An Improved Combinatorial Algorithm for Edge-Colored Clustering in Hypergraphs

Fuente: arXiv
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Hauptverfasser: Han, Seongjune, Veldt, Nate
Format: Preprint
Veröffentlicht: 2026
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author Han, Seongjune
Veldt, Nate
author_facet Han, Seongjune
Veldt, Nate
contents Many complex systems and datasets are characterized by multiway interactions of different categories, and can be modeled as edge-colored hypergraphs. We focus on clustering such datasets using the NP-hard edge-colored clustering problem, where the goal is to assign colors to nodes in such a way that node colors tend to match edge colors. A key focus in prior work has been to develop approximation algorithms for the problem that are combinatorial and easier to scale. In this paper, we present the first combinatorial approximation algorithm with an approximation factor better than 2.
format Preprint
id arxiv_https___arxiv_org_abs_2603_03273
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle An Improved Combinatorial Algorithm for Edge-Colored Clustering in Hypergraphs
Han, Seongjune
Veldt, Nate
Data Structures and Algorithms
Social and Information Networks
Many complex systems and datasets are characterized by multiway interactions of different categories, and can be modeled as edge-colored hypergraphs. We focus on clustering such datasets using the NP-hard edge-colored clustering problem, where the goal is to assign colors to nodes in such a way that node colors tend to match edge colors. A key focus in prior work has been to develop approximation algorithms for the problem that are combinatorial and easier to scale. In this paper, we present the first combinatorial approximation algorithm with an approximation factor better than 2.
title An Improved Combinatorial Algorithm for Edge-Colored Clustering in Hypergraphs
topic Data Structures and Algorithms
Social and Information Networks
url https://arxiv.org/abs/2603.03273