I am trying to learn about latent semantic analysis and am working on some movie review data.After doing LSA on the review data I have clustered the Tk matrix into 2 clusters to find words which match concept wise(dimension) wise.Not sure if it is the right interpretation.The image below contains 3 wordclouds,the first one is from the tdm and second one from each of the clusters after doing LSA.
So can we say the process has weeded out the unimportant words not relating to some concepts generated by the algo??
Is this the right way or can someone please help me on this?? @Lesaffrea