{"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/a-practioners-guide-to-evaluating-entity","title":"A Practioner's Guide to Evaluating Entity Resolution Results","arxiv_id":"1509.04238","date":"2015-09-14","proceeding":null,"authors":["Matt Barnes"],"abstract":"Entity resolution (ER) is the task of identifying records belonging to the\nsame entity (e.g. individual, group) across one or multiple databases.\nIronically, it has multiple names: deduplication and record linkage, among\nothers. In this paper we survey metrics used to evaluate ER results in order to\niteratively improve performance and guarantee sufficient quality prior to\ndeployment. Some of these metrics are borrowed from multi-class classification\nand clustering domains, though some key differences exist differentiating\nentity resolution from general clustering. Menestrina et al. empirically showed\nrankings from these metrics often conflict with each other, thus our primary\nmotivation for studying them. This paper provides practitioners the basic\nknowledge to begin evaluating their entity resolution results.","url_abs":"http://arxiv.org/abs/1509.04238v1","url_pdf":"http://arxiv.org/pdf/1509.04238v1.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":"a-practioners-guide-to-evaluating-entity","repo_url":"https://github.com/patentsview/patentsview-evaluation","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"clustering","task_name":"Clustering"},{"task_slug":"entity-resolution","task_name":"Entity Resolution"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"multi-class-classification","task_name":"Multi-class Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1509.04238","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}