Information Support for Personalities Socialization Processes Based on Common Interests

Abstract

The main objective of this article is to create an information system project for socialization by personal interests on the basis of SEO-technologies and methods of machine learning. The main purpose of this information system is to identify the user within the system using neural networks and to select similar users by analysing the user's current information. An information system was created that, through Identity and JWT tokens, provides optimized and secure authorization, logging, and support functions for the current system user session. Finding a face in a user's photo and checking the presence of a similar user in the database are implemented using convolutional and Siamese neural networks. The analysis and formation of similar user beeps were implemented using fuzzy search algorithms, the Levenshtein algorithm and the Noisy Channel model, which made it possible to maximize the automation of the user selection process and to optimize the time spent in this process. Tools have also been created to view other users’ profiles, preferences and private correspondence. All private correspondence and information about it are stored in the current database. Each user of the system can view all information about sent and received messages. The created information system implements the process of user identification, analysis, selection and further socialization of system users.