Aggregated Fuzzy Equivalence Relations in Clustering Process

Olga Grigorenko; Valerijs Mihailovs

doi:10.1007/978-3-031-08971-8_37

Aggregated Fuzzy Equivalence Relations in Clustering Process

Olga Grigorenko^*
, Valerijs Mihailovs

^*Corresponding author for this work

University of Latvia

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › Research › peer-review

6 Citations (Scopus)

Abstract

The aim of the work is to involve fuzzy equivalence relations and aggregation of corresponding equivalence relations in a clustering process. Namely, we introduce fuzzy equivalence relations for different attributes of objects and then we aggregate these fuzzy equivalence relations to determine the similarities of objects. It is possible to involve different weights for attributes, thus defining the importance attributes in decision making process. In the work we also present illustrative examples.

Original language	English
Title of host publication	Information Processing and Management of Uncertainty in Knowledge-Based Systems
Subtitle of host publication	19th International Conference, IPMU 2022, Proceedings
Editors	Davide Ciucci, Inés Couso, Jesús Medina, Dominik Ślęzak, Davide Petturiti, Bernadette Bouchon-Meunier, Ronald R. Yager
Place of Publication	Cham
Publisher	Springer
Pages	448-459
Volume	1601 CCIS
ISBN (Print)	978-303108970-1
DOIs	https://doi.org/10.1007/978-3-031-08971-8_37
Publication status	Published - 2022
Event	19th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2022 - Milan, Italy Duration: 11 Jul 2022 → 15 Jul 2022

Publication series

Name	Communications in Computer and Information Science
Volume	1601 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	19th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2022
Country/Territory	Italy
City	Milan
Period	11/07/22 → 15/07/22

Keywords

Aggregation of fuzzy relations
Fuzzy cluster analysis
Fuzzy equivalence relations

OECD Field of Science

1.2 Computer and Information Sciences
1.1 Mathematics

Access to Document

10.1007/978-3-031-08971-8_37

Cite this

Grigorenko, O., & Mihailovs, V. (2022). Aggregated Fuzzy Equivalence Relations in Clustering Process. In D. Ciucci, I. Couso, J. Medina, D. Ślęzak, D. Petturiti, B. Bouchon-Meunier, & R. R. Yager (Eds.), Information Processing and Management of Uncertainty in Knowledge-Based Systems : 19th International Conference, IPMU 2022, Proceedings (Vol. 1601 CCIS, pp. 448-459). (Communications in Computer and Information Science; Vol. 1601 CCIS). Springer. https://doi.org/10.1007/978-3-031-08971-8_37

Grigorenko, Olga ; Mihailovs, Valerijs. / Aggregated Fuzzy Equivalence Relations in Clustering Process. Information Processing and Management of Uncertainty in Knowledge-Based Systems : 19th International Conference, IPMU 2022, Proceedings. editor / Davide Ciucci ; Inés Couso ; Jesús Medina ; Dominik Ślęzak ; Davide Petturiti ; Bernadette Bouchon-Meunier ; Ronald R. Yager. Vol. 1601 CCIS Cham : Springer, 2022. pp. 448-459 (Communications in Computer and Information Science).

@inproceedings{753931060e284c829381c5a0ddc4f331,

title = "Aggregated Fuzzy Equivalence Relations in Clustering Process",

abstract = "The aim of the work is to involve fuzzy equivalence relations and aggregation of corresponding equivalence relations in a clustering process. Namely, we introduce fuzzy equivalence relations for different attributes of objects and then we aggregate these fuzzy equivalence relations to determine the similarities of objects. It is possible to involve different weights for attributes, thus defining the importance attributes in decision making process. In the work we also present illustrative examples.",

keywords = "Aggregation of fuzzy relations, Fuzzy cluster analysis, Fuzzy equivalence relations",

author = "Olga Grigorenko and Valerijs Mihailovs",

note = "Publisher Copyright: {\textcopyright} 2022, Springer Nature Switzerland AG.; 19th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2022 ; Conference date: 11-07-2022 Through 15-07-2022",

year = "2022",

doi = "10.1007/978-3-031-08971-8\_37",

language = "English",

isbn = "978-303108970-1",

volume = "1601 CCIS",

series = "Communications in Computer and Information Science",

publisher = "Springer",

pages = "448--459",

editor = "Davide Ciucci and In{\'e}s Couso and Jes{\'u}s Medina and Dominik {\'S}l{\c e}zak and Davide Petturiti and Bernadette Bouchon-Meunier and Yager, \{Ronald R.\}",

booktitle = "Information Processing and Management of Uncertainty in Knowledge-Based Systems",

address = "Germany",

}

Grigorenko, O & Mihailovs, V 2022, Aggregated Fuzzy Equivalence Relations in Clustering Process. in D Ciucci, I Couso, J Medina, D Ślęzak, D Petturiti, B Bouchon-Meunier & RR Yager (eds), Information Processing and Management of Uncertainty in Knowledge-Based Systems : 19th International Conference, IPMU 2022, Proceedings. vol. 1601 CCIS, Communications in Computer and Information Science, vol. 1601 CCIS, Springer, Cham, pp. 448-459, 19th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2022, Milan, Italy, 11/07/22. https://doi.org/10.1007/978-3-031-08971-8_37

Aggregated Fuzzy Equivalence Relations in Clustering Process. / Grigorenko, Olga ; Mihailovs, Valerijs.
Information Processing and Management of Uncertainty in Knowledge-Based Systems : 19th International Conference, IPMU 2022, Proceedings. ed. / Davide Ciucci; Inés Couso; Jesús Medina; Dominik Ślęzak; Davide Petturiti; Bernadette Bouchon-Meunier; Ronald R. Yager. Vol. 1601 CCIS Cham: Springer, 2022. p. 448-459 (Communications in Computer and Information Science; Vol. 1601 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › Research › peer-review

TY - GEN

T1 - Aggregated Fuzzy Equivalence Relations in Clustering Process

AU - Grigorenko, Olga

AU - Mihailovs, Valerijs

PY - 2022

Y1 - 2022

N2 - The aim of the work is to involve fuzzy equivalence relations and aggregation of corresponding equivalence relations in a clustering process. Namely, we introduce fuzzy equivalence relations for different attributes of objects and then we aggregate these fuzzy equivalence relations to determine the similarities of objects. It is possible to involve different weights for attributes, thus defining the importance attributes in decision making process. In the work we also present illustrative examples.

AB - The aim of the work is to involve fuzzy equivalence relations and aggregation of corresponding equivalence relations in a clustering process. Namely, we introduce fuzzy equivalence relations for different attributes of objects and then we aggregate these fuzzy equivalence relations to determine the similarities of objects. It is possible to involve different weights for attributes, thus defining the importance attributes in decision making process. In the work we also present illustrative examples.

KW - Aggregation of fuzzy relations

KW - Fuzzy cluster analysis

KW - Fuzzy equivalence relations

UR - https://link.springer.com/chapter/10.1007/978-3-031-08971-8_37

UR - https://www.scopus.com/pages/publications/85135018693

U2 - 10.1007/978-3-031-08971-8_37

DO - 10.1007/978-3-031-08971-8_37

M3 - Conference paper

SN - 978-303108970-1

VL - 1601 CCIS

T3 - Communications in Computer and Information Science

SP - 448

EP - 459

BT - Information Processing and Management of Uncertainty in Knowledge-Based Systems

A2 - Ciucci, Davide

A2 - Couso, Inés

A2 - Medina, Jesús

A2 - Ślęzak, Dominik

A2 - Petturiti, Davide

A2 - Bouchon-Meunier, Bernadette

A2 - Yager, Ronald R.

PB - Springer

CY - Cham

T2 - 19th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2022

Y2 - 11 July 2022 through 15 July 2022

ER -

Grigorenko O , Mihailovs V. Aggregated Fuzzy Equivalence Relations in Clustering Process. In Ciucci D, Couso I, Medina J, Ślęzak D, Petturiti D, Bouchon-Meunier B, Yager RR, editors, Information Processing and Management of Uncertainty in Knowledge-Based Systems : 19th International Conference, IPMU 2022, Proceedings. Vol. 1601 CCIS. Cham: Springer. 2022. p. 448-459. (Communications in Computer and Information Science). doi: 10.1007/978-3-031-08971-8_37

Aggregated Fuzzy Equivalence Relations in Clustering Process

Abstract

Publication series

Conference

Keywords

OECD Field of Science

Access to Document

Other files and links

Fingerprint

Cite this