Direct multicriteria clustering algorithms
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DOI: 10.1007/BF02618467
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References listed on IDEAS
- William Day, 1986. "Foreword: Comparison and consensus of classifications," Journal of Classification, Springer;The Classification Society, vol. 3(2), pages 183-185, September.
- Anuška Ferligoj & Vladimir Batagelj, 1983. "Some types of clustering with relational constraints," Psychometrika, Springer;The Psychometric Society, vol. 48(4), pages 541-552, December.
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Cited by:
- Michael Brusco & Patrick Doreian & Douglas Steinley & Cinthia Satornino, 2013. "Multiobjective Blockmodeling for Social Network Analysis," Psychometrika, Springer;The Psychometric Society, vol. 78(3), pages 498-525, July.
- Renato Coppi & Pierpaolo D’Urso & Paolo Giordani, 2010. "A Fuzzy Clustering Model for Multivariate Spatial Time Series," Journal of Classification, Springer;The Classification Society, vol. 27(1), pages 54-88, March.
- Ying Liu & Sudha Ram & Robert F. Lusch & Michael Brusco, 2010. "Multicriterion Market Segmentation: A New Model, Implementation, and Evaluation," Marketing Science, INFORMS, vol. 29(5), pages 880-894, 09-10.
- Lu, Emiao & Handl, Julia & Xu, Dong-ling, 2018. "Determining analogies based on the integration of multiple information sources," International Journal of Forecasting, Elsevier, vol. 34(3), pages 507-528.
- G. Damiana Costanzo, 2001. "A constrainedk-means clustering algorithm for classifying spatial units," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 10(1), pages 237-256, January.
- Nenad Mladenovic & Pierre Hansen & Jack Brimberg, 2013. "Sequential clustering with radius and split criteria," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 21(1), pages 95-115, June.
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Keywords
Multicriteria optimization; Pareto-efficiency; Agglomerative hierarchical algorithms; Local optimization; Relocation algorithms; Constrained clustering; Consensus clustering;All these keywords.
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