Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
Development of a corporate knowledge management system using machine learning techniques. / Tkachenko, Elena; Rogova, Elena; Bodrunov, Sergey; Romanov, Igor.
Proceedings of the 22nd European Conference on Knowledge Management, ECKM 2021. ред. / Alexeis Garcia-Perez; Lyndon Simkin. Academic Conferences and Publishing International Limited, 2021. стр. 757-767 (Proceedings of the European Conference on Knowledge Management, ECKM).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
}
TY - GEN
T1 - Development of a corporate knowledge management system using machine learning techniques
AU - Tkachenko, Elena
AU - Rogova, Elena
AU - Bodrunov, Sergey
AU - Romanov, Igor
N1 - Publisher Copyright: © The Authors, 2021. All Rights Reserved.
PY - 2021
Y1 - 2021
N2 - Modern knowledge management systems are often essentially data libraries that differ only in the degree of structuring and processing methodology. From the point of view of management theory, the management process consists of such stages as analysis, goal setting, planning, implementation and control. In knowledge management, as a rule, only the analytical stage is presented. The process of management itself is limited by the difficulty of forecasting the processes of development of the system of corporate and public knowledge. In our study, we attempted to solve this problem by applying machine learning techniques. The term Machine Learning was used for the first time by Arthur Lee Samuel (1959). Machine learning is a class of artificial intelligence methods, the characteristic feature of which is not a direct solution to the problem, but training in the process of applying solutions to many similar problems. The science of machine learning itself studies methods for constructing algorithms capable of learning from various inputs. As part of this study, we will be interested only in learning with a teacher, which, in turn, is divided into the following subtasks:-Classification tasks; Regression tasks; Ranking tasks; Prediction tasks. The specific feature of learning with a teacher is that there is both a lot of data in which the model searches for patterns, and answers to the forecast of the model as part of its training. We have simulated the forecasting process in relation to the knowledge system of a company operating in the securities market. Machine learning methods have shown high efficiency in solving the entire range of tasks related to knowledge management.
AB - Modern knowledge management systems are often essentially data libraries that differ only in the degree of structuring and processing methodology. From the point of view of management theory, the management process consists of such stages as analysis, goal setting, planning, implementation and control. In knowledge management, as a rule, only the analytical stage is presented. The process of management itself is limited by the difficulty of forecasting the processes of development of the system of corporate and public knowledge. In our study, we attempted to solve this problem by applying machine learning techniques. The term Machine Learning was used for the first time by Arthur Lee Samuel (1959). Machine learning is a class of artificial intelligence methods, the characteristic feature of which is not a direct solution to the problem, but training in the process of applying solutions to many similar problems. The science of machine learning itself studies methods for constructing algorithms capable of learning from various inputs. As part of this study, we will be interested only in learning with a teacher, which, in turn, is divided into the following subtasks:-Classification tasks; Regression tasks; Ranking tasks; Prediction tasks. The specific feature of learning with a teacher is that there is both a lot of data in which the model searches for patterns, and answers to the forecast of the model as part of its training. We have simulated the forecasting process in relation to the knowledge system of a company operating in the securities market. Machine learning methods have shown high efficiency in solving the entire range of tasks related to knowledge management.
KW - Forecasting
KW - Knowledge management
KW - Machine learning
UR - http://www.scopus.com/inward/record.url?scp=85117139957&partnerID=8YFLogxK
U2 - 10.34190/EKM.21.128
DO - 10.34190/EKM.21.128
M3 - Conference contribution
AN - SCOPUS:85117139957
SN - 9781914587061
T3 - Proceedings of the European Conference on Knowledge Management, ECKM
SP - 757
EP - 767
BT - Proceedings of the 22nd European Conference on Knowledge Management, ECKM 2021
A2 - Garcia-Perez, Alexeis
A2 - Simkin, Lyndon
PB - Academic Conferences and Publishing International Limited
T2 - 22nd European Conference on Knowledge Management, ECKM 2021
Y2 - 2 September 2021 through 3 September 2021
ER -
ID: 99665694