Svd, Dimensionality Reduction, Latent Semantic Indexing, Machine Learning, Similarity Search.
represented as a linear combination of term-concept and document-concept weights. Consider and MxN term document which is very huge in dimensional, which is represented as a matrix W. We can factorize it into 3 different matrices. Here T and D are new Basis, which are orthogonal ( orthonormal),