{"id":"https://openalex.org/W4306316936","doi":"https://doi.org/10.1145/3511808.3557501","title":"Fairness of Machine Learning in Search Engines","display_name":"Fairness of Machine Learning in Search Engines","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4306316936","doi":"https://doi.org/10.1145/3511808.3557501"},"language":"en","primary_location":{"id":"doi:10.1145/3511808.3557501","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557501","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101972978","display_name":"Yi Fang","orcid":"https://orcid.org/0000-0001-6572-4315"},"institutions":[{"id":"https://openalex.org/I16269868","display_name":"Santa Clara University","ror":"https://ror.org/03ypqe447","country_code":"US","type":"education","lineage":["https://openalex.org/I16269868"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yi Fang","raw_affiliation_strings":["Santa Clara University, Santa Clara, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Santa Clara University, Santa Clara, CA, USA","institution_ids":["https://openalex.org/I16269868"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086089915","display_name":"Hongfu Liu","orcid":"https://orcid.org/0000-0002-4261-8154"},"institutions":[{"id":"https://openalex.org/I6902469","display_name":"Brandeis University","ror":"https://ror.org/05abbep66","country_code":"US","type":"education","lineage":["https://openalex.org/I6902469"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongfu Liu","raw_affiliation_strings":["Brandeis University, Waltham, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Brandeis University, Waltham, MA, USA","institution_ids":["https://openalex.org/I6902469"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021486404","display_name":"Zhiqiang Tao","orcid":"https://orcid.org/0000-0002-5639-7540"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhiqiang Tao","raw_affiliation_strings":["Rochester Institute of Technology, Rochester, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology, Rochester, NY, USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026283694","display_name":"Mikhail Yurochkin","orcid":"https://orcid.org/0000-0003-0153-6811"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mikhail Yurochkin","raw_affiliation_strings":["IBM Research & MIT-IBM Watson AI lab, Cambridge, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research & MIT-IBM Watson AI lab, Cambridge, MA, USA","institution_ids":["https://openalex.org/I1341412227"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6375,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.78123295,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"5132","last_page":"5135"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9664000272750854,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11045","display_name":"Privacy, Security, and Data Protection","score":0.9538999795913696,"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/computer-science","display_name":"Computer science","score":0.8092058897018433},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.7559171915054321},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6319290399551392},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6284630298614502},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5669832229614258},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5141063332557678},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.4889882802963257},{"id":"https://openalex.org/keywords/search-engine","display_name":"Search engine","score":0.4843057692050934},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.446006178855896},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.40661343932151794},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.34923964738845825}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8092058897018433},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.7559171915054321},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6319290399551392},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6284630298614502},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5669832229614258},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5141063332557678},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.4889882802963257},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.4843057692050934},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.446006178855896},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.40661343932151794},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.34923964738845825}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3511808.3557501","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557501","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W2100960835","https://openalex.org/W2704480242","https://openalex.org/W2787991113","https://openalex.org/W2912638141","https://openalex.org/W2950173087","https://openalex.org/W2963116854","https://openalex.org/W2963392941","https://openalex.org/W2964031043","https://openalex.org/W2964751853","https://openalex.org/W2974817986","https://openalex.org/W2985745615","https://openalex.org/W3003545719","https://openalex.org/W3012903288","https://openalex.org/W3033733989","https://openalex.org/W3034235662","https://openalex.org/W3092499828","https://openalex.org/W3102092462","https://openalex.org/W3102518922","https://openalex.org/W3103891807","https://openalex.org/W3123223998","https://openalex.org/W3153906321","https://openalex.org/W3164238513","https://openalex.org/W3165956705","https://openalex.org/W3167423814","https://openalex.org/W3187057914","https://openalex.org/W3192198661","https://openalex.org/W3208316297","https://openalex.org/W3208695477","https://openalex.org/W3216389579","https://openalex.org/W4225159056","https://openalex.org/W4284673705","https://openalex.org/W4284687761","https://openalex.org/W4285613665","https://openalex.org/W4300482433"],"related_works":["https://openalex.org/W3127142483","https://openalex.org/W4385565564","https://openalex.org/W2898073868","https://openalex.org/W2138488530","https://openalex.org/W4390446658","https://openalex.org/W2971071571","https://openalex.org/W2798835721","https://openalex.org/W2387658907","https://openalex.org/W2922169395","https://openalex.org/W25098770"],"abstract_inverted_index":{"Fairness":[0],"has":[1],"gained":[2],"increasing":[3],"importance":[4],"in":[5,43,63,90,130],"a":[6],"variety":[7],"of":[8,16,21,28,32,34,61,101],"AI":[9],"and":[10,38,51,73,75,99,124,127],"machine":[11,22,64],"learning":[12,69,77],"contexts.":[13],"As":[14],"one":[15],"the":[17,29,59,85,94,118],"most":[18],"ubiquitous":[19],"applications":[20],"learning,":[23,65],"search":[24,44,91],"engines":[25],"mediate":[26],"much":[27],"information":[30,108],"experiences":[31],"members":[33],"society.":[35],"Consequently,":[36],"understanding":[37],"mitigating":[39],"potential":[40],"algorithmic":[41,112],"unfairness":[42],"have":[45],"become":[46],"crucial":[47],"for":[48,66],"both":[49,67],"users":[50],"systems.":[52],"In":[53],"this":[54,122,131],"tutorial,":[55],"we":[56],"will":[57,82,105],"introduce":[58],"fundamentals":[60],"fairness":[62,89,95],"supervised":[68],"such":[70,78],"as":[71,79],"classification":[72],"ranking,":[74],"unsupervised":[76],"clustering.":[80],"We":[81],"then":[83],"present":[84],"existing":[86],"work":[87],"on":[88,121],"engines,":[92],"including":[93],"definitions,":[96],"evaluation":[97],"metrics,":[98],"taxonomies":[100],"methodologies.":[102],"This":[103],"tutorial":[104],"help":[106],"orient":[107],"retrieval":[109],"researchers":[110,126],"to":[111,117],"fairness,":[113],"provide":[114],"an":[115],"introduction":[116],"growing":[119],"literature":[120],"topic,":[123],"gathering":[125],"practitioners":[128],"interested":[129],"research":[132],"direction.":[133]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}