Stockholm: Dec -03Vector-based Semantic Analysis18 Using the SVD  The matrices make it easy to project term and document vectors into a m-dimensional space (m ≤ min (terms, docs)) using ordinary linear algebra  We can select m easily just by using as many rows/columns of T 0, S 0, D 0 as we want  To get an idea, let's use m=2 and recalculate a new (approximated) X – it will still be a t x d matrix
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