{"id":"https://openalex.org/W4306317799","doi":"https://doi.org/10.1145/3511808.3557140","title":"Multi-Faceted Hierarchical Multi-Task Learning for Recommender Systems","display_name":"Multi-Faceted Hierarchical Multi-Task Learning for Recommender Systems","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4306317799","doi":"https://doi.org/10.1145/3511808.3557140"},"language":"en","primary_location":{"id":"doi:10.1145/3511808.3557140","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557140","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","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 31st ACM International Conference on Information &amp; Knowledge Management","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/A5043185748","display_name":"Junning Liu","orcid":"https://orcid.org/0000-0003-0844-4071"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junning Liu","raw_affiliation_strings":["Tencent PCG, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent PCG, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100660610","display_name":"Xinjian Li","orcid":"https://orcid.org/0000-0003-4585-159X"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinjian Li","raw_affiliation_strings":["Tencent PCG, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent PCG, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017743551","display_name":"Bo An","orcid":"https://orcid.org/0000-0002-7064-7438"},"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":"Bo An","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015213215","display_name":"Zijie Xia","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zijie Xia","raw_affiliation_strings":["Tencent WXG, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent WXG, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100407962","display_name":"Xu Wang","orcid":"https://orcid.org/0000-0003-4950-6013"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Wang","raw_affiliation_strings":["Tencent WXG, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent WXG, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7587,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.87017923,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"3332","last_page":"3341"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T11478","display_name":"Caching and Content Delivery","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9754999876022339,"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/computer-science","display_name":"Computer science","score":0.7990719079971313},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.6801416873931885},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6710957288742065},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5342667698860168},{"id":"https://openalex.org/keywords/macro","display_name":"Macro","score":0.5265583992004395},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.49043557047843933},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.433333158493042},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4066024124622345}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7990719079971313},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.6801416873931885},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6710957288742065},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5342667698860168},{"id":"https://openalex.org/C166955791","wikidata":"https://www.wikidata.org/wiki/Q629579","display_name":"Macro","level":2,"score":0.5265583992004395},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.49043557047843933},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.433333158493042},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4066024124622345},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3511808.3557140","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557140","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","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 31st ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2040367556","https://openalex.org/W2117130368","https://openalex.org/W2150884987","https://openalex.org/W2157881433","https://openalex.org/W2219888463","https://openalex.org/W2401983063","https://openalex.org/W2475334473","https://openalex.org/W2510317721","https://openalex.org/W2512971201","https://openalex.org/W2586505867","https://openalex.org/W2809290718","https://openalex.org/W2893085659","https://openalex.org/W2903852246","https://openalex.org/W2914320989","https://openalex.org/W2963168538","https://openalex.org/W2963540523","https://openalex.org/W2963877604","https://openalex.org/W2972510393","https://openalex.org/W2973172293","https://openalex.org/W3087931390","https://openalex.org/W3093601757","https://openalex.org/W3099732023","https://openalex.org/W3117286046","https://openalex.org/W3141797743","https://openalex.org/W3155127799","https://openalex.org/W3156261048","https://openalex.org/W4236965008","https://openalex.org/W6601548533"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W4312814274","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312"],"abstract_inverted_index":{"There":[0],"have":[1],"been":[2,219],"many":[3,36],"studies":[4],"on":[5,19],"improving":[6],"the":[7,20,73,94,110,119,127,132,145,240],"efficiency":[8],"of":[9,28,48,75,115,135,147,163,169,171,203,233],"shared":[10,111,136,149],"learning":[11,112,137],"in":[12,31,60,98,157,184,205,212,221,243,262],"Multi-Task":[13],"Learning":[14],"(MTL).":[15],"Previous":[16],"works":[17],"focused":[18],"\"micro\"":[21],"sharing":[22,116],"perspective":[23,134],"for":[24,196],"a":[25,45,86,103,140,158,254],"small":[26],"number":[27,47,74],"tasks,":[29],"while":[30],"Recommender":[32],"Systems":[33],"(RS)":[34],"and":[35,67,117,138,154,167,187,210,228,248],"other":[37],"AI":[38],"applications,":[39],"we":[40,63,259],"often":[41,251],"need":[42],"to":[43,55,143,239],"model":[44,56,90],"large":[46,99,159],"tasks.":[49],"For":[50,126],"example,":[51],"when":[52],"using":[53],"MTL":[54,89,181],"various":[57],"user":[58,192,209],"behaviors":[59],"RS,":[61],"if":[62],"differentiate":[64],"new":[65,68,197,246,249],"users":[66,198,247],"items":[69,250],"from":[70,253],"old":[71],"ones,":[72],"tasks":[76],"will":[77],"increase":[78,202],"exponentially":[79],"with":[80,102,121,199],"multidimensional":[81,95],"relations.":[82],"This":[83],"work":[84],"proposes":[85],"Multi-Faceted":[87],"Hierarchical":[88],"(MFH)":[91],"that":[92,177,258],"exploits":[93],"task":[96,123],"relations":[97],"scale":[100],"MTLs":[101],"nested":[104],"hierarchical":[105],"tree":[106],"structure.":[107],"MFH":[108,130,153,178,216,235],"maximizes":[109],"through":[113],"multi-facets":[114],"improves":[118],"performance":[120],"heterogeneous":[122],"tower":[124],"design.":[125],"first":[128,260],"time,":[129],"addresses":[131],"\"macro\"":[133],"defines":[139],"\"switcher\"":[141],"structure":[142],"conceptualize":[144],"structures":[146],"macro":[148],"learning.":[150],"We":[151],"evaluate":[152],"SOTA":[155,180],"models":[156,182],"industry":[160],"video":[161],"platform":[162],"10":[164],"billion":[165],"samples":[166],"hundreds":[168],"millions":[170],"monthly":[172],"active":[173],"users.":[174],"Results":[175],"show":[176],"outperforms":[179],"significantly":[183],"both":[185],"offline":[186],"online":[188,201],"evaluations":[189],"across":[190],"all":[191],"groups,":[193],"especially":[194,237],"remarkable":[195],"an":[200],"9.1%":[204],"app":[206],"time":[207],"per":[208],"1.85%":[211],"next-day":[213],"retention":[214],"rate.":[215],"currently":[217],"has":[218],"deployed":[220],"WeSee,":[222],"Tencent":[223,229],"News,":[224],"QQ":[225],"Little":[226],"World":[227],"Video,":[230],"several":[231],"products":[232],"Tencent.":[234],"is":[236],"beneficial":[238],"cold-start":[241],"problems":[242],"RS":[244],"where":[245],"suffer":[252],"\"local":[255],"overfitting\"":[256],"phenomenon":[257],"formalize":[261],"this":[263],"paper.":[264]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
