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1.
Ivanov V.K., Palyukh B.V., Sotnikov A.N.
Features of Data Warehouse Support Based on a Search Agent and an Evolutionary Model for Innovation Information Selection Статья в сборнике
Опубликовано в: Advances in Intelligent Systems and Computing. Proceedings of the Fourth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’19) , С. 120-130, Springer, Cham, 2020, ISBN: 978-30-3050-096-2.
Аннотация | Ссылки | BibTeX | Altmetric | Метки: data warehouse, genetic algorithm, innovation index, Innovativeness, Intelligent agent, novelty, relevance, subject search
@inproceedings{V.K.2020,
title = {Features of Data Warehouse Support Based on a Search Agent and an Evolutionary Model for Innovation Information Selection},
author = {Ivanov V.K. and Palyukh B.V. and Sotnikov A.N.},
url = {https://disk.yandex.ru/i/FT7JLsQmXPIMgQ
https://doi.org/10.1007/978-3-030-50097-9_13},
doi = {10.1007/978-3-030-50097-9_13},
isbn = {978-30-3050-096-2},
year = {2020},
date = {2020-00-01},
urldate = {2020-00-01},
booktitle = {Advances in Intelligent Systems and Computing. Proceedings of the Fourth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’19) },
volume = {1156},
pages = {120-130},
publisher = {Springer, Cham},
abstract = {Innovations are the key factor of the competitiveness of any modern business. This paper gives the systematized results of investigations on the data warehouse technology with an automatic data-replenishment from heterogeneous sources. The data warehouse is suggested to contain information about objects having a significant innovative potential. The selection mechanism for such information is based on quantitative evaluation of the objects innovativeness, in particular their technological novelty and relevance for them. The article presents the general architecture of the data warehouse, describes innovativeness indicators, considers Theory of Evidence application for processing incomplete and fuzzy information, defines basic ideas of measurement processing procedure to compute probabilistic values of innovativeness components, summarizes using evolutional approach in forming the linguistic model of object archetype, gives information about an experimental check if the model developed is adequate. The results of these investigations can be used for business planning, forecasting technological development, investment project expertise.
Ivanov, V.K., Palyukh, B.V., Sotnikov, A.N. (2020). Features of Data Warehouse Support Based on a Search Agent and an Evolutionary Model for Innovation Information Selection. In: Kovalev, S., Tarassov, V., Snasel, V., Sukhanov, A. (eds) Proceedings of the Fourth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’19). IITI 2019. Advances in Intelligent Systems and Computing, vol 1156. Springer, Cham. https://doi.org/10.1007/978-3-030-50097-9_13 (Scopus)},
keywords = {data warehouse, genetic algorithm, innovation index, Innovativeness, Intelligent agent, novelty, relevance, subject search},
pubstate = {published},
tppubtype = {inproceedings}
}
Innovations are the key factor of the competitiveness of any modern business. This paper gives the systematized results of investigations on the data warehouse technology with an automatic data-replenishment from heterogeneous sources. The data warehouse is suggested to contain information about objects having a significant innovative potential. The selection mechanism for such information is based on quantitative evaluation of the objects innovativeness, in particular their technological novelty and relevance for them. The article presents the general architecture of the data warehouse, describes innovativeness indicators, considers Theory of Evidence application for processing incomplete and fuzzy information, defines basic ideas of measurement processing procedure to compute probabilistic values of innovativeness components, summarizes using evolutional approach in forming the linguistic model of object archetype, gives information about an experimental check if the model developed is adequate. The results of these investigations can be used for business planning, forecasting technological development, investment project expertise.
Ivanov, V.K., Palyukh, B.V., Sotnikov, A.N. (2020). Features of Data Warehouse Support Based on a Search Agent and an Evolutionary Model for Innovation Information Selection. In: Kovalev, S., Tarassov, V., Snasel, V., Sukhanov, A. (eds) Proceedings of the Fourth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’19). IITI 2019. Advances in Intelligent Systems and Computing, vol 1156. Springer, Cham. https://doi.org/10.1007/978-3-030-50097-9_13 (Scopus)
Ivanov, V.K., Palyukh, B.V., Sotnikov, A.N. (2020). Features of Data Warehouse Support Based on a Search Agent and an Evolutionary Model for Innovation Information Selection. In: Kovalev, S., Tarassov, V., Snasel, V., Sukhanov, A. (eds) Proceedings of the Fourth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’19). IITI 2019. Advances in Intelligent Systems and Computing, vol 1156. Springer, Cham. https://doi.org/10.1007/978-3-030-50097-9_13 (Scopus)
2.
Иванов В.К., Палюх Б.В.
Реализация экспертной системы для оценки инновационности технических решений Статья в журнале
Опубликовано в: Программные продукты и системы (Software & Systems), том 32, № 4, С. 696–707, 2019.
Аннотация | Ссылки | BibTeX | Altmetric | Метки: certificate, data warehouse, evaluation, expert system, implementability, innovation, innovation index, invention, relevance, term, востребованность, изобретение, имплементируемость, инновационность, оценка, свидетельство, терм, хранилище данных, экспертная система
@article{nokey,
title = {Реализация экспертной системы для оценки инновационности технических решений},
author = {Иванов В.К. and Палюх Б.В.},
url = {https://disk.yandex.ru/i/Q7XagjMkCUl6ew
http://www.swsys.ru/index.php?page=article&id=4658&ysclid=l6y3q7vn1k593006109},
doi = {10.15827/0236-235X.128.696-707},
year = {2019},
date = {2019-12-31},
urldate = {2022-08-17},
journal = {Программные продукты и системы (Software & Systems)},
volume = {32},
number = {4},
pages = {696–707},
publisher = {ЦПС},
abstract = {Представлено возможное решение задачи алгоритмизации количественной оценки показателей инновационности технических изделий, изобретений, технологий. Введены понятия технологической новизны, востребованности и имплементируемости – составных частей критерия инновационности продукта. Предложены модель и алгоритм вычисления каждого из указанных показателей инновационности в условиях неполноты и неточности, а иногда и противоречивости исходной информации. В статье описывается разработанное специализированное ПО, которое является перспективным методологическим инструментом для использования интервальных оценок в соответствии с теорией свидетельств. Эти оценки применяются при анализе сложных многокомпонентных систем, агрегации больших объемов нечетких и неполных данных различной структуры. Представлены состав и структура мультиагентной экспертной системы, назначение которой – групповая обработка результатов измерений и оценок значений показателей инновационности объектов. Определяются активные элементы системы, их функциональность, роли, порядок взаимодействия, входные и выходные интерфейсы, общий алгоритм функционирования ПО. Описывается реализация программных модулей, приводится пример решения конкретной задачи по определению уровня инновационности технических изделий. Разработанные подход, модели, методика и ПО могут быть использованы в реализации технологии хранилища характеристик объектов, обладающих значительным инновационным потенциалом. Формализация исходных данных задачи существенно повышает адаптивность предложенных методов к различным предметным областям. Появляется возможность обработки данных различной природы, полученных в результате опроса экспертов, из поисковой системы или даже с измерительного устройства, что способствует повышению практической значимости представленной разработки.
Implementing an expert system to evaluate technical solutions innovativeness
V.K. Ivanov 1, I.V. Obraztsov, B.V. Palyukh
The paper presents a possible solution to the problem of algorithmization for quantifying innovativeness indicators of technical products, inventions and technologies. The concepts of technological novelty, relevance and implementability as components of product innovation criterion are introduced. Authors propose a model and algorithm to calculate every of these indicators of innovativeness under conditions of incompleteness and inaccuracy, and sometimes inconsistency of the initial information. The paper describes the developed specialized software that is a promising methodological tool for using interval estimations in accordance with the theory of evidence. These estimations are used in the analysis of complex multicomponent systems, aggregations of large volumes of fuzzy and incomplete data of various structures. Composition and structure of a multi-agent expert system are presented. The purpose of such system is to process groups of measurement results and to estimate indicators values of objects innovativeness. The paper defines active elements of the system, their functionality, roles, interaction order, input and output interfaces, as well as the general software functioning algorithm. It describes implementation of software modules and gives an example of solving a specific problem to determine the level of technical products innovation. The developed approach, models, methodology and software can be used to implement the storage technology to store the characteristics of objects with significant innovative potential. Formalization of the task's initial data significantly increases the possibility to adapt the proposed methods to various subject areas. There appears an opportunity to process data of various natures, obtained during experts’ surveys, from a search system or even a measuring device, which helps to increase the practical significance of the presented research.},
keywords = {certificate, data warehouse, evaluation, expert system, implementability, innovation, innovation index, invention, relevance, term, востребованность, изобретение, имплементируемость, инновационность, оценка, свидетельство, терм, хранилище данных, экспертная система},
pubstate = {published},
tppubtype = {article}
}
Представлено возможное решение задачи алгоритмизации количественной оценки показателей инновационности технических изделий, изобретений, технологий. Введены понятия технологической новизны, востребованности и имплементируемости – составных частей критерия инновационности продукта. Предложены модель и алгоритм вычисления каждого из указанных показателей инновационности в условиях неполноты и неточности, а иногда и противоречивости исходной информации. В статье описывается разработанное специализированное ПО, которое является перспективным методологическим инструментом для использования интервальных оценок в соответствии с теорией свидетельств. Эти оценки применяются при анализе сложных многокомпонентных систем, агрегации больших объемов нечетких и неполных данных различной структуры. Представлены состав и структура мультиагентной экспертной системы, назначение которой – групповая обработка результатов измерений и оценок значений показателей инновационности объектов. Определяются активные элементы системы, их функциональность, роли, порядок взаимодействия, входные и выходные интерфейсы, общий алгоритм функционирования ПО. Описывается реализация программных модулей, приводится пример решения конкретной задачи по определению уровня инновационности технических изделий. Разработанные подход, модели, методика и ПО могут быть использованы в реализации технологии хранилища характеристик объектов, обладающих значительным инновационным потенциалом. Формализация исходных данных задачи существенно повышает адаптивность предложенных методов к различным предметным областям. Появляется возможность обработки данных различной природы, полученных в результате опроса экспертов, из поисковой системы или даже с измерительного устройства, что способствует повышению практической значимости представленной разработки.
Implementing an expert system to evaluate technical solutions innovativeness
V.K. Ivanov 1, I.V. Obraztsov, B.V. Palyukh
The paper presents a possible solution to the problem of algorithmization for quantifying innovativeness indicators of technical products, inventions and technologies. The concepts of technological novelty, relevance and implementability as components of product innovation criterion are introduced. Authors propose a model and algorithm to calculate every of these indicators of innovativeness under conditions of incompleteness and inaccuracy, and sometimes inconsistency of the initial information. The paper describes the developed specialized software that is a promising methodological tool for using interval estimations in accordance with the theory of evidence. These estimations are used in the analysis of complex multicomponent systems, aggregations of large volumes of fuzzy and incomplete data of various structures. Composition and structure of a multi-agent expert system are presented. The purpose of such system is to process groups of measurement results and to estimate indicators values of objects innovativeness. The paper defines active elements of the system, their functionality, roles, interaction order, input and output interfaces, as well as the general software functioning algorithm. It describes implementation of software modules and gives an example of solving a specific problem to determine the level of technical products innovation. The developed approach, models, methodology and software can be used to implement the storage technology to store the characteristics of objects with significant innovative potential. Formalization of the task's initial data significantly increases the possibility to adapt the proposed methods to various subject areas. There appears an opportunity to process data of various natures, obtained during experts’ surveys, from a search system or even a measuring device, which helps to increase the practical significance of the presented research.
Implementing an expert system to evaluate technical solutions innovativeness
V.K. Ivanov 1, I.V. Obraztsov, B.V. Palyukh
The paper presents a possible solution to the problem of algorithmization for quantifying innovativeness indicators of technical products, inventions and technologies. The concepts of technological novelty, relevance and implementability as components of product innovation criterion are introduced. Authors propose a model and algorithm to calculate every of these indicators of innovativeness under conditions of incompleteness and inaccuracy, and sometimes inconsistency of the initial information. The paper describes the developed specialized software that is a promising methodological tool for using interval estimations in accordance with the theory of evidence. These estimations are used in the analysis of complex multicomponent systems, aggregations of large volumes of fuzzy and incomplete data of various structures. Composition and structure of a multi-agent expert system are presented. The purpose of such system is to process groups of measurement results and to estimate indicators values of objects innovativeness. The paper defines active elements of the system, their functionality, roles, interaction order, input and output interfaces, as well as the general software functioning algorithm. It describes implementation of software modules and gives an example of solving a specific problem to determine the level of technical products innovation. The developed approach, models, methodology and software can be used to implement the storage technology to store the characteristics of objects with significant innovative potential. Formalization of the task's initial data significantly increases the possibility to adapt the proposed methods to various subject areas. There appears an opportunity to process data of various natures, obtained during experts’ surveys, from a search system or even a measuring device, which helps to increase the practical significance of the presented research.
3.
Иванов В.К.
Применение теории свидетельств для количественной оценки показателей инновационности объекта Статья в сборнике
Опубликовано в: Труды 16-й Национальной конференции по искусственному интеллекту с международным участием КИИ–2018 : т. 1 : Секция 3 : Интеллектуальные системы поддержки принятия решений и управления, С. 168-175, 2018, ISBN: 978-5-600-02247-8.
Аннотация | Ссылки | BibTeX | Метки: assessment, engineering solution, evidence theory, innovation, innovation index, novelty, relevance, востребованность, инновационность, новизна, оценка, теория свидетельств, техническое решение
@inproceedings{nokey,
title = {Применение теории свидетельств для количественной оценки показателей инновационности объекта},
author = {Иванов В.К.},
url = {https://disk.yandex.ru/i/8B0LBaC1bp3bUQ},
isbn = {978-5-600-02247-8},
year = {2018},
date = {2018-11-30},
urldate = {2018-11-30},
booktitle = {Труды 16-й Национальной конференции по искусственному интеллекту с международным участием КИИ–2018 : т. 1 : Секция 3 : Интеллектуальные системы поддержки принятия решений и управления},
volume = {1},
pages = {168-175},
abstract = {Рассмотрен подход к количественной оценке показателей инновационности объектов различной природы. Предложена модель оценки, основанная на использовании результатов поиска информации об объектах в базах данных. Представлено специфическое применение теории свидетельств. Описана лингвистическая модель, технология обработки результатов измерений, полученных из поисковых систем, методика оценки достоверности источника данных. На примерах показана правомерность подхода.
V.K. Ivanov. Some Results of Experimental Check of The Model of the Object Innovativeness Quantitative Evaluation
The paper presents the results of the experiments that were conducted to confirm the main ideas of the proposed approach to determining the objects innovativeness. This approach assumed that the product life cycle of whose descriptions are placed in di¥erent data warehouses is adequate. The proposed formal model allows us to calculate the quantitative value of the additive evaluation criterion of objects innovativeness. The obtained experimental data make it possible to evaluate the adopted approach correctness.
},
keywords = {assessment, engineering solution, evidence theory, innovation, innovation index, novelty, relevance, востребованность, инновационность, новизна, оценка, теория свидетельств, техническое решение},
pubstate = {published},
tppubtype = {inproceedings}
}
Рассмотрен подход к количественной оценке показателей инновационности объектов различной природы. Предложена модель оценки, основанная на использовании результатов поиска информации об объектах в базах данных. Представлено специфическое применение теории свидетельств. Описана лингвистическая модель, технология обработки результатов измерений, полученных из поисковых систем, методика оценки достоверности источника данных. На примерах показана правомерность подхода.
V.K. Ivanov. Some Results of Experimental Check of The Model of the Object Innovativeness Quantitative Evaluation
The paper presents the results of the experiments that were conducted to confirm the main ideas of the proposed approach to determining the objects innovativeness. This approach assumed that the product life cycle of whose descriptions are placed in di¥erent data warehouses is adequate. The proposed formal model allows us to calculate the quantitative value of the additive evaluation criterion of objects innovativeness. The obtained experimental data make it possible to evaluate the adopted approach correctness.
V.K. Ivanov. Some Results of Experimental Check of The Model of the Object Innovativeness Quantitative Evaluation
The paper presents the results of the experiments that were conducted to confirm the main ideas of the proposed approach to determining the objects innovativeness. This approach assumed that the product life cycle of whose descriptions are placed in di¥erent data warehouses is adequate. The proposed formal model allows us to calculate the quantitative value of the additive evaluation criterion of objects innovativeness. The obtained experimental data make it possible to evaluate the adopted approach correctness.
4.
Ivanov V.K.
Computational Model to Quantify Object Innovativeness Статья в сборнике
Опубликовано в: Proceedings of the II International Scientific and Practical Conference “Fuzzy Technologies in the Industry – FTI 2018” , С. 249-258, Ulyanovsk, 2018, ISSN: 1613-0073.
Аннотация | Ссылки | BibTeX | Метки: assessment, innovation, innovation index, Innovativeness, linguistic model, novelty, relevance
@inproceedings{nokey,
title = {Computational Model to Quantify Object Innovativeness},
author = {Ivanov V.K.},
url = {https://disk.yandex.ru/i/wHOy6DTBYeabog},
issn = {1613-0073},
year = {2018},
date = {2018-10-31},
urldate = {2022-08-29},
booktitle = {Proceedings of the II International Scientific and Practical Conference “Fuzzy Technologies in the Industry – FTI 2018” },
volume = {2258},
pages = {249-258},
publisher = {Ulyanovsk},
abstract = {The article considers the quantitative assessment approach to the innovativeness of different objects. The proposed assessment model is based on the object data retrieval from various databases including the Internet. We present an object linguistic model, the processing technique for the measurement results including the results retrieved from the different search engines, and the evaluating technique of the source credibility. Empirical research of the computational model adequacy includes the acquisition and preprocessing of patent data from different databases and the computation of invention innovativeness values: their novelty and relevance. The experiment results, namely the comparative assessments of innovativeness values and major trends, show the models developed are sufficiently adequate and can be used in further research.},
keywords = {assessment, innovation, innovation index, Innovativeness, linguistic model, novelty, relevance},
pubstate = {published},
tppubtype = {inproceedings}
}
The article considers the quantitative assessment approach to the innovativeness of different objects. The proposed assessment model is based on the object data retrieval from various databases including the Internet. We present an object linguistic model, the processing technique for the measurement results including the results retrieved from the different search engines, and the evaluating technique of the source credibility. Empirical research of the computational model adequacy includes the acquisition and preprocessing of patent data from different databases and the computation of invention innovativeness values: their novelty and relevance. The experiment results, namely the comparative assessments of innovativeness values and major trends, show the models developed are sufficiently adequate and can be used in further research.
5.
Ivanov V.K., Glebova A.G., Obrazthov I.V.
Quantitative Assessment of Solution Innovation in Engineering Education Статья в сборнике
Опубликовано в: 2018 IV International Conference on Information Technologies in Engineering Education (Inforino), 2018, ISBN: 978-1-5386-5832-1.
Аннотация | Ссылки | BibTeX | Altmetric | Метки: assessment, education, electronic information and educational environment, engineering education, engineering solution, iee, innovation, innovation index, novelty, relevance
@inproceedings{nokey,
title = {Quantitative Assessment of Solution Innovation in Engineering Education},
author = {Ivanov V.K. and Glebova A.G. and Obrazthov I.V.},
url = {https://disk.yandex.ru/i/09kY-liNmQvEVw},
doi = {10.1109/INFORINO.2018.8581799},
isbn = {978-1-5386-5832-1},
year = {2018},
date = {2018-10-30},
urldate = {2018-10-30},
booktitle = {2018 IV International Conference on Information Technologies in Engineering Education (Inforino)},
abstract = {The article discusses the quantitative assessment approach to the innovation of engineering system components. The validity of the approach is based on the expert appraisal of the university’s electronic information educational environment components and the measurement of engineering solution innovation in engineering education. The implementation of batch processing of object innovation assessments is justified and described.
},
keywords = {assessment, education, electronic information and educational environment, engineering education, engineering solution, iee, innovation, innovation index, novelty, relevance},
pubstate = {published},
tppubtype = {inproceedings}
}
The article discusses the quantitative assessment approach to the innovation of engineering system components. The validity of the approach is based on the expert appraisal of the university’s electronic information educational environment components and the measurement of engineering solution innovation in engineering education. The implementation of batch processing of object innovation assessments is justified and described.
6.
Иванов В.К., Виноградова Н.В.
Современные методы автоматизированного извлечения ключевых слов из текста Статья в журнале
Опубликовано в: Информационные ресурсы России, № 4, С. 13-18, 2016, ISSN: 0204-3653.
Аннотация | Ссылки | BibTeX | Метки: data centre, keyword, method, relevance, search, selection, semantics, spectral, statistical, text, word-combination, выделение, гибридный, ключевое слово, лингвистика, метод, поиск, релевантность, семантика, словосочетание, спектральный, статистический, текст
@article{nokey,
title = {Современные методы автоматизированного извлечения ключевых слов из текста},
author = {Иванов В.К. and Виноградова Н.В.},
editor = {ключевое слово, метод, выделение, текст, семантика, гибридный, лингвистика, словосочетание, спектральный, статистический, поиск, релевантность, keyword, method, selection, text, semantics, hybrid, linguistics, word-combination, spectral, statistical, search, relevance, data centre},
url = {https://disk.yandex.ru/i/Zi2TSkY7hI89uA},
issn = {0204-3653},
year = {2016},
date = {2016-12-31},
urldate = {2016-12-31},
journal = {Информационные ресурсы России},
number = {4},
pages = {13-18},
publisher = {Москва},
abstract = {Cтатья посвящена актуальной на сегодняшний день проблеме – методам автоматизированного извлечения ключевых слов из текста. В статье представлен аналитический обзор материалов по этой тематике. Особенностью обзора является широкое использование для анализа работ российских авторов, изданных за последнее время, что должно показать текущий уровень отечественных исследований и помочь определить потенциальные точки их дальнейшего развития. В статье классифицированы основные методы автоматизированного извлечения ключевых слов, выделены их особенности, определены применимость, описаны достоинства и недостатки. Дается систематизированный обзор исследований и разработок, основанных на лингвистических, статистических, спектральных и гибридных методах. Статья может быть полезна разработчикам информационно-поисковых систем, специалистам в области оптимизации поисковых процедур, исследователям технологий информационного поиска, патентоведам, работникам библиотечной сферы.
Vinogradova N.V., Ivanov V.K. Modern methods of automated extraction of keywords from text
The article is devoted to the up to date problem, namely the methods of automated extraction of keywords from a text. The article presents the analytical review on the problem. The speciality of a review is a wide range of works by Russian authors published lately that can indicate the current level of home investigations and help to define the further development potentials. The authors made an effort to classify the basic methods of the automated extraction of keywords, to emphasize their features, to define their potential for use, to specify strengths and shortcomings. The systemization review of the R&D based on linguistic, statistical, spectral and hybrid methods is conducted. The article may be beneficial to the information storage and retrieval system developers, experts in search procedure optimization, explorers of information search technologies, patent specialists, workers of libraries.},
keywords = {data centre, keyword, method, relevance, search, selection, semantics, spectral, statistical, text, word-combination, выделение, гибридный, ключевое слово, лингвистика, метод, поиск, релевантность, семантика, словосочетание, спектральный, статистический, текст},
pubstate = {published},
tppubtype = {article}
}
Cтатья посвящена актуальной на сегодняшний день проблеме – методам автоматизированного извлечения ключевых слов из текста. В статье представлен аналитический обзор материалов по этой тематике. Особенностью обзора является широкое использование для анализа работ российских авторов, изданных за последнее время, что должно показать текущий уровень отечественных исследований и помочь определить потенциальные точки их дальнейшего развития. В статье классифицированы основные методы автоматизированного извлечения ключевых слов, выделены их особенности, определены применимость, описаны достоинства и недостатки. Дается систематизированный обзор исследований и разработок, основанных на лингвистических, статистических, спектральных и гибридных методах. Статья может быть полезна разработчикам информационно-поисковых систем, специалистам в области оптимизации поисковых процедур, исследователям технологий информационного поиска, патентоведам, работникам библиотечной сферы.
Vinogradova N.V., Ivanov V.K. Modern methods of automated extraction of keywords from text
The article is devoted to the up to date problem, namely the methods of automated extraction of keywords from a text. The article presents the analytical review on the problem. The speciality of a review is a wide range of works by Russian authors published lately that can indicate the current level of home investigations and help to define the further development potentials. The authors made an effort to classify the basic methods of the automated extraction of keywords, to emphasize their features, to define their potential for use, to specify strengths and shortcomings. The systemization review of the R&D based on linguistic, statistical, spectral and hybrid methods is conducted. The article may be beneficial to the information storage and retrieval system developers, experts in search procedure optimization, explorers of information search technologies, patent specialists, workers of libraries.
Vinogradova N.V., Ivanov V.K. Modern methods of automated extraction of keywords from text
The article is devoted to the up to date problem, namely the methods of automated extraction of keywords from a text. The article presents the analytical review on the problem. The speciality of a review is a wide range of works by Russian authors published lately that can indicate the current level of home investigations and help to define the further development potentials. The authors made an effort to classify the basic methods of the automated extraction of keywords, to emphasize their features, to define their potential for use, to specify strengths and shortcomings. The systemization review of the R&D based on linguistic, statistical, spectral and hybrid methods is conducted. The article may be beneficial to the information storage and retrieval system developers, experts in search procedure optimization, explorers of information search technologies, patent specialists, workers of libraries.
7.
Ivanov V.K., Palyukh B.V., Sotnikov A.N.
Efficiency of Genetic Algorithm For Subject Search Queries Статья в журнале
Опубликовано в: Lobachevskii Journal of Mathematics, том 37, № 3, С. 244–254, 2016, ISSN: 1995-0802, (Ivanov V.K., Palyukh B.V., Sotnikov A.N. Efficiency of Genetic Algorithm For Subject Search Queries. Lobachevskii Journal of Mathematics, 2016, Vol. 37, No. 3, pp. 244–254. Pleiades Publishing, Ltd., 2016.).
Аннотация | Ссылки | BibTeX | Altmetric | Метки: convergence, data centre, fitness function, genetic algorithm, innovation index, population, ranking, relevance, search precision, search query
@article{101_b0a4bd11-a8c6-4980-875a-9f7caf882815,
title = {Efficiency of Genetic Algorithm For Subject Search Queries},
author = {Ivanov V.K. and Palyukh B.V. and Sotnikov A.N.},
url = {https://disk.yandex.ru/i/DWS1H4M7CMLXxQ},
doi = {10.1134/S1995080216030124},
issn = {1995-0802},
year = {2016},
date = {2016-09-29},
urldate = {2025-01-21},
journal = {Lobachevskii Journal of Mathematics},
volume = {37},
number = {3},
pages = {244–254},
publisher = {Pleiades Publishing, Ltd.},
abstract = {<p>The article presents and generalizes the results on some performance indicators of genetic algorithm developed by authors and applied to effective search queries and selection of relevant results after document subject search. It is shown that the developed technology expands opportunities of semantic search and increases the number of the found relevant results. In particular, we made an effort to show the ability of the developed algorithm to achieve the neighborhood of the fitness function in a finite number of steps, to provide higher precision of search in comparison with the well-known search engines of the Internet as well as to provide the acceptable semantic relevance of the found documents.</p>},
note = {Ivanov V.K., Palyukh B.V., Sotnikov A.N. Efficiency of Genetic Algorithm For Subject Search Queries. Lobachevskii Journal of Mathematics, 2016, Vol. 37, No. 3, pp. 244–254. Pleiades Publishing, Ltd., 2016.},
keywords = {convergence, data centre, fitness function, genetic algorithm, innovation index, population, ranking, relevance, search precision, search query},
pubstate = {published},
tppubtype = {article}
}
<p>The article presents and generalizes the results on some performance indicators of genetic algorithm developed by authors and applied to effective search queries and selection of relevant results after document subject search. It is shown that the developed technology expands opportunities of semantic search and increases the number of the found relevant results. In particular, we made an effort to show the ability of the developed algorithm to achieve the neighborhood of the fitness function in a finite number of steps, to provide higher precision of search in comparison with the well-known search engines of the Internet as well as to provide the acceptable semantic relevance of the found documents.</p>
8.
Ivanov V.K., Palyukh B.V., Sotnikov A.N.
Intelligent subject search support in science and education Статья в сборнике
Опубликовано в: Innovative Information Technologies : Materials of the III International scientific-рractical conference I2T-2014. Part 2. Innovative Information Technologies in Science, С. 34-40, Москва, 2014, ISSN: 2303-9728, (Ivanov V.K., Palyukh B.V., Sotnikov A.N. Intelligent subject search support in science and education // Innovative Information Technologies : Materials of the III International scientific-рractical conference I2T-2014. Part 2. Innovative Information Technologies in Science. – M., 2014. - P. 34-40.).
Ссылки | BibTeX | Метки: data centre, data mining, data warehouse, education, filtering, fitness, genetic algorithm, innovation, innovation index, population, ranking, relevance, science, search, search query
@inproceedings{107_4f8d4848-dc2d-4155-afcb-561453cc4b27,
title = {Intelligent subject search support in science and education},
author = {Ivanov V.K. and Palyukh B.V. and Sotnikov A.N.},
url = {https://disk.yandex.ru/i/jLPLFrgAkYz6dg},
issn = {2303-9728},
year = {2014},
date = {2014-04-29},
urldate = {2025-01-23},
booktitle = {Innovative Information Technologies : Materials of the III International scientific-рractical conference I2T-2014. Part 2. Innovative Information Technologies in Science},
pages = {34-40},
publisher = {Москва},
note = {Ivanov V.K., Palyukh B.V., Sotnikov A.N. Intelligent subject search support in science and education // Innovative Information Technologies : Materials of the III International scientific-рractical conference I2T-2014. Part 2. Innovative Information Technologies in Science. – M., 2014. - P. 34-40.},
keywords = {data centre, data mining, data warehouse, education, filtering, fitness, genetic algorithm, innovation, innovation index, population, ranking, relevance, science, search, search query},
pubstate = {published},
tppubtype = {inproceedings}
}
9.
Ivanov V.K., Palyukh B.V., Sotnikov A.N.
Approaches to the Intelligent Subject Search Статья в сборнике
Опубликовано в: Federated Conference on Computer Science and Information Systems (FedCSIS'2014) (September 7-10, 2014. Warsaw, Poland). Annals of Computer Science and Information Systems. Volume 3. Position Papers, С. 13-20, Warszawa: PTI, 2014, (Ivanov V.K., Palyukh B.V., Sotnikov A.N. Approaches to the Intelligent Subject Search // Federated Conference on Computer Science and Information Systems (FedCSIS'2014) (September 7-10, 2014. Warsaw, Poland). Annals of Computer Science and Information Systems. Volume 3. Position Papers, DOI 10.15439/978-83-60810-57-6. - Warsawa, 2014. - P. 13-20).
Аннотация | Ссылки | BibTeX | Altmetric | Метки: data centre, data mining, data warehouse, education, filtering, fitness, genetic algorithm, innovation, innovation index, population, ranking, relevance, science, search, search query
@inproceedings{108_1f69f485-7466-46d2-8628-a25cbfc5e063,
title = {Approaches to the Intelligent Subject Search},
author = {Ivanov V.K. and Palyukh B.V. and Sotnikov A.N.},
url = {https://disk.yandex.ru/i/8CvNhqvF1S45gQ},
doi = {10.15439/978-83-60810-57-6},
year = {2014},
date = {2014-01-23},
urldate = {2025-01-23},
booktitle = {Federated Conference on Computer Science and Information Systems (FedCSIS'2014) (September 7-10, 2014. Warsaw, Poland). Annals of Computer Science and Information Systems. Volume 3. Position Papers},
pages = {13-20},
publisher = {Warszawa: PTI},
abstract = {<p>This article presents main results of the pilot study of approaches to the subject information search based on automated semantic processing of mass scientific and technical data. The authors focus on technology of building and qualification of search queries with the following filtering and ranking of search data. Software architecture, specific features of subject search and research results application are considered.</p>},
note = {Ivanov V.K., Palyukh B.V., Sotnikov A.N. Approaches to the Intelligent Subject Search // Federated Conference on Computer Science and Information Systems (FedCSIS'2014) (September 7-10, 2014. Warsaw, Poland). Annals of Computer Science and Information Systems. Volume 3. Position Papers, DOI 10.15439/978-83-60810-57-6. - Warsawa, 2014. - P. 13-20},
keywords = {data centre, data mining, data warehouse, education, filtering, fitness, genetic algorithm, innovation, innovation index, population, ranking, relevance, science, search, search query},
pubstate = {published},
tppubtype = {inproceedings}
}
<p>This article presents main results of the pilot study of approaches to the subject information search based on automated semantic processing of mass scientific and technical data. The authors focus on technology of building and qualification of search queries with the following filtering and ranking of search data. Software architecture, specific features of subject search and research results application are considered.</p>
Я подготовил и опубликовал довольно много печатных материалов. И, готовя к публикации очередной материал, я каждый раз помнил основное правило — публиковать результаты работы. Не писал текст для того, чтобы написать статью или отчет. Поэтому мне трудно найти свои работу, которая вызывала бы у меня чувство неловкости.
Также отмечу, что писал и сейчас пишу довольно медленно. Для серьезных статей хорошо, если получается одна страница в день. Многократно правлю текст, пытаясь предельно точно передать свою мысль. Не всегда удаётся, но стараюсь. И, как правило, начинаю с плана, в котором фиксирую предполагаемые структуру и содержание текста. Помогает.
Результаты см. выше.