English

Approximate Association via Dissociation

Data Structures and Algorithms 2015-10-29 v1

Abstract

A vertex set XX of a graph GG is an association set if each component of GXG - X is a clique, or a dissociation set if each component of GXG - X is a single vertex or a single edge. Interestingly, GXG - X is then precisely a graph containing no induced P3P_3's or containing no P3P_3's, respectively. We observe some special structures and show that if none of them exists, then the minimum association set problem can be reduced to the minimum (weighted) dissociation set problem. This yields the first nontrivial approximation algorithm for association set, and its approximation ratio is 2.5, matching the best result of the closely related cluster editing problem. The reduction is based on a combinatorial study of modular decomposition of graphs free of these special structures. Further, a novel algorithmic use of modular decomposition enables us to implement this approach in O(mn+n2)O(m n + n^2) time.

Keywords

Cite

@article{arxiv.1510.08276,
  title  = {Approximate Association via Dissociation},
  author = {Jie You and Jianxin Wang and Yixin Cao},
  journal= {arXiv preprint arXiv:1510.08276},
  year   = {2015}
}
R2 v1 2026-06-22T11:30:58.419Z