Algorithm of adaptation of electronic document management system based on machine learning technology
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Algorithm of adaptation of electronic document management system based on machine learning technology Artem Obukhov1
· Mikhail Krasnyanskiy1 · Maxim Nikolyukin1
Received: 6 February 2020 / Accepted: 28 July 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract The topical problem in the development of electronic document management systems (EDMS) is their adaptation and personalization to the individual characteristics of the user. This article discusses the issue of development of an adaptation algorithm using machine learning methods for solving the problem of structural-parametric synthesis of EDMS. In the framework of the presented algorithm, the approaches to the formalization of workflow processes, ways to adapt the interface to the user parameters using artificial neural networks and a comprehensive assessment of the system’s adaptability are considered. The scientific novelty of the approach consists in the algorithmic and software development for automation of the data collection, analysis and interface adaptation through the use and integration of neural networks in the information system. The application of machine learning methods for the formation and adaptation of EDMS interface allows you to automate the process of personalizing it to the user’s individual characteristics, increase the system’s flexibility and provide the best user experience at the first interaction with EDMS based on the intelligent analysis of data about other users. The main scientific results obtained in the article include: formalized criteria for adapting EDMS; algorithm for designing and adapting EDMS; and development of software for adapting EDMS, including a trained neural network and API. Keywords Electronic document management system · Criteria of adaptation · Machine learning · Artificial neural networks
1 Introduction An important problem in the modern software design is the implementation of not only efficient and high-quality information systems, but also adapted to the user’s individual needs, which provides the best user experience, optimization for its equipment, compatibility with already installed The study was supported by the Ministry of Education and Science of the Russian Federation under the Grant of the President of the Russian Federation, MK-74.2020.9. Electronic supplementary material The online version of this article (https://doi.org/10.1007/s13748-020-00214-2) contains supplementary material, which is available to authorized users.
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Artem Obukhov [email protected] Mikhail Krasnyanskiy [email protected] Maxim Nikolyukin [email protected]
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systems [1–3]. Electronic document management systems (EDMS) are also developing in this direction, becoming more and more flexible and adapted [4]. The topic of our study is the use of machine learning methods for adapting EDMS to the individual characteristics of users. The subject of the study is the adaptation algorithm for the EDMS interface. The subject area and literary sources, existing approaches to the adapt
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