Spectral Subgraph Localization

Ama Bembua Bainson, Judith Hermanns, Petros Petsinis, Niklas Aavad, Casper Dam Larsen, Tiarnan Swayne, Amit Boyarski, Davide Mottin, Alex M. Bronstein, Panagiotis Karras

Keywords: spectral methods; subgraph localization; subgraph isomorphism; optimization

TL;DR: We propose SSL, an effective and scalable spectral method to localize a graph inside another graph.

Abstract: Several graph analysis problems are based on some variant of subgraph isomorphism: Given two graphs, G and Q, does G contain a subgraph isomorphic to Q? As this problem is NP-complete, past work usually avoids addressing it explicitly. In this paper, we propose a method that localizes, i.e., finds the best-match position of, Q in G, by aligning their Laplacian spectra and enhance its stability via bagging strategies; we relegate the finding of an exact node correspondence from Q to G to a subsequent and separate graph alignment task. We demonstrate that our localization strategy outperforms a baseline based on the state-of-the-art method for graph alignment in terms of accuracy on real graphs and scales to hundreds of nodes as no other method does.

Submission Type: Full paper proceedings track submission (max 9 main pages).

Agreement: Check this if you are okay with being contacted to participate in an anonymous survey.

Submission Number: 178