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This demonstration showcases FairEM360, a framework for 1) auditing the output of entity matchers across a wide range of fairness measures and paradigms, 2) providing potential explanations for the underlying reasons for unfairness, and 3) providing resolutions for the unfairness issues through an exploratory process with human-in-the-loop feedback, utilizing an ensemble of matchers. We aspire for FairEM360 to contribute to the prioritization of fairness as a key consideration in the evaluation of EM pipelines.<\/jats:p>","DOI":"10.14778\/3685800.3685889","type":"journal-article","created":{"date-parts":[[2024,11,8]],"date-time":"2024-11-08T17:25:21Z","timestamp":1731086721000},"page":"4417-4420","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["FairEM360: A Suite for Responsible Entity Matching"],"prefix":"10.14778","volume":"17","author":[{"given":"Nima","family":"Shahbazi","sequence":"first","affiliation":[{"name":"University of Illinois, Chicago"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mahdi","family":"Erfanian","sequence":"additional","affiliation":[{"name":"University of Illinois, Chicago"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abolfazl","family":"Asudeh","sequence":"additional","affiliation":[{"name":"University of Illinois, Chicago"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fatemeh","family":"Nargesian","sequence":"additional","affiliation":[{"name":"University of Rochester"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Divesh","family":"Srivastava","sequence":"additional","affiliation":[{"name":"AT&amp;T Chief Data Office"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,11,8]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"crossref","unstructured":"Cheng Fu Xianpei Han Jiaming He and Le Sun. 2021. Hierarchical matching network for heterogeneous entity resolution. In IJCAI. 3665--3671.","DOI":"10.24963\/ijcai.2020\/507"},{"key":"e_1_2_1_2_1","volume-title":"Magellan: Toward building entity matching management systems","author":"Konda Pradap Venkatramanan","year":"2018","unstructured":"Pradap Venkatramanan Konda. 2018. Magellan: Toward building entity matching management systems. The University of Wisconsin-Madison."},{"key":"e_1_2_1_3_1","doi-asserted-by":"crossref","unstructured":"Y. Li J. Li Y. Suhara A. Doan and W. Tan. 2020. Deep entity matching with pre-trained language models. PVLDB 14 1 (2020).","DOI":"10.14778\/3421424.3421431"},{"key":"e_1_2_1_4_1","unstructured":"Christoph Molnar. 2020. Interpretable machine learning. Lulu. com."},{"key":"e_1_2_1_5_1","doi-asserted-by":"crossref","unstructured":"Sidharth Mudgal Han Li and et al. 2018. Deep learning for entity matching: A design space exploration. 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In TheWebConf. 2634--2640.","DOI":"10.1145\/3366423.3380017"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/3685800.3685889","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,31]],"date-time":"2024-12-31T05:24:26Z","timestamp":1735622666000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/3685800.3685889"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8]]},"references-count":11,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2024,8]]}},"alternative-id":["10.14778\/3685800.3685889"],"URL":"https:\/\/doi.org\/10.14778\/3685800.3685889","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2024,8]]},"assertion":[{"value":"2024-11-08","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}