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MCClusteringSM: An approach for the Multicriteria Clustering Problem based on a Credibility Similarity Measure
Computer Science and Information Systems, Tome 21 (2024) no. 3 Cet article a éte moissonné depuis la source Computer Science and Information Systems website

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Multicriteria clustering problem has been studied and applied scarcely. When a multicriteria clustering problem is tackled with an outranking approach, it is necessary to include preferences of decision makers on the raw dataset, e.g., weights and thresholds of the evaluation criteria. Then, it is necessary to conduct a process to obtain a comprehensive model of preferences represented in a fuzzy or crisp outranking relation. Subsequently, the model can be exploited to derive a multicriteria clustering. This work presents an exhaustive search approach using a credibility similarity measure to exploit a fuzzy outranking relation to derive a multicriteria clustering. The work includes two experimental designs to evaluate the performance of the algorithm. Results show that the proposed method has good performance exploiting fuzzy outranking relations to create the clusterings.
Keywords: MCDA, Multicriteria Clustering Problem, Similarity Measure 
@article{CSIS_2024_21_3_a22,
     author = {Lugo Medrano Cesar and Gastelum Chavira Diego Alonso and Valdez Lafarga Octavio and Velarde Cervantes Jose Luis},
     title = {MCClusteringSM: {An} approach for the {Multicriteria} {Clustering} {Problem} based on a {Credibility} {Similarity} {Measure}},
     journal = {Computer Science and Information Systems},
     year = {2024},
     volume = {21},
     number = {3},
     url = {http://geodesic.mathdoc.fr/item/CSIS_2024_21_3_a22/}
}
TY  - JOUR
AU  - Lugo Medrano Cesar
AU  - Gastelum Chavira Diego Alonso
AU  - Valdez Lafarga Octavio
AU  - Velarde Cervantes Jose Luis
TI  - MCClusteringSM: An approach for the Multicriteria Clustering Problem based on a Credibility Similarity Measure
JO  - Computer Science and Information Systems
PY  - 2024
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IS  - 3
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ID  - CSIS_2024_21_3_a22
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%A Gastelum Chavira Diego Alonso
%A Valdez Lafarga Octavio
%A Velarde Cervantes Jose Luis
%T MCClusteringSM: An approach for the Multicriteria Clustering Problem based on a Credibility Similarity Measure
%J Computer Science and Information Systems
%D 2024
%V 21
%N 3
%U http://geodesic.mathdoc.fr/item/CSIS_2024_21_3_a22/
%F CSIS_2024_21_3_a22
Lugo Medrano Cesar; Gastelum Chavira Diego Alonso; Valdez Lafarga Octavio; Velarde Cervantes Jose Luis. MCClusteringSM: An approach for the Multicriteria Clustering Problem based on a Credibility Similarity Measure. Computer Science and Information Systems, Tome 21 (2024) no. 3. http://geodesic.mathdoc.fr/item/CSIS_2024_21_3_a22/