Аннотация:Probabilistic topic modeling of text collections is a powerful
tool for statistical text analysis. In this paper we announce the BigARTM
open source project (http://bigartm.org), which provides the parallel
online EM algorithm for learning additively regularized multimodal topic
models of large collections. We show that BigARTM outperforms other
popular packages in quality, runtime and multicriteria functionality.