A General Framework for Multiplets Selection: Algorithmization and Complexity Analysis
Abstract
In this contribution, we present the multiplets algorithm for constructing and selecting optimal sets of disjoint hyperedges across multiple groups in tabular data. We describe its main computational steps and provide a complexity analysis covering both the edge construction and optimization phases, based on the Linear Sum Assignment method and the Constraint Programming SAT-based solver.
Fields of Study & Subjects
Data Mining Algorithms and Applications
Data Mining and Machine Learning Applications
Advanced Clustering Algorithms Research
Publication details
- Pages
- 46–49
- Publication date
- 1 January 2026
- Language
- EN