An Introduction to Matrix factorization and Factorization Machines in Recommendation System, and Beyond
Information Retrieval
2022-03-22 v1 Machine Learning
Abstract
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.
Cite
@article{arxiv.2203.11026,
title = {An Introduction to Matrix factorization and Factorization Machines in Recommendation System, and Beyond},
author = {Yuefeng Zhang},
journal= {arXiv preprint arXiv:2203.11026},
year = {2022}
}
Comments
15 pages, 6 figures. A notebook for better understanding MF, FM and their derivations in recommendation system