{"id":"https://openalex.org/W4386125399","doi":"https://doi.org/10.14778/3611479.3611525","title":"Through the Fairness Lens: Experimental Analysis and Evaluation of Entity Matching","display_name":"Through the Fairness Lens: Experimental Analysis and Evaluation of Entity Matching","publication_year":2023,"publication_date":"2023-07-01","ids":{"openalex":"https://openalex.org/W4386125399","doi":"https://doi.org/10.14778/3611479.3611525"},"language":"en","primary_location":{"id":"doi:10.14778/3611479.3611525","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3611479.3611525","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the VLDB Endowment","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032735930","display_name":"Nima Shahbazi","orcid":"https://orcid.org/0000-0001-7016-3807"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nima Shahbazi","raw_affiliation_strings":["University of Illinois Chicago"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois Chicago","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092427222","display_name":"Nikola Danevski","orcid":null},"institutions":[{"id":"https://openalex.org/I5388228","display_name":"University of Rochester","ror":"https://ror.org/022kthw22","country_code":"US","type":"education","lineage":["https://openalex.org/I5388228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nikola Danevski","raw_affiliation_strings":["University of Rochester"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Rochester","institution_ids":["https://openalex.org/I5388228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012572863","display_name":"Fatemeh Nargesian","orcid":"https://orcid.org/0000-0002-4710-8719"},"institutions":[{"id":"https://openalex.org/I5388228","display_name":"University of Rochester","ror":"https://ror.org/022kthw22","country_code":"US","type":"education","lineage":["https://openalex.org/I5388228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fatemeh Nargesian","raw_affiliation_strings":["University of Rochester"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Rochester","institution_ids":["https://openalex.org/I5388228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027319416","display_name":"Abolfazl Asudeh","orcid":"https://orcid.org/0000-0002-5251-6186"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abolfazl Asudeh","raw_affiliation_strings":["University of Illinois Chicago"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois Chicago","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088315797","display_name":"Divesh Srivastava","orcid":"https://orcid.org/0000-0002-7609-9217"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Divesh Srivastava","raw_affiliation_strings":["AT&T Chief Data Office"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AT&T Chief Data Office","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.4012,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.93882404,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"16","issue":"11","first_page":"3279","last_page":"3292"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11045","display_name":"Privacy, Security, and Data Protection","score":0.9879000186920166,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.7286506295204163},{"id":"https://openalex.org/keywords/through-the-lens-metering","display_name":"Through-the-lens metering","score":0.6427885890007019},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.6368225812911987},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5822256803512573},{"id":"https://openalex.org/keywords/audit","display_name":"Audit","score":0.5815442204475403},{"id":"https://openalex.org/keywords/parity","display_name":"Parity (physics)","score":0.49043986201286316},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.32801568508148193},{"id":"https://openalex.org/keywords/lens","display_name":"Lens (geology)","score":0.2951904535293579},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23146387934684753},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18071186542510986},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16299539804458618},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.1539631187915802},{"id":"https://openalex.org/keywords/accounting","display_name":"Accounting","score":0.07732555270195007}],"concepts":[{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.7286506295204163},{"id":"https://openalex.org/C43091099","wikidata":"https://www.wikidata.org/wiki/Q1067788","display_name":"Through-the-lens metering","level":3,"score":0.6427885890007019},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.6368225812911987},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5822256803512573},{"id":"https://openalex.org/C199521495","wikidata":"https://www.wikidata.org/wiki/Q181487","display_name":"Audit","level":2,"score":0.5815442204475403},{"id":"https://openalex.org/C2777151079","wikidata":"https://www.wikidata.org/wiki/Q141160","display_name":"Parity (physics)","level":2,"score":0.49043986201286316},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.32801568508148193},{"id":"https://openalex.org/C15336307","wikidata":"https://www.wikidata.org/wiki/Q1766051","display_name":"Lens (geology)","level":2,"score":0.2951904535293579},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23146387934684753},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18071186542510986},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16299539804458618},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.1539631187915802},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.07732555270195007},{"id":"https://openalex.org/C109214941","wikidata":"https://www.wikidata.org/wiki/Q18334","display_name":"Particle physics","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C78762247","wikidata":"https://www.wikidata.org/wiki/Q1273174","display_name":"Petroleum engineering","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.14778/3611479.3611525","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3611479.3611525","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the VLDB Endowment","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.6499999761581421,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W648207664","https://openalex.org/W2014352947","https://openalex.org/W2100960835","https://openalex.org/W2104511295","https://openalex.org/W2114764731","https://openalex.org/W2250539671","https://openalex.org/W2286724461","https://openalex.org/W2399361902","https://openalex.org/W2733471169","https://openalex.org/W2775696413","https://openalex.org/W2798649495","https://openalex.org/W2896331720","https://openalex.org/W2945883855","https://openalex.org/W2946123203","https://openalex.org/W2962762307","https://openalex.org/W2963100392","https://openalex.org/W2986691260","https://openalex.org/W3012733951","https://openalex.org/W3014295153","https://openalex.org/W3045854241","https://openalex.org/W3085666889","https://openalex.org/W3092962901","https://openalex.org/W3156469762","https://openalex.org/W3173874427","https://openalex.org/W3174324482","https://openalex.org/W3197182341","https://openalex.org/W3209119957","https://openalex.org/W4281396256","https://openalex.org/W4292200197","https://openalex.org/W4306316980","https://openalex.org/W4312765260","https://openalex.org/W4320024257","https://openalex.org/W4386125399"],"related_works":["https://openalex.org/W2032233321","https://openalex.org/W3121970507","https://openalex.org/W2110028391","https://openalex.org/W54497855","https://openalex.org/W217960748","https://openalex.org/W3125814499","https://openalex.org/W2090827041","https://openalex.org/W187246281","https://openalex.org/W2565703248","https://openalex.org/W2143548620"],"abstract_inverted_index":{"Entity":[0],"matching":[1],"(EM)":[2],"is":[3,126],"a":[4,14,21,61],"challenging":[5],"problem":[6],"studied":[7],"by":[8],"different":[9,138],"communities":[10],"for":[11,78,137],"over":[12],"half":[13],"century.":[15],"Algorithmic":[16],"fairness":[17,46,133],"has":[18,41],"also":[19],"become":[20],"timely":[22],"topic":[23],"to":[24,44,119,128,141],"address":[25],"machine":[26],"bias":[27],"and":[28,108,153],"its":[29],"societal":[30],"impacts.":[31],"Despite":[32],"extensive":[33,57],"research":[34],"on":[35],"these":[36],"two":[37,71,95],"topics,":[38],"little":[39],"attention":[40],"been":[42],"paid":[43],"the":[45,79,85],"of":[47,60,63,81,87,163],"entity":[48],"matching.":[49],"Towards":[50],"addressing":[51],"this":[52,67],"gap,":[53],"we":[54],"perform":[55],"an":[56],"experimental":[58],"evaluation":[59],"variety":[62],"EM":[64,83,165],"techniques":[65],"in":[66,98,115,159],"paper.":[68],"We":[69],"generated":[70],"social":[72],"datasets":[73,77],"from":[74],"publicly":[75],"available":[76],"purpose":[80],"auditing":[82],"through":[84],"lens":[86],"fairness.":[88],"Our":[89],"findings":[90],"underscore":[91],"potential":[92],"unfairness":[93],"under":[94],"common":[96],"conditions":[97],"real-world":[99],"societies:":[100],"(i)":[101],"when":[102,110],"some":[103,116],"demographic":[104],"groups":[105,117],"are":[106,112,135],"over-represented,":[107],"(ii)":[109],"names":[111],"more":[113,161],"similar":[114],"compared":[118],"others.":[120],"Among":[121],"our":[122],"many":[123],"findings,":[124],"it":[125],"noteworthy":[127],"mention":[129],"that":[130],"while":[131],"various":[132],"definitions":[134],"valuable":[136],"settings,":[139],"due":[140],"EM's":[142],"class":[143],"imbalance":[144],"nature,":[145],"measures":[146],"such":[147],"as":[148],"positive":[149,155],"predictive":[150],"value":[151],"parity":[152,157],"true":[154],"rate":[156],"are,":[158],"general,":[160],"capable":[162],"revealing":[164],"unfairness.":[166]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":2}],"updated_date":"2026-06-19T17:40:00.097472","created_date":"2025-10-10T00:00:00"}