Matrix Factorization and Latent Semantic Indexing Low-Rank Approximation LoW-rank approximation Solution via Svd set smallest r-k singular values to zero ***** **** ****米 k column notation sum of rank 1 matricesMatrix Factorization and Latent Semantic Indexing 20 ▪ Solution via SVD Low-rank Approximation set smallest r-k singular values to zero Ak=Udiag (1 ,..., k ,0,..., 0)V T column notation: sum of rank 1 matrices T ii k Ak =i=1 i uv k Low-Rank Approximation