{"id":"https://openalex.org/W4403864118","doi":"https://doi.org/10.1109/tevc.2024.3487624","title":"Pareto Optimization for Fair Subset Selection: A Case Study on Personalized Recommendation","display_name":"Pareto Optimization for Fair Subset Selection: A Case Study on Personalized Recommendation","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4403864118","doi":"https://doi.org/10.1109/tevc.2024.3487624"},"language":"en","primary_location":{"id":"doi:10.1109/tevc.2024.3487624","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tevc.2024.3487624","pdf_url":null,"source":{"id":"https://openalex.org/S93787993","display_name":"IEEE Transactions on Evolutionary Computation","issn_l":"1089-778X","issn":["1089-778X","1941-0026"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Evolutionary Computation","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/A5080798381","display_name":"Lei Zhang","orcid":"https://orcid.org/0000-0002-6447-2053"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0002-6447-2053","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102000332","display_name":"Zhanpeng Wang","orcid":"https://orcid.org/0000-0002-0178-4703"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhanpeng Wang","raw_affiliation_strings":["School of Computer Science and Technology, Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076244223","display_name":"Haipeng Yang","orcid":"https://orcid.org/0000-0001-9159-2707"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haipeng Yang","raw_affiliation_strings":["School of Computer Science and Technology, Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0001-9159-2707","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113979365","display_name":"Xiang Sun","orcid":"https://orcid.org/0009-0006-0275-983X"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Sun","raw_affiliation_strings":["School of Computer Science and Technology, Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0009-0006-0275-983X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100602238","display_name":"Fan Cheng","orcid":"https://orcid.org/0000-0003-0175-0818"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Cheng","raw_affiliation_strings":["School of Computer Science and Technology, Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0003-0175-0818","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I143868143"],"apc_list":{"value":2495,"currency":"USD","value_usd":2495},"apc_paid":null,"fwci":0.314,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.69773284,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.8930000066757202,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.8930000066757202,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/multi-objective-optimization","display_name":"Multi-objective optimization","score":0.6432629823684692},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5955297946929932},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5632221698760986},{"id":"https://openalex.org/keywords/pareto-principle","display_name":"Pareto principle","score":0.5453025102615356},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4814373850822449},{"id":"https://openalex.org/keywords/evolutionary-computation","display_name":"Evolutionary computation","score":0.42675548791885376},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42590251564979553},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3442557156085968},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25974714756011963}],"concepts":[{"id":"https://openalex.org/C68781425","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multi-objective optimization","level":2,"score":0.6432629823684692},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5955297946929932},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5632221698760986},{"id":"https://openalex.org/C137635306","wikidata":"https://www.wikidata.org/wiki/Q182667","display_name":"Pareto principle","level":2,"score":0.5453025102615356},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4814373850822449},{"id":"https://openalex.org/C105902424","wikidata":"https://www.wikidata.org/wiki/Q1197129","display_name":"Evolutionary computation","level":2,"score":0.42675548791885376},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42590251564979553},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3442557156085968},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25974714756011963}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tevc.2024.3487624","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tevc.2024.3487624","pdf_url":null,"source":{"id":"https://openalex.org/S93787993","display_name":"IEEE Transactions on Evolutionary Computation","issn_l":"1089-778X","issn":["1089-778X","1941-0026"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Evolutionary Computation","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5739591058","display_name":null,"funder_award_id":"62076001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6658230062","display_name":null,"funder_award_id":"61976001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2090178682","https://openalex.org/W4241467429","https://openalex.org/W2001591765","https://openalex.org/W2073147994","https://openalex.org/W1588199609","https://openalex.org/W2384474142","https://openalex.org/W1550055091","https://openalex.org/W2744462909","https://openalex.org/W3083133203","https://openalex.org/W1971520370"],"abstract_inverted_index":{"Subset":[0],"selection":[1,47,64],"is":[2,58,111,154,160,176,200,206],"a":[3,7,49,105,117],"fundamental":[4],"problem":[5,35],"across":[6],"wide":[8],"range":[9],"of":[10,48,52,99,152,179],"applications.":[11],"In":[12,102,182],"this":[13,103,157],"study,":[14],"we":[15,31,124,184],"explore":[16],"scenarios":[17],"where":[18,71,196],"the":[19,22,46,61,69,72,80,85,97,129,150,164,177,203,210,214,218,222,227],"variables":[20,53],"within":[21],"original":[23],"dataset":[24],"are":[25],"divided":[26],"into":[27],"distinct":[28],"groups.":[29],"Subsequently,":[30],"investigate":[32],"an":[33,197],"optimization":[34,75],"that":[36,126],"includes":[37],"extra":[38],"fairness":[39,86,94,119],"constraints":[40,95],"(i.e.,":[41],"partition":[42],"matroid":[43],"constraints),":[44],"restricting":[45],"specified":[50],"number":[51,178],"from":[54],"each":[55],"group,":[56],"which":[57],"known":[59],"as":[60],"fair":[62],"subset":[63],"(FSS)":[65],"problem.":[66],"First,":[67],"for":[68,113],"case":[70],"existing":[73],"Pareto":[74,106],"algorithms":[76],"do":[77,91],"not":[78,92],"have":[79],"ability":[81,131],"to":[82,89,187],"well":[83],"handle":[84],"constraints,":[87],"due":[88],"they":[90],"consider":[93],"in":[96,225],"process":[98],"solutions":[100],"generation.":[101],"article,":[104],"Optimization":[107],"algorithm":[108],"named":[109,192],"POFSS":[110,127,186,220],"proposed":[112,219],"FSS,":[114],"by":[115],"introducing":[116],"designed":[118,201],"balance":[120],"flip":[121],"operator.":[122],"Also,":[123],"prove":[125],"has":[128],"approximation":[130,158],"of$\\max":[132],"\\{":[133],"{}[{\\alpha":[134],"}/{l}](1-e^{-\\gamma":[135],"}),":[136],"{}({\\gamma":[137],"}/{k}),":[138],"1-e^{-r\\overline":[139],"{k}/k":[140],"}":[141],"\\}$in":[142],"polynomial":[143],"time":[144],"when$":[145],"l":[146,175],"\\lt":[147],"\\log":[148],"_{2}{n}$and":[149],"probability":[151],"mutation":[153],"constant$c/n~(c\\lt":[155],"2)$and":[156],"ratio":[159,205],"no":[161],"worse":[162],"than":[163],"previous":[165],"theoretical":[166],"result":[167],"($\\alpha":[168],"$,$\\gamma":[169],"$represent":[170],"two":[171],"submodular":[172],"ratios,":[173],"and":[174,202],"disjoint":[180],"groups).":[181],"addition,":[183],"apply":[185],"one":[188],"typical":[189],"FSS":[190],"task":[191,216],"personalized":[193],"recommendation":[194],"(PR),":[195],"acceleration":[198,204],"strategy":[199],"strictly":[207],"proved.":[208],"Finally,":[209],"experimental":[211],"results":[212],"on":[213],"PR":[215],"show":[217],"outperforms":[221],"state-of-the-art":[223],"methods":[224],"addressing":[226],"FSS.":[228]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}