{"id":"https://openalex.org/W4387158099","doi":"https://doi.org/10.1145/3624918.3625318","title":"Automatic Feature Fairness in Recommendation via Adversaries","display_name":"Automatic Feature Fairness in Recommendation via Adversaries","publication_year":2023,"publication_date":"2023-11-23","ids":{"openalex":"https://openalex.org/W4387158099","doi":"https://doi.org/10.1145/3624918.3625318"},"language":"en","primary_location":{"id":"doi:10.1145/3624918.3625318","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3624918.3625318","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3624918.3625318","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017709678","display_name":"Hengchang Hu","orcid":"https://orcid.org/0000-0001-7847-0641"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Hengchang Hu","raw_affiliation_strings":["School of Computing, National University of Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Computing, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100983190","display_name":"Yiming Cao","orcid":"https://orcid.org/0009-0008-5953-496X"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yiming Cao","raw_affiliation_strings":["Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061585298","display_name":"Zhankui He","orcid":"https://orcid.org/0000-0002-9139-8004"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhankui He","raw_affiliation_strings":["Computer Science and Engineering, UC, San Diego, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, UC, San Diego, USA","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103099741","display_name":"Samson Tan","orcid":"https://orcid.org/0000-0003-1019-8228"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Samson Tan","raw_affiliation_strings":["AWS AI Research & Education, USA"],"affiliations":[{"raw_affiliation_string":"AWS AI Research & Education, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066305082","display_name":"Min\u2010Yen Kan","orcid":"https://orcid.org/0000-0001-8507-3716"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Min-Yen Kan","raw_affiliation_strings":["National University of Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5017709678"],"corresponding_institution_ids":["https://openalex.org/I165932596"],"apc_list":null,"apc_paid":null,"fwci":0.6959,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.76192268,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"245","last_page":"252"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9987000226974487,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9987000226974487,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9977999925613403,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.996999979019165,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.8715571165084839},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7795225381851196},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.6448434591293335},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.630558967590332},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5723373889923096},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5700744390487671},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.5574032664299011},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5474432706832886},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5202906727790833},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5176085233688354},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5064476728439331},{"id":"https://openalex.org/keywords/perturbation","display_name":"Perturbation (astronomy)","score":0.4725135266780853},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3483164608478546},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11958983540534973}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8715571165084839},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7795225381851196},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.6448434591293335},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.630558967590332},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5723373889923096},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5700744390487671},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5574032664299011},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5474432706832886},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5202906727790833},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5176085233688354},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5064476728439331},{"id":"https://openalex.org/C177918212","wikidata":"https://www.wikidata.org/wiki/Q803623","display_name":"Perturbation (astronomy)","level":2,"score":0.4725135266780853},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3483164608478546},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11958983540534973},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3624918.3625318","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3624918.3625318","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2309.15418","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2309.15418","pdf_url":"https://arxiv.org/pdf/2309.15418","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3624918.3625318","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3624918.3625318","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1593806347","https://openalex.org/W1945616565","https://openalex.org/W2295739661","https://openalex.org/W2397930585","https://openalex.org/W2604662567","https://openalex.org/W2629213068","https://openalex.org/W2768075475","https://openalex.org/W2787991113","https://openalex.org/W2797400361","https://openalex.org/W2798868970","https://openalex.org/W2896537337","https://openalex.org/W2950173087","https://openalex.org/W2954667104","https://openalex.org/W2962712142","https://openalex.org/W2963189767","https://openalex.org/W2963323306","https://openalex.org/W2963857521","https://openalex.org/W2972965281","https://openalex.org/W2989872778","https://openalex.org/W2998534896","https://openalex.org/W3034203759","https://openalex.org/W3048742138","https://openalex.org/W3080925373","https://openalex.org/W3088511490","https://openalex.org/W3097679710","https://openalex.org/W3102415183","https://openalex.org/W3102518922","https://openalex.org/W3103310105","https://openalex.org/W3103891807","https://openalex.org/W3105712174","https://openalex.org/W3106212003","https://openalex.org/W3153182568","https://openalex.org/W3155890782","https://openalex.org/W3156939347","https://openalex.org/W3163155381","https://openalex.org/W3164446335","https://openalex.org/W3164548985","https://openalex.org/W3166842523","https://openalex.org/W3168738558","https://openalex.org/W3170713142","https://openalex.org/W3181882572","https://openalex.org/W4226183797","https://openalex.org/W4231054948","https://openalex.org/W4232449914","https://openalex.org/W4239966440","https://openalex.org/W4280595799","https://openalex.org/W4287270373","https://openalex.org/W4293846201","https://openalex.org/W4296604534","https://openalex.org/W4302016201","https://openalex.org/W4387846851"],"related_works":["https://openalex.org/W2118717649","https://openalex.org/W2413243053","https://openalex.org/W410723623","https://openalex.org/W2015341305","https://openalex.org/W2035068594","https://openalex.org/W4225593417","https://openalex.org/W2573498121","https://openalex.org/W3022298670","https://openalex.org/W3160494304","https://openalex.org/W4312352990"],"abstract_inverted_index":{"Fairness":[0],"is":[1],"a":[2],"widely":[3],"discussed":[4],"topic":[5],"in":[6,15,149,157],"recommender":[7],"systems,":[8],"but":[9],"its":[10],"practical":[11],"implementation":[12],"faces":[13],"challenges":[14],"defining":[16],"sensitive":[17],"features":[18,122],"while":[19,117],"maintaining":[20],"recommendation":[21],"accuracy.":[22],"We":[23,50,73,126],"propose":[24],"feature":[25,40,48,53,63,82,89,108],"fairness":[26,151],"as":[27,139],"the":[28,128,134],"foundation":[29],"to":[30,61,94,107,114],"achieve":[31],"equitable":[32],"treatment":[33],"across":[34],"diverse":[35],"groups":[36],"defined":[37],"by":[38],"various":[39],"combinations.":[41],"This":[42,91],"improves":[43],"overall":[44],"accuracy":[45,153],"through":[46,55],"balanced":[47],"generalizability.":[49],"introduce":[51],"unbiased":[52],"learning":[54],"adversarial":[56,59,100,179],"training,":[57,185],"using":[58],"perturbation":[60,97,131,180],"enhance":[62],"representation.":[64],"The":[65],"adversaries":[66,75],"improve":[67,115],"model":[68],"generalization":[69],"for":[70,120,162],"under-represented":[71],"features.":[72],"adapt":[74],"automatically":[76],"based":[77,132],"on":[78,133],"two":[79],"forms":[80],"of":[81,88],"biases:":[83],"frequency":[84],"and":[85,99,152,160,164,170,191],"combination":[86,112],"variety":[87],"values.":[90],"allows":[92],"us":[93],"dynamically":[95],"adjust":[96],"strengths":[98,193],"training":[101,124],"weights.":[102],"Stronger":[103],"perturbations":[104,186],"are":[105],"applied":[106],"values":[109],"with":[110],"fewer":[111],"varieties":[113],"generalization,":[116],"higher":[118],"weights":[119],"low-frequency":[121],"address":[123],"imbalances.":[125],"leverage":[127],"Adaptive":[129],"Adversarial":[130],"widely-applied":[135],"Factorization":[136],"Machine":[137],"(AAFM)":[138],"our":[140],"backbone":[141],"model.":[142],"In":[143],"experiments,":[144],"AAFM":[145,155],"surpasses":[146],"strong":[147],"baselines":[148],"both":[150],"measures.":[154],"excels":[156],"providing":[158],"item-":[159],"user-fairness":[161],"single-":[163],"multi-feature":[165],"tasks,":[166],"showcasing":[167],"their":[168,192],"versatility":[169],"scalability.":[171],"To":[172],"maintain":[173],"good":[174],"accuracy,":[175],"we":[176],"find":[177],"that":[178],"must":[181],"be":[182],"well-managed:":[183],"during":[184],"should":[187,194],"not":[188],"overly":[189],"persist":[190],"decay.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}