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Статья

Robust PLSA Performs Better Than LDA

Lecture Notes in Computer Science. 2013. Vol. 7814. P. 784-787.
Konstantin Vorontsov, Potapenko A.

In this paper we introduce a generalized learning algorithm for probabilistic topic models (PTM). Many known and new algorithms for PLSA, LDA, and SWB models can be obtained as its special cases by choosing a subset of the following “options”: regularization, sampling, update frequency, sparsing and robustness. We show that a robust topic model, which distinguishes specific, background and topic terms, doesn’t need Dirichlet regularization and provides controllably sparse solution.