论文标题
推荐系统中矩阵分解和分解机的简介
An Introduction to Matrix factorization and Factorization Machines in Recommendation System, and Beyond
论文作者
论文摘要
本文旨在更好地了解基质分解（MF），分解机（FM）及其与深层算法在建议系统中的应用。具体而言，本文将侧重于单数值分解（SVD）及其推导，例如Funk-SVD，SVD ++等。显示了逐步公式计算和可解释的图片。更重要的是，我们解释了深度学习帮助FM的DEEPFM模型。通过数值示例，我们试图将理论与现实世界中的问题联系起来。
This paper aims at a better understanding of matrix factorization (MF), factorization machines (FM), and their combination with deep algorithms' application in recommendation systems. Specifically, this paper will focus on Singular Value Decomposition (SVD) and its derivations, e.g Funk-SVD, SVD++, etc. Step-by-step formula calculation and explainable pictures are displayed. What's more, we explain the DeepFM model in which FM is assisted by deep learning. Through numerical examples, we attempt to tie the theory to real-world problems.
