On Tsallis Entropy-Based and Bezdek-Type Fuzzy Latent Semantics Analysis

Yuchi Kanzawa

doi:10.1109/SMC.2018.00623

On Tsallis Entropy-Based and Bezdek-Type Fuzzy Latent Semantics Analysis

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this study, we present two types of fuzzy counterparts to the probabilistic latent semantic analysis (pLSA) approach. The first type is derived by solving the optimization problem of Tsallis entropy-penalizing free energy of a pseudo pLSA model using a modified i.i.d. assumption; this derivation is similar to that of the conventional fuzzy counterpart of the pLSA that involves solving the optimization problem of Shannon entropy-penalizing free energy. The second proposed approach is derived from the first approach by letting the fuzzification parameter approach infinity; this derivation is similar to the derivation of a fuzzy clustering algorithm from another fuzzy clustering algorithm by letting the fuzzification parameter approach infinity. Furthermore, some numerical examples for the proposed methods are presented.

Original language	English
Title of host publication	Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3685-3689
Number of pages	5
ISBN (Electronic)	9781538666500
DOIs	https://doi.org/10.1109/SMC.2018.00623
Publication status	Published - 2019 Jan 16
Event	2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018 - Miyazaki, Japan Duration: 2018 Oct 7 → 2018 Oct 10

Publication series

Name	Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018

Conference

Conference	2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018
Country/Territory	Japan
City	Miyazaki
Period	18/10/7 → 18/10/10

ASJC Scopus subject areas

Information Systems
Information Systems and Management
Health Informatics
Artificial Intelligence
Computer Networks and Communications
Human-Computer Interaction

Access to Document

10.1109/SMC.2018.00623

Cite this

Kanzawa, Y. (2019). On Tsallis Entropy-Based and Bezdek-Type Fuzzy Latent Semantics Analysis. In Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018 (pp. 3685-3689). [8616620] (Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SMC.2018.00623

On Tsallis Entropy-Based and Bezdek-Type Fuzzy Latent Semantics Analysis. / Kanzawa, Yuchi.

Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018. Institute of Electrical and Electronics Engineers Inc., 2019. p. 3685-3689 8616620 (Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kanzawa, Y 2019, On Tsallis Entropy-Based and Bezdek-Type Fuzzy Latent Semantics Analysis. in Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018., 8616620, Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018, Institute of Electrical and Electronics Engineers Inc., pp. 3685-3689, 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018, Miyazaki, Japan, 18/10/7. https://doi.org/10.1109/SMC.2018.00623

Kanzawa Y. On Tsallis Entropy-Based and Bezdek-Type Fuzzy Latent Semantics Analysis. In Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018. Institute of Electrical and Electronics Engineers Inc. 2019. p. 3685-3689. 8616620. (Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018). doi: 10.1109/SMC.2018.00623

@inproceedings{f4d942fb687d4268a4568e1695b78eaa,

title = "On Tsallis Entropy-Based and Bezdek-Type Fuzzy Latent Semantics Analysis",

abstract = "In this study, we present two types of fuzzy counterparts to the probabilistic latent semantic analysis (pLSA) approach. The first type is derived by solving the optimization problem of Tsallis entropy-penalizing free energy of a pseudo pLSA model using a modified i.i.d. assumption; this derivation is similar to that of the conventional fuzzy counterpart of the pLSA that involves solving the optimization problem of Shannon entropy-penalizing free energy. The second proposed approach is derived from the first approach by letting the fuzzification parameter approach infinity; this derivation is similar to the derivation of a fuzzy clustering algorithm from another fuzzy clustering algorithm by letting the fuzzification parameter approach infinity. Furthermore, some numerical examples for the proposed methods are presented.",

author = "Yuchi Kanzawa",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018 ; Conference date: 07-10-2018 Through 10-10-2018",

year = "2019",

month = jan,

day = "16",

doi = "10.1109/SMC.2018.00623",

language = "English",

series = "Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "3685--3689",

booktitle = "Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018",

}

TY - GEN

T1 - On Tsallis Entropy-Based and Bezdek-Type Fuzzy Latent Semantics Analysis

AU - Kanzawa, Yuchi

PY - 2019/1/16

Y1 - 2019/1/16

N2 - In this study, we present two types of fuzzy counterparts to the probabilistic latent semantic analysis (pLSA) approach. The first type is derived by solving the optimization problem of Tsallis entropy-penalizing free energy of a pseudo pLSA model using a modified i.i.d. assumption; this derivation is similar to that of the conventional fuzzy counterpart of the pLSA that involves solving the optimization problem of Shannon entropy-penalizing free energy. The second proposed approach is derived from the first approach by letting the fuzzification parameter approach infinity; this derivation is similar to the derivation of a fuzzy clustering algorithm from another fuzzy clustering algorithm by letting the fuzzification parameter approach infinity. Furthermore, some numerical examples for the proposed methods are presented.

AB - In this study, we present two types of fuzzy counterparts to the probabilistic latent semantic analysis (pLSA) approach. The first type is derived by solving the optimization problem of Tsallis entropy-penalizing free energy of a pseudo pLSA model using a modified i.i.d. assumption; this derivation is similar to that of the conventional fuzzy counterpart of the pLSA that involves solving the optimization problem of Shannon entropy-penalizing free energy. The second proposed approach is derived from the first approach by letting the fuzzification parameter approach infinity; this derivation is similar to the derivation of a fuzzy clustering algorithm from another fuzzy clustering algorithm by letting the fuzzification parameter approach infinity. Furthermore, some numerical examples for the proposed methods are presented.

UR - http://www.scopus.com/inward/record.url?scp=85062241193&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85062241193&partnerID=8YFLogxK

U2 - 10.1109/SMC.2018.00623

DO - 10.1109/SMC.2018.00623

M3 - Conference contribution

AN - SCOPUS:85062241193

T3 - Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018

SP - 3685

EP - 3689

BT - Proceedings - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2018 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2018

Y2 - 7 October 2018 through 10 October 2018

ER -

On Tsallis Entropy-Based and Bezdek-Type Fuzzy Latent Semantics Analysis

Abstract

Publication series

Conference

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this