{"id":"https://openalex.org/W4415539993","doi":"https://doi.org/10.1145/3746027.3755224","title":"Prototype-Guided Representation Projection for Multi-Domain Multi-Task Recommendation","display_name":"Prototype-Guided Representation Projection for Multi-Domain Multi-Task Recommendation","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415539993","doi":"https://doi.org/10.1145/3746027.3755224"},"language":null,"primary_location":{"id":"doi:10.1145/3746027.3755224","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746027.3755224","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 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3746027.3755224","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5061378094","display_name":"Binrui Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Binrui Wu","raw_affiliation_strings":["Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0009-9056-9543","affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109779415","display_name":"Haochen Sui","orcid":"https://orcid.org/0009-0000-0405-7301"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haochen Sui","raw_affiliation_strings":["University of Michigan, Ann Arbor, Michigan, USA"],"raw_orcid":"https://orcid.org/0009-0000-0405-7301","affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, Michigan, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059445819","display_name":"Jiaye Lin","orcid":"https://orcid.org/0009-0002-4485-6612"},"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":"Jiaye Lin","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0002-4485-6612","affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012051562","display_name":"Jiechao Gao","orcid":"https://orcid.org/0000-0003-0628-1416"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiechao Gao","raw_affiliation_strings":["Center for SDGC, Stanford University, Stanford, CA, USA"],"raw_orcid":"https://orcid.org/0000-0003-0628-1416","affiliations":[{"raw_affiliation_string":"Center for SDGC, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101103024","display_name":"Ting Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I33434090","display_name":"University of Massachusetts Boston","ror":"https://ror.org/04ydmy275","country_code":"US","type":"education","lineage":["https://openalex.org/I33434090"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ting Xu","raw_affiliation_strings":["University of Massachusetts Boston, Boston, MA, USA"],"raw_orcid":"https://orcid.org/0009-0004-5049-6849","affiliations":[{"raw_affiliation_string":"University of Massachusetts Boston, Boston, MA, USA","institution_ids":["https://openalex.org/I33434090"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083054865","display_name":"Keyan Jin","orcid":"https://orcid.org/0009-0004-9783-8818"},"institutions":[{"id":"https://openalex.org/I49835588","display_name":"Macao Polytechnic University","ror":"https://ror.org/02sf5td35","country_code":"MO","type":"education","lineage":["https://openalex.org/I49835588"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Keyan Jin","raw_affiliation_strings":["Macao Polytechnic University, Macao, Macao, China"],"raw_orcid":"https://orcid.org/0009-0004-9783-8818","affiliations":[{"raw_affiliation_string":"Macao Polytechnic University, Macao, Macao, China","institution_ids":["https://openalex.org/I49835588"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5107850233","display_name":"Xuesong Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210155967","display_name":"OriginWater (China)","ror":"https://ror.org/04h7gmn81","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210155967"]},{"id":"https://openalex.org/I4401726859","display_name":"Kuaishou (China)","ror":"https://ror.org/0258as409","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuesong Zhang","raw_affiliation_strings":["KuaiShou Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0008-8163-7228","affiliations":[{"raw_affiliation_string":"KuaiShou Technology, Beijing, China","institution_ids":["https://openalex.org/I4210155967","https://openalex.org/I4401726859"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5061378094"],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.43292582,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6075","last_page":"6083"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9944999814033508,"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"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9943000078201294,"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/representation","display_name":"Representation (politics)","score":0.7742000222206116},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.651199996471405},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5228999853134155},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.47870001196861267},{"id":"https://openalex.org/keywords/independence","display_name":"Independence (probability theory)","score":0.4771000146865845},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46219998598098755},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4050000011920929}],"concepts":[{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.7742000222206116},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7430999875068665},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.651199996471405},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5855000019073486},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5274999737739563},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5228999853134155},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.47870001196861267},{"id":"https://openalex.org/C35651441","wikidata":"https://www.wikidata.org/wiki/Q625303","display_name":"Independence (probability theory)","level":2,"score":0.4771000146865845},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46219998598098755},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40779998898506165},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4050000011920929},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4032999873161316},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.40290001034736633},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3610999882221222},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3610999882221222},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.34790000319480896},{"id":"https://openalex.org/C175694140","wikidata":"https://www.wikidata.org/wiki/Q980329","display_name":"Orthographic projection","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.2702000141143799},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26510000228881836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746027.3755224","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746027.3755224","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 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3746027.3755224","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746027.3755224","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 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1969719708","https://openalex.org/W2084701050","https://openalex.org/W2110518760","https://openalex.org/W2809290718","https://openalex.org/W2903852246","https://openalex.org/W2962745591","https://openalex.org/W3087931390","https://openalex.org/W3094431459","https://openalex.org/W3209943551","https://openalex.org/W4213365329","https://openalex.org/W4224318508","https://openalex.org/W4292419518","https://openalex.org/W4313023122","https://openalex.org/W4382318707","https://openalex.org/W4382765742","https://openalex.org/W4384774596","https://openalex.org/W4385270144","https://openalex.org/W4385565675","https://openalex.org/W4385568236","https://openalex.org/W4385774925","https://openalex.org/W4386721920","https://openalex.org/W4386729322","https://openalex.org/W4396820856","https://openalex.org/W4399695571"],"related_works":[],"abstract_inverted_index":{"Multi-domain":[0],"and":[1,7,41,119,176],"multi-task":[2],"learning":[3,69],"enhance":[4],"the":[5,29,36,77,125,136,149,154,158,164],"efficiency":[6],"performance":[8],"of":[9,31,39,66,90,138,161],"industrial":[10],"recommendation":[11,78],"systems":[12],"by":[13,130],"integrating":[14],"information":[15],"from":[16,28],"different":[17],"domains/tasks":[18],"to":[19,57,70,94,124,134,147],"model":[20,56],"user":[21],"interests":[22],"uniformly.":[23],"However,":[24],"existing":[25,196],"methods":[26],"suffer":[27],"problem":[30],"representation":[32,151],"entanglement,":[33],"which":[34,61],"limits":[35],"effective":[37],"handling":[38],"commonality":[40],"specificity":[42],"among":[43],"various":[44],"domains/tasks.":[45,109],"In":[46],"this":[47,59],"paper,":[48],"we":[49],"propose":[50],"a":[51,63,87,103],"Prototype-guided":[52],"Representation":[53],"Projection":[54],"(PRP)":[55],"address":[58],"issue,":[60],"explores":[62],"novel":[64],"direction":[65],"applying":[67],"prototype":[68,105,127,155],"deal":[71],"with":[72],"complex":[73],"domain/task":[74,111],"relationships":[75],"in":[76,180],"field.":[79],"To":[80],"identify":[81],"inter-domain/task":[82],"commonality,":[83],"PRP":[84,142],"initially":[85],"uses":[86],"shared":[88],"Mixture":[89],"Experts":[91],"(MoE)":[92],"architecture":[93],"learn":[95],"representations":[96,121],"for":[97,184],"each":[98],"sample,":[99],"projecting":[100],"them":[101],"into":[102],"common":[104],"space":[106],"across":[107],"all":[108],"For":[110],"specificity,":[112],"specific":[113],"feature":[114],"extraction":[115],"experts":[116],"are":[117,122],"employed,":[118],"sample":[120,166],"projected":[123],"corresponding":[126],"spaces,":[128,156],"constrained":[129],"an":[131,181],"orthogonal":[132],"loss":[133],"ensure":[135],"independence":[137],"those":[139],"spaces.":[140],"Moreover,":[141],"utilizes":[143],"Optimal":[144],"Transport":[145],"(OT)":[146],"guide":[148],"correct":[150],"projection":[152],"within":[153],"employing":[157],"linear":[159],"combination":[160],"prototypes":[162],"as":[163],"new":[165],"representation.":[167],"We":[168],"conduct":[169],"offline":[170],"experiments":[171],"on":[172],"two":[173],"open-source":[174],"datasets":[175],"deploy":[177],"our":[178,193],"approach":[179,194],"online":[182],"system":[183],"A/B":[185],"testing.":[186],"Extensive":[187],"experimental":[188],"results":[189],"consistently":[190],"demonstrate":[191],"that":[192],"outperforms":[195],"methods.":[197]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-25T00:00:00"}
