{"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/random-mappings-designed-for-commercial","title":"Random mappings designed for commercial search engines","arxiv_id":"1507.05929","date":"2015-07-21","proceeding":null,"authors":["Donaldson Roger","Gupta Arijit","Plan Yaniv","Reimer Thomas"],"abstract":"We give a practical random mapping that takes any set of documents\nrepresented as vectors in Euclidean space and then maps them to a sparse subset\nof the Hamming cube while retaining ordering of inter-vector inner products.\nOnce represented in the sparse space, it is natural to index documents using\ncommercial text-based search engines which are specialized to take advantage of\nthis sparse and discrete structure for large-scale document retrieval. We give\na theoretical analysis of the mapping scheme, characterizing exact asymptotic\nbehavior and also giving non-asymptotic bounds which we verify through\nnumerical simulations. We balance the theoretical treatment with several\npractical considerations; these allow substantial speed up of the method. We\nfurther illustrate the use of this method on search over two real data sets: a\ncorpus of images represented by their color histograms, and a corpus of daily\nstock market index values.","url_abs":"http://arxiv.org/abs/1507.05929v1","url_pdf":"http://arxiv.org/pdf/1507.05929v1.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":"random-mappings-designed-for-commercial","repo_url":"https://gitlab.com/dgpr-sparse-search/code","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"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}