{"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/permutation-search-methods-are-efficient-yet","title":"Permutation Search Methods are Efficient, Yet Faster Search is Possible","arxiv_id":"1506.03163","date":"2015-06-10","proceeding":null,"authors":["Bilegsaikhan Naidan","Leonid Boytsov","Eric Nyberg"],"abstract":"We survey permutation-based methods for approximate k-nearest neighbor\nsearch. In these methods, every data point is represented by a ranked list of\npivots sorted by the distance to this point. Such ranked lists are called\npermutations. The underpinning assumption is that, for both metric and\nnon-metric spaces, the distance between permutations is a good proxy for the\ndistance between original points. Thus, it should be possible to efficiently\nretrieve most true nearest neighbors by examining only a tiny subset of data\npoints whose permutations are similar to the permutation of a query. We further\ntest this assumption by carrying out an extensive experimental evaluation where\npermutation methods are pitted against state-of-the art benchmarks (the\nmulti-probe LSH, the VP-tree, and proximity-graph based retrieval) on a variety\nof realistically large data set from the image and textual domain. The focus is\non the high-accuracy retrieval methods for generic spaces. Additionally, we\nassume that both data and indices are stored in main memory. We find\npermutation methods to be reasonably efficient and describe a setup where these\nmethods are most useful. To ease reproducibility, we make our software and data\nsets publicly available.","url_abs":"http://arxiv.org/abs/1506.03163v4","url_pdf":"http://arxiv.org/pdf/1506.03163v4.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":"permutation-search-methods-are-efficient-yet","repo_url":"https://github.com/searchivarius/nmslib","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":{"status":"gone","observed_at":"2026-09-18","how":"tree_404+repo_404"}}],"tasks":[{"task_slug":"retrieval","task_name":"Retrieval"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}