About: An extensible C++ library of Hierarchical Bayesian clustering algorithms, such as Bayesian Gaussian mixture models, variational Dirichlet processes, Gaussian latent Dirichlet allocation and more.

New maximum cluster argument for all algorithms. Also no more matlab interface since it seemed no one was using it, and I cannot support it any longer.

About: The Java package jLDADMM is released to provide alternative choices 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.

Initial Announcement on mloss.org.

About: Python Framework for Vector Space Modelling that can handle unlimited datasets (streamed input, online algorithms work incrementally in constant memory).

• added the "hashing trick" (by Homer Strong)
• support for adding target classes in SVMlight format (by Corrado Monti)
• fixed problems with global lemmatizer object when running in parallel on Windows
• parallelization of Wikipedia processing + added script version that lemmatizes the input documents
• added class method to initialize Dictionary from an existing corpus (by Marko Burjek)