CEVCLUS: evidential clustering with instance-level constraints for relational data

Recent advances in clustering consider incorporating background knowledge in the partitioning algorithm, using, e.g., pairwise constraints between objects. As a matter of fact, prior information, when available, often makes it possible to better retrieve meaningful clusters in data. Here, this appro...

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Bibliographic Details
Published in:	Soft computing (Berlin, Germany) Vol. 18; no. 7; pp. 1321 - 1335
Main Authors:	Antoine, V., Quost, B., Masson, M.-H., Denoeux, T.
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01.07.2014 Springer Nature B.V Springer Verlag
Subjects:	Algorithms Artificial Intelligence Clustering Computational Intelligence Computer Science Constraints Control Engineering Knowledge Mathematical Logic and Foundations Mechatronics Methodologies and Application Partitioning Probability distribution Robotics Pairwise constraints Belief functions Dempster–Shafer theory Evidence theory Relational data Constrained clustering
ISSN:	1432-7643, 1433-7479
Online Access:	Get full text
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