Noisy Channel

Intelligent system for user groups socialization with similar interests

The article develops a general architectural system of socialization of groups of users with similar interests and functional requirements for it. To process a large part of the information, the system is implemented using the methods of fuzzy text information search and machine learning. thus, N-gram, selection expansion and structured Noisy Channel models are applied. A feature of the implementation is the processing of the text, the analysis of words in the text and the formation of evaluations.

Information Support for Personalities Socialization Processes Based on Common Interests

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.