Calculate a topic model for a corpus then calculate the probability of those topics in a new corpus. Using R on windows 7.

topics-for-new-corpus.R

library(topicmodels)
data(AssociatedPress)

train <- AssociatedPress[1:100]
test <- AssociatedPress[101:150]

train.lda <- LDA(train,5)

# Determine the posterior probabilities of the topics 
# for each document and of the  terms for each topic 
# for a fitted topic model.
test.lda <- posterior(train.lda,test)

# Here is the matrix with topics as cols,
# documents as rows and cell values as
# posterior probabilities
test.lda[[2]]