Google’s Recommender System Breakthrough Detects Semantic Intent

Google quietly published a research paper on personalized semantics for recommender systems like Google Discover and YouTube.
IEEE

Recommendations for Culinary Places in Yogyakarta Using Matrix Factorization and Stochastic Gradient Descent

Abstract: Despite easy access to information, people struggle to find accurate culinary. The recommender system aims to provide recommendations that suit users’ needs. Matrix factorization (MF) is the ...
IEEE

Non-Negative Matrix Factorization in Recommender Models: Concept, Survey, and Future Direction

Abstract: Recommender Systems have gained attraction since last two decades owing to its popularity of providing customers with the information of their choice, items they might purchase, movies they ...