What is diversity in recommendation systems?

A recommender system aims to suggest relevant content or products to users that might be liked or purchased by them. Aug 28, 2020 ... IMF Working Papers. Intelligent Export Diversification: An Export Recommendation System with Machine Learning. By Natasha X Che. August ... Mar 15, 2023 ... This survey aims to provide a timely and comprehensive overview of recent trends of deep reinforcement learning in recommender systems. Nov 18, 2020 ... The paper presents the development and the comparison of multiple recommendation systems, capable of making item suggestions, based on user, ... ... machine learning based course recommendation system for higher education students. principal component analysis (PCA) algorithm is used for feature selection. Feb 27, 2023 ... Recommender Systems Algorithms and Techniques · Matrix Factorization · Deep Neural Networks · Contextual Sequence Learning · Wide and Deep. Jun 19, 2024 ... Recommendation systems rely on big data analytics and machine learning (ML) algorithms to find patterns in user behavior data and recommend ... Explore and run machine learning code with Kaggle Notebooks | Using data from Articles sharing and reading from CI&T DeskDrop. Recommended Citation. Bommireddy, Durga Rajesh, "Recommendation System using machine learning for fertilizer prediction" (2024). Electronic Theses, Projects, ... Oct 4, 2023 ... Reinforcement Learning (RL) takes recommendation systems to a whole new level. Instead of static recommendations, RL algorithms make sequential ...