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JACIII Vol.24 No.1 pp. 58-64
doi: 10.20965/jaciii.2020.p0058
(2020)

Paper:

Tsallis Entropy-Based Fuzzy Latent Semantics Analysis

Yuchi Kanzawa

Shibaura Institute of Technology
3-7-5 Toyosu, Koto, Tokyo 135-8548, Japan

Received:
March 20, 2019
Accepted:
September 12, 2019
Published:
January 20, 2020
Keywords:
latent semantic analysis, Tsallis entropy, fuzzy clustering
Abstract

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.

Cite this article as:
Y. Kanzawa, “Tsallis Entropy-Based Fuzzy Latent Semantics Analysis,” J. Adv. Comput. Intell. Intell. Inform., Vol.24, No.1, pp. 58-64, 2020.
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Last updated on Feb. 17, 2020