Matrix Factorization (Collaborative Filtering)

From Algorithm Wiki
Jump to navigation Jump to search

Description

Collaborative filtering is a technique used in recommendation systems. It analyzes relationships between users and interdependencies among products to identify new user-item associations.

A method of collaborative filtering uses matrix factorization. In its basic form, matrix factorization characterizes both items and users by vectors of factors inferred from item rating patterns.

Parameters

$n$: dimension of matrix

Table of Algorithms

Name Year Time Space Approximation Factor Model Reference
LU Matrix Decomposition 1945 $O(n^{3})$ $O(n^{2})$ Exact Deterministic
QR Matrix Decomposition 1955 $O(n^{2})$ $O(n^{2})$ Exact Deterministic
Cholesky Decomposition 1983 $O(n^{2})$ $O(n^{2})$ Exact Deterministic

Time Complexity Graph

Collaborative Filtering - Matrix Factorization - Time.png