  In this technical report, we present jLDADMM---an easy-to-use Java toolkit
for conventional topic models. jLDADMM is released to provide alternatives for
topic modeling on normal or short texts. It provides implementations of the
Latent Dirichlet Allocation topic model and the one-topic-per-document
Dirichlet Multinomial Mixture model (i.e. mixture of unigrams), using collapsed
Gibbs sampling. In addition, jLDADMM supplies a document clustering evaluation
to compare topic models. jLDADMM is open-source and available to download at:
https://github.com/datquocnguyen/jLDADMM
