{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/growing-graphs-with-hyperedge-replacement","title":"Growing Graphs with Hyperedge Replacement Graph Grammars","arxiv_id":"1608.03192","date":"2016-08-10","proceeding":null,"authors":["Salvador Aguiñaga","Rodrigo Palacios","David Chiang","Tim Weninger"],"abstract":"Discovering the underlying structures present in large real world graphs is a\nfundamental scientific problem. In this paper we show that a graph's clique\ntree can be used to extract a hyperedge replacement grammar. If we store an\nordering from the extraction process, the extracted graph grammar is guaranteed\nto generate an isomorphic copy of the original graph. Or, a stochastic\napplication of the graph grammar rules can be used to quickly create random\ngraphs. In experiments on large real world networks, we show that random\ngraphs, generated from extracted graph grammars, exhibit a wide range of\nproperties that are very similar to the original graphs. In addition to graph\nproperties like degree or eigenvector centrality, what a graph \"looks like\"\nultimately depends on small details in local graph substructures that are\ndifficult to define at a global level. We show that our generative graph model\nis able to preserve these local substructures when generating new graphs and\nperforms well on new and difficult tests of model robustness.","url_abs":"http://arxiv.org/abs/1608.03192v1","url_pdf":"http://arxiv.org/pdf/1608.03192v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"growing-graphs-with-hyperedge-replacement","repo_url":"https://github.com/nddsg/HRG","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}