The purpose of the work is to confirm experimentally theoretical estimates for time complexity of operations of the string processing model linked with the metric space for solving data processing problems in knowledge-driven systems including the research and comparison of the operation characteristics of these operations with the characteristics of similar operations for the most relevant data structures. Integral and unit testing were used to obtain the results of the performed computational experiments and verify their correctness. The C \ C++ implementation of operations of the string processing model was tested. The paper gives definitions of concepts necessary for the calculation of metric features calculated over strings. As a result of the experiments, theoretical estimates of the computational complexity of the implemented operations and the validity of the choice of parameters of the used data structures were confirmed, which ensures near-optimal throughput and operation time indicators of operations. According to the obtained results, the advantage is the ability to guarantee the time complexity of the string processing operations no higher than O  at all stages of a life cycle of data structures used to represent strings, from their creation to destruction, which allows for high throughput in data processing and responsiveness of systems built on the basis of the implemented operations. In case of solving particular string processing problems and using more suitable for these cases data structures such as vector or map the implemented operations have disadvantages meaning they are inferior in terms of the amount of data processed per time unit. The string processing model is focused on the application in knowledge-driven systems at the data management level.
topic strings processing
lists processing
string operation
concatenation
string splitting
searching by key
url https://doklady.bsuir.by/jour/article/view/2782
work_keys_str_mv AT vpivashenko stringprocessingmodelforknowledgedrivensystems
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