Designing an Adaptive Electronic Document Management System Based on Neural Network Architecture

Artem Obukhov

Abstract


The article deals with the issues of design automation of adaptive electronic document management systems. Automation of the processes of analysis, processing and transmission of information in the development of information systems will reduce the complexity of implementation, time and material costs, free up the resources of developers to solve more complex and creative problems. One of the ways to automate these processes is the use of machine learning methods, however, without a formalized methodological and mathematical apparatus, it is impossible to provide a comprehensive solution to the problem. The article describes the approbation of a neural network architecture, including a set of approaches and methods based on neural network technologies, using the example of the subject area of electronic document management systems (EDMS). The structure of an adaptive EDMS, implemented in accordance with this architecture, is presented. In the course of experimental research, two test EDMS were implemented: the classical one, developed according to the RAD methodology and the MVC pattern, and the adaptive one, the design of which was carried out within the framework of a neural network architecture. As a result, a decrease in the cost (by 24.7%) and complexity (by 32.5%) of the EDMS implementation was achieved, and the adaptability of the system was increased (by 13.6%). There is also an improvement in its quality and an increase in productivity. The results obtained confirm the effectiveness of the proposed approaches and tools.

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References


Nemchinova E. A., Plotnikova N. P., Fedosin S. A. Podgotovka i obrabotka normativno-spravochnoj tekstovoj informacii dlya klassifikacii s pomoshch'yu iskusstvennyh nejronnyh setej //Nelinejnyj mir. 2019. T. 17. №. 2. P. 27-33.

Solomencev YA. K., CHochia P. A. Primenenie nejronnyh setej dlya diagnostiki vida i parametrov iskazhenij izobrazheniya //Informacionnye processy. 2020. T. 20. №. 2. P. 95-103.

Vinokurov A. V. Parametricheskij metod obrabotki videoinformacii na osnove primeneniya nejronnyh setej kak mekhanizm adaptacii razmera izobrazhenij k propusknoj sposobnosti kanala svyazi //Promyshlennye ASU i kontrollery. 2017. №. 6. P. 36-39.

Kislicyn E. V., Panova M. V., ZHernakov R. S. Principy primeneniya nejrosetevyh tekhnologij pri analize bol'shih dannyh //Perspektivy nauki. 2017. №. 9. P. 7-10.

Vitenburg E. A. Arhitektura programmnogo kompleksa intellektual'noj podderzhki prinyatiya reshenij pri proektirovanii sistemy zashchity informacionnoj sistemy predpriyatiya //Vestnik kibernetiki. 2019. №. 4. P. 46-51.

Gajnullin R. N., Rahal Ya., Rizaev I.S., Sharnin L.M.. Prognozirovanie biznes-processov na osnove nejronnyh setej //Vestnik Kazanskogo tekhnologicheskogo universiteta. 2017. T. 20. №. 3. P. 121-124.

Danilov A. D., Mugatina V. M. Reshenie zadachi optimizacii regressionnogo testirovaniya s ispol'zovaniem nejrosetevogo podhoda //Modelirovanie, optimizaciya i informacionnye tekhnologii. 2020. T. 8. №. 1. P. 35-36.

Obuhov A.D., Krasnyanskij M.N. Nejrosetevaya arhitektura informacionnyh sistem // Vestnik Udmurtskogo universiteta. Matematika. Mekhanika. Komp'yuternye nauki. 2019. T. 29. Vyp. 3. P. 438-455.

Obukhov A., Krasnyanskiy M., Nikolyukin M. Algorithm of adaptation of electronic document management system based on machine learning technology //Progress in Artificial Intelligence. 2020. P. 1-17.

Krasnyanskiy M., Ostroukh A., Karpushkin S., Obukhov A. Formulation of the Problem of Structural and Parametric Synthesis of Electronic Document Management System of Research and Education Institution //Global Journal of Pure and Applied Mathematics. 2016. T. 12. №. 3. P. 2395-2409.

Stefanova N. A., Kurbangeldyev D. Ocenka stoimosti razrabotki programmnogo obespecheniya //Aktual'nye voprosy sovremennoj ekonomiki. 2020. №. 1. P. 67-72.

Yakovlev Yu. S., Kurzanceva L. I. O razvitii adaptivnogo cheloveko-mashinnogo interfejsa i kriteriyah ego ocenki v uchebnyh sistemah //Obrazovatel'nye tekhnologii i obshchestvo. 2013. T. 16. №. 1. P. 547-563.

Bastien J. M. C., Scapin D. L. Evaluating a user interface with ergonomic criteria // International Journal of Human‐Computer Interaction, 1995. T. 7. №. 2. P. 105-121.

Lipaev V. V. Kachestvo krupnomasshtabnyh programmnyh sredstv. Directmedia, 2015. 231 p.

Burdyko T. G., Bushmeleva K. I. Pokazateli kachestva programmnyh sredstv //Vestnik kibernetiki. 2019. №. 1. P. 60-66.

Azhmuhamedov I. M., Knyazeva O. M. Kompleksnyj kriterij ocenki kachestva informacionnyh sistem //Aktual'nye problemy gumanitarnyh i estestvennyh nauk. 2017. №. 4-6. P. 14-17.

Bulanov V. A., Fomichyova O. E. Sovremennye problemy ocenki proizvoditel'nosti informacionnyh sistem //Promyshlennye ASU i kontrollery. 2020. №. 1. P. 49-54.


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