Text Modeling Using Multinomial Scaled Dirichlet Distributions

  • Nuha ZamzamiEmail author
  • Nizar Bouguila
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10868)


The Dirichlet Compound Multinomial (DCM), the composition of the Dirichlet and the multinomial, is a widely accepted generative model for text documents that takes into account burstiness. However, recent research showed that the Dirichlet is not the best to be chosen as a prior to multinomial. In this paper, we propose a novel model called the Multinomial Scaled Dirichlet (MSD) distribution that is the composition of the scaled Dirichlet distribution and the multinomial. Moreover, we investigate the Expectation Maximization (EM) with the MSD mixture model as a new clustering algorithm for documents. Experiments show that the new model is competitive with the best state-of-the-art methods on different text data sets.


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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Concordia Institute for Information Systems EngineeringConcordia UniversityMontrealCanada
  2. 2.Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia

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