Topic prediction using Latent Dirichlet Allocation

I have used LDA on a corpus of documents and found some Topics. The output of my code is two matrices containing probabilities. one doc-topic probabilities and the other word-topic probabilities. But I actually don't know how to use these results to predict the topic of a n开发者_如何学JAVAew document. I am using Gibbs sampling. Does anyone know how? thanks

The Java implementation http://www.arbylon.net/projects/lda-j/lda-j-src-20050325.zip has an short example program in src\org\knowceans\lda\SearchEnglet.java. I hope you are a bit familiar with java and the code helps you.

The original paper http://jmlr.csail.mit.edu/papers/volume3/blei03a/blei03a.pdf describes inference in sections 5.1 and 5.2.