{"paper":{"title":"Graph Similarity and Approximate Isomorphism","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CC","cs.DM"],"primary_cat":"cs.DS","authors_text":"Gaurav Rattan, Gerhard J. Woeginger, Martin Grohe","submitted_at":"2018-02-23T12:54:40Z","abstract_excerpt":"The graph similarity problem, also known as approximate graph isomorphism or graph matching problem, has been extensively studied in the machine learning community, but has not received much attention in the algorithms community: Given two graphs $G,H$ of the same order $n$ with adjacency matrices $A_G,A_H$, a well-studied measure of similarity is the Frobenius distance \\[ \\mathrm{dist}(G,H):=\\min_{\\pi}\\|A_G^\\pi-A_H\\|_F, \\] where $\\pi$ ranges over all permutations of the vertex set of $G$, where $A_G^\\pi$ denotes the matrix obtained from $A_G$ by permuting rows and columns according to $\\pi$, "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.08509","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}