{"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/bayesian-estimation-of-bipartite-matchings","title":"Bayesian Estimation of Bipartite Matchings for Record Linkage","arxiv_id":"1601.06630","date":"2016-01-25","proceeding":null,"authors":["Mauricio Sadinle"],"abstract":"The bipartite record linkage task consists of merging two disparate datafiles\ncontaining information on two overlapping sets of entities. This is non-trivial\nin the absence of unique identifiers and it is important for a wide variety of\napplications given that it needs to be solved whenever we have to combine\ninformation from different sources. Most statistical techniques currently used\nfor record linkage are derived from a seminal paper by Fellegi and Sunter\n(1969). These techniques usually assume independence in the matching statuses\nof record pairs to derive estimation procedures and optimal point estimators.\nWe argue that this independence assumption is unreasonable and instead target a\nbipartite matching between the two datafiles as our parameter of interest.\nBayesian implementations allow us to quantify uncertainty on the matching\ndecisions and derive a variety of point estimators using different loss\nfunctions. We propose partial Bayes estimates that allow uncertain parts of the\nbipartite matching to be left unresolved. We evaluate our approach to record\nlinkage using a variety of challenging scenarios and show that it outperforms\nthe traditional methodology. We illustrate the advantages of our methods\nmerging two datafiles on casualties from the civil war of El Salvador.","url_abs":"http://arxiv.org/abs/1601.06630v1","url_pdf":"http://arxiv.org/pdf/1601.06630v1.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":"bayesian-estimation-of-bipartite-matchings","repo_url":"https://github.com/msadinle/BRL","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1601.06630","atlas_url":"https://app.syntology.ai/?focus=1601.06630","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}