{"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/an-online-hierarchical-algorithm-for-extreme","title":"An Online Hierarchical Algorithm for Extreme Clustering","arxiv_id":"1704.01858","date":"2017-04-06","proceeding":null,"authors":["Ari Kobren","Nicholas Monath","Akshay Krishnamurthy","Andrew McCallum"],"abstract":"Many modern clustering methods scale well to a large number of data items, N,\nbut not to a large number of clusters, K. This paper introduces PERCH, a new\nnon-greedy algorithm for online hierarchical clustering that scales to both\nmassive N and K--a problem setting we term extreme clustering. Our algorithm\nefficiently routes new data points to the leaves of an incrementally-built\ntree. Motivated by the desire for both accuracy and speed, our approach\nperforms tree rotations for the sake of enhancing subtree purity and\nencouraging balancedness. We prove that, under a natural separability\nassumption, our non-greedy algorithm will produce trees with perfect dendrogram\npurity regardless of online data arrival order. Our experiments demonstrate\nthat PERCH constructs more accurate trees than other tree-building clustering\nalgorithms and scales well with both N and K, achieving a higher quality\nclustering than the strongest flat clustering competitor in nearly half the\ntime.","url_abs":"http://arxiv.org/abs/1704.01858v1","url_pdf":"http://arxiv.org/pdf/1704.01858v1.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":"an-online-hierarchical-algorithm-for-extreme","repo_url":"https://github.com/iesl/xcluster","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null},{"paper_slug":"an-online-hierarchical-algorithm-for-extreme","repo_url":"https://github.com/nikhilRP/oslo","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"clustering","task_name":"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}