Detecting and Characterizing Small Dense Bipartite-like Subgraphs by the Bipartiteness Ratio Measure
Abstract
We study the problem of finding and characterizing subgraphs with small \textit{bipartiteness ratio}. We give a bicriteria approximation algorithm \verb|SwpDB| such that if there exists a subset of volume at most and bipartiteness ratio , then for any , it finds a set of volume at most and bipartiteness ratio at most . By combining a truncation operation, we give a local algorithm \verb|LocDB|, which has asymptotically the same approximation guarantee as the algorithm \verb|SwpDB| on both the volume and bipartiteness ratio of the output set, and runs in time , independent of the size of the graph. Finally, we give a spectral characterization of the small dense bipartite-like subgraphs by using the th \textit{largest} eigenvalue of the Laplacian of the graph.
Keywords
Cite
@article{arxiv.1209.5045,
title = {Detecting and Characterizing Small Dense Bipartite-like Subgraphs by the Bipartiteness Ratio Measure},
author = {Angsheng Li and Pan Peng},
journal= {arXiv preprint arXiv:1209.5045},
year = {2013}
}
Comments
17 pages; ISAAC 2013