I implemented LSA (Latent Semantic Analysis) on MATLAB. I have a $D\times N$ term-document matrix, where $D$: # of words, $N$: # of docs. I did low-rank approximation using SVD, and got $$X_k = U_k \cdot S_k \cdot V_k' (D=1000, N=600, K=4)$$
Now I want to classify the documents into 4 classes, and I know I have to use the col-vectors of $V_k'$.
Each column of it has 4 values. I think each value indicates how much the document is related to the topic (in latent spaces). Am I right?
But when I see the column's value, it has both positive and negative values. How can I interpret it?