{"id":"https://openalex.org/W4213348292","doi":"https://doi.org/10.1145/3488560.3498427","title":"Fighting Mainstream Bias in Recommender Systems via Local Fine Tuning","display_name":"Fighting Mainstream Bias in Recommender Systems via Local Fine Tuning","publication_year":2022,"publication_date":"2022-02-11","ids":{"openalex":"https://openalex.org/W4213348292","doi":"https://doi.org/10.1145/3488560.3498427"},"language":"en","primary_location":{"id":"doi:10.1145/3488560.3498427","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3488560.3498427","pdf_url":null,"source":{"id":"https://openalex.org/S4363608885","display_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","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 Fifteenth ACM International Conference on Web Search and Data Mining","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/A5019994221","display_name":"Ziwei Zhu","orcid":"https://orcid.org/0000-0002-3990-4774"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ziwei Zhu","raw_affiliation_strings":["Texas A&amp;M University, College Station, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Texas A&amp;M University, College Station, TX, USA","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048489384","display_name":"James Caverlee","orcid":"https://orcid.org/0000-0001-8350-8528"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"James Caverlee","raw_affiliation_strings":["Texas A&amp;M University, College Station, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Texas A&amp;M University, College Station, TX, USA","institution_ids":["https://openalex.org/I91045830"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I91045830"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1497","last_page":"1506"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9926000237464905,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.982699990272522,"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/mainstream","display_name":"Mainstream","score":0.9724869132041931},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.77194744348526},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.6333513855934143},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6028623580932617},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.5697852969169617},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5545491576194763},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2571284770965576},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.2416333556175232},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.06086733937263489}],"concepts":[{"id":"https://openalex.org/C2777617010","wikidata":"https://www.wikidata.org/wiki/Q18957","display_name":"Mainstream","level":2,"score":0.9724869132041931},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.77194744348526},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.6333513855934143},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6028623580932617},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5697852969169617},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5545491576194763},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2571284770965576},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2416333556175232},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.06086733937263489},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3488560.3498427","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3488560.3498427","pdf_url":null,"source":{"id":"https://openalex.org/S4363608885","display_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","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 Fifteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5920510888","display_name":"FAI: Towards Fairness in Deep Neural Networks with Learning Interpretation","funder_award_id":"1939716","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2009205701","https://openalex.org/W2035055162","https://openalex.org/W2054141820","https://openalex.org/W2069065514","https://openalex.org/W2150886314","https://openalex.org/W2336195973","https://openalex.org/W2605350416","https://openalex.org/W2748058847","https://openalex.org/W2808751420","https://openalex.org/W2945827670","https://openalex.org/W2950173087","https://openalex.org/W2963085847","https://openalex.org/W2963189767","https://openalex.org/W2998534896","https://openalex.org/W3012748865","https://openalex.org/W3035446616","https://openalex.org/W3035523484","https://openalex.org/W3083159507","https://openalex.org/W3088231796","https://openalex.org/W3100278010","https://openalex.org/W3103891807","https://openalex.org/W3115418111","https://openalex.org/W3115572006","https://openalex.org/W3117355859","https://openalex.org/W3127259869","https://openalex.org/W3153182568","https://openalex.org/W3157014581","https://openalex.org/W3164446335","https://openalex.org/W4254182148"],"related_works":["https://openalex.org/W1484355083","https://openalex.org/W2772628444","https://openalex.org/W4220714703","https://openalex.org/W2735929803","https://openalex.org/W2170391450","https://openalex.org/W2098758514","https://openalex.org/W3008845055","https://openalex.org/W2041004656","https://openalex.org/W4376854386","https://openalex.org/W1966742602"],"abstract_inverted_index":{"In":[0,53],"collaborative":[1],"filtering,":[2],"the":[3,31,88,118,146,149,162,167,173],"quality":[4],"of":[5,30,50,148],"recommendations":[6,49],"critically":[7],"relies":[8],"on":[9,78],"how":[10],"easily":[11],"a":[12,19,23,38,84],"model":[13],"can":[14,165],"find":[15],"similar":[16],"users":[17,157,171],"for":[18,91,155,169],"target":[20],"user.":[21,93],"Hence,":[22],"niche":[24,71,156],"user":[25,40],"who":[26],"prefers":[27],"items":[28],"out":[29],"mainstream":[32,39,59,69,85,89,100,170],"may":[33],"receive":[34,48],"poor":[35],"recommendations,":[36],"while":[37],"sharing":[41],"interests":[42],"with":[43],"many":[44],"others":[45],"will":[46],"likely":[47],"higher":[51],"quality.":[52],"this":[54,58],"work,":[55],"we":[56,73,95,109,121],"study":[57],"bias":[60,101],"centering":[61],"around":[62],"three":[63],"key":[64],"thrusts.":[65],"First,":[66],"to":[67,82,116,152],"distinguish":[68],"and":[70,113,129,134,158],"users,":[72],"explore":[74,110],"four":[75],"approaches":[76],"based":[77],"outlier":[79],"detection":[80],"techniques":[81],"identify":[83],"score":[86],"indicating":[87],"level":[90],"each":[92],"Second,":[94],"empirically":[96],"show":[97,145,160],"that":[98,161],"severe":[99],"is":[102],"produced":[103],"by":[104],"conventional":[105],"recommendation":[106],"models.":[107],"Last,":[108],"both":[111],"global":[112,124],"local":[114,136],"methods":[115,151],"mitigate":[117],"bias.":[119],"Concretely,":[120],"propose":[122],"two":[123],"models:":[125],"Distribution":[126],"Calibration":[127],"(DC)":[128],"Weighted":[130],"Loss":[131],"(WL)":[132],"methods;":[133],"one":[135],"method:":[137],"Local":[138],"Fine":[139],"Tuning":[140],"(LFT)":[141],"method.":[142],"Extensive":[143],"experiments":[144],"effectiveness":[147],"proposed":[150,163],"improve":[153,166],"utility":[154,168],"also":[159],"LFT":[164],"at":[172],"same":[174],"time.":[175]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
