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Clustering algorithms: A comparative approach

Citations

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Cited by:

  1. Alfred Kume & Stephen G Walker, 2021. "The utility of clusters and a Hungarian clustering algorithm," PLOS ONE, Public Library of Science, vol. 16(8), pages 1-23, August.
  2. Hossam M J Mustafa & Masri Ayob & Dheeb Albashish & Sawsan Abu-Taleb, 2020. "Solving text clustering problem using a memetic differential evolution algorithm," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-18, June.
  3. Yerbury, Luke W. & Campello, Ricardo J.G.B. & Livingston Jr, G.C. & Goldsworthy, Mark & O’Neil, Lachlan, 2025. "Comparing clustering approaches for smart meter time series: Investigating the influence of dataset properties on performance," Applied Energy, Elsevier, vol. 391(C).
  4. Hossam M J Mustafa & Masri Ayob & Mohd Zakree Ahmad Nazri & Graham Kendall, 2019. "An improved adaptive memetic differential evolution optimization algorithms for data clustering problems," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-28, May.
  5. Nathaniel C. Custodio & Harold R. Lucero & Melvin G. Torres & Rhozzel C. Tayubong & Angela D. Quillondrino, 2026. "Predictive Sales and Inventory System with Customer Segmentation for Enhance Customer Relationship Management," International Journal of Research and Innovation in Applied Science, RSIS International, vol. 11(1), pages 1619-1627, January.
  6. Christian Hennig, 2022. "An empirical comparison and characterisation of nine popular clustering methods," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 16(1), pages 201-229, March.
  7. Ebba Mark & Ryan Rafaty & Moritz Schwarz, 2022. "Spatial-temporal dynamics of employment shocks in declining coal mining regions and potentialities of the 'just transition'," Papers 2211.12619, arXiv.org.
  8. Trotta, Gianluca, 2020. "An empirical analysis of domestic electricity load profiles: Who consumes how much and when?," Applied Energy, Elsevier, vol. 275(C).
  9. K. S. Sablin & E. S. Kagan & E. S. Chernova, 2020. "Clustering of the Russian coal mining regions: Investment and innovation activity," Journal of New Economy, Ural State University of Economics, vol. 21(1), pages 89-106, March.
  10. Chong, Woon Kian & Chang, Chiachi, 2024. "Information exploitation of human resource data with persistent homology," Journal of Business Research, Elsevier, vol. 172(C).
  11. Wolfgang Garn & Mehrdad Amirghasemi, 2025. "Transparency of combinatorial optimisations via machine learning and explainable AI," Annals of Operations Research, Springer, vol. 354(1), pages 427-458, November.
  12. Giovana D da Silva & Filipi N Silva & Henrique F de Arruda & Bárbara C e Souza & Luciano da F Costa & Diego R Amancio, 2024. "Using full-text content to characterize and identify best seller books: A study of early 20th-century literature," PLOS ONE, Public Library of Science, vol. 19(4), pages 1-20, April.
  13. Narjes Vara & Mahdieh Mirzabeigi & Hajar Sotudeh & Seyed Mostafa Fakhrahmad, 2022. "Application of k-means clustering algorithm to improve effectiveness of the results recommended by journal recommender system," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3237-3252, June.
  14. Quispe, Laura V.C. & Tohalino, Jorge A.V. & Amancio, Diego R., 2021. "Using virtual edges to improve the discriminability of co-occurrence text networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
  15. Mikhail Kanevski, 2021. "Unsupervised learning of Swiss population spatial distribution," PLOS ONE, Public Library of Science, vol. 16(2), pages 1-24, February.
  16. Sultan Mahmud & Ferdausi Mahojabin Sumana & Md Mohsin & Md. Hasinur Rahaman Khan, 2022. "Redefining homogeneous climate regions in Bangladesh using multivariate clustering approaches," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(2), pages 1863-1884, March.
  17. Tohalino, Jorge A.V. & Amancio, Diego R., 2022. "On predicting research grants productivity via machine learning," Journal of Informetrics, Elsevier, vol. 16(2).
  18. Mark, Ebba & Rafaty, Ryan & Schwarz, Moritz, 2024. "Spatial–temporal dynamics of structural unemployment in declining coal mining regions and potentialities of the ‘just transition’," Energy Policy, Elsevier, vol. 195(C).
  19. Fernandez Martinez, Roberto & Lostado Lorza, Ruben & Santos Delgado, Ana Alexandra & Piedra, Nelson, 2021. "Use of classification trees and rule-based models to optimize the funding assignment to research projects: A case study of UTPL," Journal of Informetrics, Elsevier, vol. 15(1).
  20. Corrêa, Edilson A. & Marinho, Vanessa Q. & Amancio, Diego R., 2020. "Semantic flow in language networks discriminates texts by genre and publication date," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
  21. Théophile Carniel & José Halloy & Jean-Michel Dalle, 2023. "A novel clustering approach to bipartite investor-startup networks," PLOS ONE, Public Library of Science, vol. 18(1), pages 1-20, January.
  22. Alexander, Carol & Cumming, Douglas, 2026. "Coordinated journals, concentrated networks and citation growth: Evidence from finance," Journal of Banking & Finance, Elsevier, vol. 188(C).
  23. Simon Crase & Suresh N Thennadil, 2022. "An analysis framework for clustering algorithm selection with applications to spectroscopy," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-24, March.
  24. Ioannis Mikrou & Nickolas S. Sapidis, 2024. "Enhancing operational research in mechatronic systems via modularization: comparative analysis of four clustering algorithms using validation indices," Operational Research, Springer, vol. 24(4), pages 1-44, December.
  25. Torgunn Aslaug Skjerve & Gunnar Klemetsdal & Bente Aspeholen Åby & Jon Kristian Sommerseth & Ulf Geir Indahl & Hanne Fjerdingby Olsen, 2025. "Using Density and Fuzzy Clustering for Data Cleaning and Segmental Description of Livestock Data," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 30(3), pages 870-885, September.
  26. Polina Bombina & Dwayne Tally & Zachary B Abrams & Kevin R Coombes, 2024. "SillyPutty: Improved clustering by optimizing the silhouette width," PLOS ONE, Public Library of Science, vol. 19(6), pages 1-17, June.
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