LSA: Latent Semantic Analysis

Often we want to think about documents from the perspective of semantic content. One standard approach to doing this is to perform Latent Semantic Analysis or LSA on the corpus. You can do this using the lsa function:

lsa(crps)

LDA: Latent Dirichlet Allocation

Another way to get a handle on the semantic content of a corpus is to use Latent Dirichlet Allocation:

m = DocumentTermMatrix(crps)
k = 2            # number of topics
iteration = 1000 # number of gibbs sampling iterations
alpha = 0.1      # hyper parameter
beta = 0.1       # hyber parameter
l = lda(m, k, iteration, alpha, beta) # l is k x word matrix.
                                      # value is probablity of occurrence of a word in a topic.