Tsallis entropy-based fuzzy latent semantics analysis

Research output: Contribution to journalArticlepeer-review


In this study, we present a fuzzy counterpart to the probabilistic latent semantic analysis (PLSA) approach. It is derived by solving the optimization problem of Tsallis entropy-penalizing free energy of a pseudo PLSA model by using a modified i.i.d. assumption. This derivation is similar to that of the conventional fuzzy counterpart of the PLSA, which involves solving the optimization problem of Shannon entropy-penalizing free energy. Furthermore, the proposed method is validated using numerical examples.

Original languageEnglish
Pages (from-to)58-64
Number of pages7
JournalJournal of Advanced Computational Intelligence and Intelligent Informatics
Issue number1
Publication statusPublished - 2020


  • Fuzzy clustering
  • Latent semantic analysis
  • Tsallis entropy

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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