recommendation systems

APPLICATION OF MACHINE LEARNING FOR USER SENTIMENT ANALYSIS IN INFORMATION AND COMMUNICATION SYSTEMS

The article examines modern methods of applying machine learning and recommendation systems for sentiment analysis of users in information and communication environments. Social networks and digital platforms have become important sources of public opinion, generating large volumes of textual data daily. Traditional analysis methods, such as lexical approaches or classical machine learning algorithms, have limitations in detecting context, sarcasm, slang, and emotional nuances in the text. This complicates the accurate identification of user emotions and socially significant topics.

Recommendation systems techniques based on generative models and matrix factorization: a survey

Collaborative filtering (CF) is a technique that can filter out items that a user might like based on the behaviors and preferences of similar users.  It is a key en-abler technique for an effective recommendation system (RS).  Model-based recommendation systems, a subset of CF, use data, typically ratings, to construct models for providing personalized suggestions to users.  Our objective in this work is to provide a comprehensive overview of various techniques employed in Model-based RS, focusing on their theoretical foundations and practical applications.  We explore

Recommendation Systems in E-Commerce Applications

Nowadays, there are more and more web applications of all kinds. Each of them solves a specific problem and makes life easier for its users. Web applications come in many different types: from a platform for learning courses and watching movies to an online store selling goods. The best systems are those that make things as easy as possible for the user, behave like old friends who know the behavior and tastes of their users and can predict their next move.

MATRIX FACTORIZATION OF BIG DATA IN THE INDUSTRIAL SYSTEMS

The creation of new technologies and their implementation in various fields necessitated Big Data processing and storage. In industrial systems, modernization means the use of a large number of smart devices that perform specialized functions. Data from such devices are used to control the system and automate production processes. A change in the parameters of individual components of the manufacturing system may indicate the need to adjust the global management strategy. The intelligent industrial systems main characteristics were defined in the paper.