SVD user-based collaborative filtering recommender system

This workflow takes user-item matrix A as a input. Then it calculates reduced SVD decomposition A_k by taking only k greatest singular values and corresponding singular vectors. This worfkflow calculates recommendations and predictions for particular user %{id} from matrix A. Particular row %{id} is taken from original matrix A and replaced with %{id} row in A_k matrix. Predictions are made for %{id} user based on another users A_k.

Note: This workflow uses R-script operator with R library 'Matrix'.

1. Install R-component in RapidMiner.

2. Install library 'Matrix' in R-console inside RapidMiner

Type :

> install.packages('Matrix')

inside R console and follow instructions.

Reference:

Bošnjak, M., Antulov-Fantulin, N. Šmuc, T. and Gamberger, D., Constructing recommender systems workflow templates in RapidMiner, Proceedings of the RapidMiner Community Meeting And Conference (RCOMM), 2011, Dublin, Ireland - In Press