Abstract
This chapter discusses alternative formulations of correlation clustering where constraints are added to the basic formulation. Although adding constraints results in a shrinkage of the feasible region, the corresponding constrained formulations can be interpreted as generalizations of the basic correlation-clustering formulation, as the latter can be obtained from a constrained formulation by setting the additional constraints to ad hoc values.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2022 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Bonchi, F., García-Soriano, D., Gullo, F. (2022). Constraints. In: Correlation Clustering. Synthesis Lectures on Data Mining and Knowledge Discovery. Springer, Cham. https://doi.org/10.1007/978-3-031-79210-6_2
Download citation
DOI: https://doi.org/10.1007/978-3-031-79210-6_2
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-79198-7
Online ISBN: 978-3-031-79210-6
eBook Packages: Synthesis Collection of Technology (R0)eBColl Synthesis Collection 11