Tag Results

SVD user-based collaborative filtering rec... (1)

• Download

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 ...

Created: 2011-05-09 | Last updated: 2011-05-09

Credits: Ninoaf Matko Bošnjak

Attributions: User-based collaborative filtering recommender system template Datasets for the pack: RCOMM2011 recommender systems workflow templates

LSI content based recommender system template (1)

• Download

This workflow performs LSI text-mining content based recommendation. We use SVD to capture latent semantics between items and words and to obtain low-dimensional representation of items. Latent Semantic Indexing (LSI) takes k greatest singular values and left and right singular vectors to obtain matrix  A_k=U_k * S_k * V_k^T. Items are represented as word-vectors in the original space, where each row in matrix A represents word-vector of particular item. Matrix U_k, on the other hand ...

Created: 2011-05-06 | Last updated: 2011-05-09

Credits: Ninoaf Matko Bošnjak

Attributions: Content based recommender system template Datasets for the pack: RCOMM2011 recommender systems workflow templates