Neural network tool environment for creating adaptive application program interfaces

The software is used in almost all areas of human activity. Erroneous actions of the user, which often depend on his emotional state, can lead to negative consequences, especially in production management, technological processes, design activities, medicine, etc. The article is devoted to the problem of personalizing the interface of application programs to user's individual features based on neural network technologies. The novelty of the approach proposed in the work is the prototype interface formation based selecting each menu item separately, which allows forming a personalized interface. The authors propose using a tool environment, which includes a set of components of the interface part for a dynamically generated unique prototype of the interface adapted to each user features. As a tool for selecting interface components, the authors used a deep neural network presented in the form of a multilayer perceptron. The input parameters of the neural network are the distinctive features of users, the outputs are the components of the future prototype interface. Professional, psychophysiological characteristics of users, their demographic characteristics, as well as emotional state were chosen as criteria for adapting the interface part of applications. The output parameters are interface components: text font size and hyperlinks, size and distance between web page elements, tooltip view and context menu, messages to the user, color scheme, availability of a window for information search, etc. Aы a result, the paper presents a developed instrumental environment for creating personalized application program interfaces using neural network technologies. During the software work, users are evaluated by their characteristics using basic tests of the IT sphere and psychology. To determine the emotional tone, age and gender, the system uses the Python Deepface library, which implements an algorithm based on a trained vertical neural network. The implementation of the proposed instrumental environment will ensure comfortable interaction between users and the application.