A Java Implementation of Latent Factor Models for Recommender Systems


Introduction

This is a Java implementation of a user/item bias baseline model, and three basic latent factor models (LFMs) for rating prediction in recommender systems.


Features


Download and Examples

Please find the latest source here lfm.zip. Below is a brief introduction to the contained files.

Util.java
- Common functions: data input, vector computation, RMSE calculation and etc.
Rec.java
- An interface to be implemented by all the models.
RecBaseline.java
- Baseline model:
RecMF.java
- Pure factor model:
RecMuMF.java
- A mixed model:
RecSVD.java
- SVD model: .

Here is an example to run "SVD" on the Movielens 1M dataset.


Feedback

We are always happy to receive feedback. Please notify us of any bugs by sending email to thomo@cs.uvic.ca

Reference

  1. Koren, Yehuda, and Robert Bell. "Advances in collaborative filtering." In Recommender Systems Handbook, pp. 145-186. Springer US, 2011.