LSI content based recommender system template
(1)
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