{"id":"https://openalex.org/W3115572006","doi":"https://doi.org/10.1145/3437963.3441769","title":"Leave No User Behind: Towards Improving the Utility of Recommender Systems for Non-mainstream Users","display_name":"Leave No User Behind: Towards Improving the Utility of Recommender Systems for Non-mainstream Users","publication_year":2021,"publication_date":"2021-03-06","ids":{"openalex":"https://openalex.org/W3115572006","doi":"https://doi.org/10.1145/3437963.3441769","mag":"3115572006"},"language":"en","primary_location":{"id":"doi:10.1145/3437963.3441769","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3437963.3441769","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3437963.3441769","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 14th ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3437963.3441769","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Roger Zhe Li","orcid":null},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Roger Zhe Li","raw_affiliation_strings":["Delft University of Technology, Delft, Netherlands"],"affiliations":[{"raw_affiliation_string":"Delft University of Technology, Delft, Netherlands","institution_ids":["https://openalex.org/I98358874"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Juli\u00e1n Urbano","orcid":null},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Juli\u00e1n Urbano","raw_affiliation_strings":["Delft University of Technology, Delft, Netherlands"],"affiliations":[{"raw_affiliation_string":"Delft University of Technology, Delft, Netherlands","institution_ids":["https://openalex.org/I98358874"]}]},{"author_position":"last","author":{"id":null,"display_name":"Alan Hanjalic","orcid":null},"institutions":[{"id":"https://openalex.org/I98358874","display_name":"Delft University of Technology","ror":"https://ror.org/02e2c7k09","country_code":"NL","type":"education","lineage":["https://openalex.org/I98358874"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Alan Hanjalic","raw_affiliation_strings":["Delft University of Technology, Delft, Netherlands"],"affiliations":[{"raw_affiliation_string":"Delft University of Technology, Delft, Netherlands","institution_ids":["https://openalex.org/I98358874"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I98358874"],"apc_list":null,"apc_paid":null,"fwci":6.2328,"has_fulltext":true,"cited_by_count":26,"citation_normalized_percentile":{"value":0.96370212,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"103","last_page":"111"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10203","display_name":"Recommender Systems and Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9940000176429749,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9765999913215637,"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/recommender-system","display_name":"Recommender system","score":0.815500020980835},{"id":"https://openalex.org/keywords/mainstream","display_name":"Mainstream","score":0.8119999766349792},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.732200026512146},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6018000245094299},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5738000273704529},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.542900025844574}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8194000124931335},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.815500020980835},{"id":"https://openalex.org/C2777617010","wikidata":"https://www.wikidata.org/wiki/Q18957","display_name":"Mainstream","level":2,"score":0.8119999766349792},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.732200026512146},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6018000245094299},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5738000273704529},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.542900025844574},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.5055999755859375},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4560999870300293},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39010000228881836},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.3521000146865845},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.336899995803833},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3352000117301941},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.32249999046325684},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2996000051498413},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2816999852657318},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.2581000030040741},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.2581000030040741}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3437963.3441769","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3437963.3441769","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3437963.3441769","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 14th ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2102.01744","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2102.01744","pdf_url":"https://arxiv.org/pdf/2102.01744","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":"","raw_type":"text"},{"id":"pmh:oai:tudelft.nl:uuid:10f51376-66a9-4e33-b491-d2fb31adf0c7","is_oa":true,"landing_page_url":"http://resolver.tudelft.nl/uuid:10f51376-66a9-4e33-b491-d2fb31adf0c7","pdf_url":null,"source":{"id":"https://openalex.org/S4306400906","display_name":"Research Repository (Delft University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I98358874","host_organization_name":"Delft University of Technology","host_organization_lineage":["https://openalex.org/I98358874"],"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":"","raw_type":"conference paper"}],"best_oa_location":{"id":"doi:10.1145/3437963.3441769","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3437963.3441769","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3437963.3441769","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 14th ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3115572006.pdf","grobid_xml":"https://content.openalex.org/works/W3115572006.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W1720514416","https://openalex.org/W1832693441","https://openalex.org/W2001259128","https://openalex.org/W2027731328","https://openalex.org/W2046974451","https://openalex.org/W2054141820","https://openalex.org/W2094286023","https://openalex.org/W2157881433","https://openalex.org/W2171960770","https://openalex.org/W2295739661","https://openalex.org/W2575006718","https://openalex.org/W2742272831","https://openalex.org/W2788376297","https://openalex.org/W2798331900","https://openalex.org/W2808668898","https://openalex.org/W2897955056","https://openalex.org/W2900806287","https://openalex.org/W2950416834","https://openalex.org/W3026230850","https://openalex.org/W3035539675","https://openalex.org/W4288280764","https://openalex.org/W4288616732"],"related_works":[],"abstract_inverted_index":{"In":[0,16],"a":[1,29,40,51],"collaborative-filtering":[2],"recommendation":[3,155,176],"scenario,":[4],"biases":[5],"in":[6,12,127,195],"the":[7,13,22,26,85,90,96,100,112,128,135,138,168,175,184,205],"data":[8],"will":[9],"likely":[10],"propagate":[11],"learned":[14,129],"recommendations.":[15],"this":[17,59],"paper":[18],"we":[19],"focus":[20],"on":[21],"so-called":[23],"mainstream":[24,41,148,179],"bias:":[25],"tendency":[27],"of":[28,64,98,116,137,186],"recommender":[30],"system":[31],"to":[32,36,45,57,95,107,143,151,197,203],"provide":[33,152],"better":[34,198],"recommendations":[35,169],"users":[37,86,118,172,200],"who":[38],"have":[39],"taste,":[42],"as":[43,93,134,192],"opposed":[44],"non-mainstream":[46,171],"users.":[47,159,180],"We":[48],"propose":[49],"NAECF,":[50],"conceptually":[52],"simple":[53],"but":[54],"effective":[55],"idea":[56,62],"address":[58],"bias.":[60],"The":[61,81],"consists":[63],"adding":[65],"an":[66],"autoencoder":[67],"(AE)":[68],"layer":[69],"when":[70,104],"learning":[71,105],"user":[72],"and":[73,87,119,125,150,201],"item":[74],"representations":[75],"with":[76],"text-based":[77],"Convolutional":[78],"Neural":[79],"Networks.":[80],"AEs,":[82,140],"one":[83,88],"for":[84,89,170,178],"items,":[91],"serve":[92],"adversaries":[94],"process":[97],"minimizing":[99],"rating":[101],"prediction":[102],"error":[103],"how":[106],"recommend.":[108],"They":[109],"enforce":[110],"that":[111],"specific":[113],"unique":[114],"properties":[115],"all":[117,158],"items":[120,202],"are":[121,141],"sufficiently":[122],"well":[123],"incorporated":[124],"preserved":[126],"representations.":[130],"These":[131],"representations,":[132],"extracted":[133],"bottlenecks":[136],"corresponding":[139],"expected":[142],"be":[144],"less":[145],"biased":[146],"towards":[147],"users,":[149],"more":[153],"balanced":[154],"utility":[156],"across":[157],"Our":[160,181],"experimental":[161],"results":[162,182],"confirm":[163],"these":[164],"expectations,":[165],"significantly":[166],"improving":[167],"while":[173],"maintaining":[174],"quality":[177],"emphasize":[183],"importance":[185],"deploying":[187],"extensive":[188],"content-based":[189],"features,":[190],"such":[191],"online":[193],"reviews,":[194],"order":[196],"represent":[199],"maximize":[204],"de-biasing":[206],"effect.":[207]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":5}],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2021-01-05T00:00:00"}
