{"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/memetic-graph-clustering","title":"Memetic Graph Clustering","arxiv_id":"1802.07034","date":"2018-02-20","proceeding":null,"authors":["Sonja Biedermann","Monika Henzinger","Christian Schulz","Bernhard Schuster"],"abstract":"It is common knowledge that there is no single best strategy for graph\nclustering, which justifies a plethora of existing approaches. In this paper,\nwe present a general memetic algorithm, VieClus, to tackle the graph clustering\nproblem. This algorithm can be adapted to optimize different objective\nfunctions. A key component of our contribution are natural recombine operators\nthat employ ensemble clusterings as well as multi-level techniques. Lastly, we\ncombine these techniques with a scalable communication protocol, producing a\nsystem that is able to compute high-quality solutions in a short amount of\ntime. We instantiate our scheme with local search for modularity and show that\nour algorithm successfully improves or reproduces all entries of the 10th\nDIMACS implementation~challenge under consideration using a small amount of\ntime.","url_abs":"http://arxiv.org/abs/1802.07034v1","url_pdf":"http://arxiv.org/pdf/1802.07034v1.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":"memetic-graph-clustering","repo_url":"https://github.com/VieClus/VieClus","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"clustering","task_name":"Clustering"},{"task_slug":"graph-clustering","task_name":"Graph Clustering"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}