{"id":"https://openalex.org/W4226344625","doi":"https://doi.org/10.1145/3624918.3625313","title":"Vertical Allocation-based Fair Exposure Amortizing in Ranking","display_name":"Vertical Allocation-based Fair Exposure Amortizing in Ranking","publication_year":2023,"publication_date":"2023-11-23","ids":{"openalex":"https://openalex.org/W4226344625","doi":"https://doi.org/10.1145/3624918.3625313"},"language":"en","primary_location":{"id":"doi:10.1145/3624918.3625313","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3624918.3625313","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/10.1145/3624918.3625313","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100338214","display_name":"Tao Yang","orcid":"https://orcid.org/0000-0002-7282-2463"},"institutions":[{"id":"https://openalex.org/I223532165","display_name":"University of Utah","ror":"https://ror.org/03r0ha626","country_code":"US","type":"education","lineage":["https://openalex.org/I223532165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tao Yang","raw_affiliation_strings":["Kahlert School of Computing, University of Utah, USA"],"raw_orcid":"https://orcid.org/0000-0002-7282-2463","affiliations":[{"raw_affiliation_string":"Kahlert School of Computing, University of Utah, USA","institution_ids":["https://openalex.org/I223532165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036683049","display_name":"Zhichao Xu","orcid":"https://orcid.org/0000-0002-2370-4487"},"institutions":[{"id":"https://openalex.org/I223532165","display_name":"University of Utah","ror":"https://ror.org/03r0ha626","country_code":"US","type":"education","lineage":["https://openalex.org/I223532165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhichao Xu","raw_affiliation_strings":["Kahlert School of Computing, University of Utah, USA"],"raw_orcid":"https://orcid.org/0000-0002-2370-4487","affiliations":[{"raw_affiliation_string":"Kahlert School of Computing, University of Utah, USA","institution_ids":["https://openalex.org/I223532165"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089655391","display_name":"Qingyao Ai","orcid":"https://orcid.org/0000-0002-5030-709X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingyao Ai","raw_affiliation_strings":["DCST, Quan Cheng Laboratory, Zhongguancun Laboratory, Tsinghua University, China"],"raw_orcid":"https://orcid.org/0000-0002-5030-709X","affiliations":[{"raw_affiliation_string":"DCST, Quan Cheng Laboratory, Zhongguancun Laboratory, Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1896,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.8160133,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"234","last_page":"244"},"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":0.996399998664856,"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":0.996399998664856,"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/T11045","display_name":"Privacy, Security, and Data Protection","score":0.989799976348877,"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"}},{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.984499990940094,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.9012949466705322},{"id":"https://openalex.org/keywords/amortizing-loan","display_name":"Amortizing loan","score":0.7095893621444702},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.6508216857910156},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5865033864974976},{"id":"https://openalex.org/keywords/balance","display_name":"Balance (ability)","score":0.4725461006164551},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.30440646409988403},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2381359040737152},{"id":"https://openalex.org/keywords/loan","display_name":"Loan","score":0.10417550802230835},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.07603341341018677}],"concepts":[{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.9012949466705322},{"id":"https://openalex.org/C51034333","wikidata":"https://www.wikidata.org/wiki/Q4747796","display_name":"Amortizing loan","level":5,"score":0.7095893621444702},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.6508216857910156},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5865033864974976},{"id":"https://openalex.org/C168031717","wikidata":"https://www.wikidata.org/wiki/Q1530280","display_name":"Balance (ability)","level":2,"score":0.4725461006164551},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.30440646409988403},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2381359040737152},{"id":"https://openalex.org/C2777764128","wikidata":"https://www.wikidata.org/wiki/Q189539","display_name":"Loan","level":2,"score":0.10417550802230835},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.07603341341018677},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C107235782","wikidata":"https://www.wikidata.org/wiki/Q5188121","display_name":"Cross-collateralization","level":4,"score":0.0},{"id":"https://openalex.org/C71387314","wikidata":"https://www.wikidata.org/wiki/Q494128","display_name":"Non-performing loan","level":3,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3624918.3625313","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3624918.3625313","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:2204.03046","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2204.03046","pdf_url":"https://arxiv.org/pdf/2204.03046","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3624918.3625313","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3624918.3625313","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":[{"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals","score":0.46000000834465027}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":77,"referenced_works":["https://openalex.org/W39762900","https://openalex.org/W1787140601","https://openalex.org/W1961345416","https://openalex.org/W1992549066","https://openalex.org/W2014352947","https://openalex.org/W2026784708","https://openalex.org/W2045471213","https://openalex.org/W2050096199","https://openalex.org/W2061873838","https://openalex.org/W2069870183","https://openalex.org/W2154739689","https://openalex.org/W2530395818","https://openalex.org/W2550925836","https://openalex.org/W2573167395","https://openalex.org/W2604961496","https://openalex.org/W2704480242","https://openalex.org/W2728544954","https://openalex.org/W2734755249","https://openalex.org/W2748058847","https://openalex.org/W2768894107","https://openalex.org/W2769473018","https://openalex.org/W2787991113","https://openalex.org/W2797400361","https://openalex.org/W2809701591","https://openalex.org/W2891340679","https://openalex.org/W2897363137","https://openalex.org/W2905569957","https://openalex.org/W2922169395","https://openalex.org/W2963189767","https://openalex.org/W2964247748","https://openalex.org/W2965366403","https://openalex.org/W2997842202","https://openalex.org/W3008301325","https://openalex.org/W3023071042","https://openalex.org/W3028722847","https://openalex.org/W3099814932","https://openalex.org/W3102092462","https://openalex.org/W3102518922","https://openalex.org/W3102540985","https://openalex.org/W3103006639","https://openalex.org/W3104475013","https://openalex.org/W3105035347","https://openalex.org/W3105507623","https://openalex.org/W3105712174","https://openalex.org/W3123029532","https://openalex.org/W3129302614","https://openalex.org/W3130740428","https://openalex.org/W3154672276","https://openalex.org/W3155690528","https://openalex.org/W3155877950","https://openalex.org/W3156662033","https://openalex.org/W3160411391","https://openalex.org/W3171919372","https://openalex.org/W3189344277","https://openalex.org/W3205761523","https://openalex.org/W3211130843","https://openalex.org/W3213774197","https://openalex.org/W4200503933","https://openalex.org/W4220802549","https://openalex.org/W4224950663","https://openalex.org/W4225378011","https://openalex.org/W4283022819","https://openalex.org/W4283156235","https://openalex.org/W4283156909","https://openalex.org/W4284675352","https://openalex.org/W4284677642","https://openalex.org/W4284687761","https://openalex.org/W4284690424","https://openalex.org/W4287077603","https://openalex.org/W4292218840","https://openalex.org/W4294241863","https://openalex.org/W4302322961","https://openalex.org/W4312048084","https://openalex.org/W4367047007","https://openalex.org/W4378711683","https://openalex.org/W4378713513","https://openalex.org/W6802418890"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2085384747","https://openalex.org/W2088166309","https://openalex.org/W2342948995","https://openalex.org/W2150136235","https://openalex.org/W2053591227","https://openalex.org/W2581240705","https://openalex.org/W2041353081","https://openalex.org/W2568183987","https://openalex.org/W4226344625"],"abstract_inverted_index":{"Result":[0],"ranking":[1,18,25,92,111,165,180],"often":[2],"affects":[3],"consumer":[4],"satisfaction":[5,23],"as":[6,8],"well":[7],"the":[9,17,57,76,107,135,187,191],"amount":[10],"of":[11,36,78,127,138],"exposure":[12,37,108,162],"each":[13],"item":[14,48],"receives":[15],"in":[16,110,125,152,182],"services.":[19,112],"Myopically":[20],"maximizing":[21],"customer":[22],"by":[24,41],"items":[26],"only":[27],"according":[28],"to":[29,33,55,87,133,156],"relevance":[30,93],"will":[31,52],"lead":[32],"unfair":[34,42],"distribution":[35],"for":[38,47,73,98,118],"items,":[39],"followed":[40],"opportunities":[43],"and":[44,59,75,81,94,164,190],"economic":[45],"gains":[46],"producers/providers.":[49],"Such":[50],"unfairness":[51],"force":[53],"providers":[54,62,82],"leave":[56],"system":[58],"discourage":[60],"new":[61],"from":[63,185],"coming":[64],"in.":[65],"Eventually,":[66],"fewer":[67],"purchase":[68],"options":[69],"would":[70,83],"be":[71,84,123],"left":[72],"consumers,":[74],"utilities":[77],"both":[79,99,186],"consumers":[80],"harmed.":[85],"Thus,":[86],"maintain":[88],"a":[89,143,158],"balance":[90,160],"between":[91,161],"fairness":[95,109,120,163],"is":[96],"crucial":[97],"parties.":[100],"In":[101],"this":[102],"paper,":[103],"we":[104],"focus":[105],"on":[106,169],"We":[113,140],"demonstrate":[114],"that":[115,174],"existing":[116],"methods":[117],"amortized":[119],"optimization":[121],"could":[122],"suboptimal":[124],"terms":[126],"fairness-relevance":[128],"tradeoff":[129],"because":[130],"they":[131],"fail":[132],"utilize":[134],"prior":[136],"knowledge":[137],"consumers.":[139],"further":[141],"propose":[142],"novel":[144],"algorithm":[145],"named":[146],"Vertical":[147],"Allocation-based":[148],"Fair":[149],"Exposure":[150],"Amortizing":[151],"Ranking,":[153],"or":[154],"VerFair,":[155],"reach":[157],"better":[159],"performance.":[166],"Extensive":[167],"experiments":[168],"three":[170],"real-world":[171],"datasets":[172],"show":[173],"VerFair":[175],"significantly":[176],"outperforms":[177],"state-of-the-art":[178],"fair":[179],"algorithms":[181],"fairness-performance":[183],"trade-offs":[184],"individual":[188],"level":[189],"group":[192],"level.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}