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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 Mixturemodel (i.e. mixture of unigrams), using collapsed Gibbs sampling. In addition, jLDADMM supplies a document clustering evaluation to compare topic models. See the usage of jLDADMM in its website at http://jldadmm.sourceforge.net/
General purpose matrix utilities for Java in Parallel Computing
Fast Matrix for Java (fm4j) is a general-purpose matrix utility library for computing with dense matrices.
fm4j encapsulated different underlying implementations and select the optimal one in run-time depending on the size of the input matrix. Moreover, fm4j employs Java (Tm) Concurrency to take advantage of the computation power of multi-cor processors.
A straight-forward Java implementation of a mixturemodel with pluggable mixture functions, e.g. a mixture of Gaussian functions. The number and dimensionality of the mixture functions is not limited. All critical calculations are performed in log-space.