{"id":"https://openalex.org/W7117715385","doi":"https://doi.org/10.1109/tmc.2025.3649484","title":"A Federated Recommendation System Framework Based on Variational Autoencoder With Mixture of Experts","display_name":"A Federated Recommendation System Framework Based on Variational Autoencoder With Mixture of Experts","publication_year":2025,"publication_date":"2025-12-31","ids":{"openalex":"https://openalex.org/W7117715385","doi":"https://doi.org/10.1109/tmc.2025.3649484"},"language":null,"primary_location":{"id":"doi:10.1109/tmc.2025.3649484","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmc.2025.3649484","pdf_url":null,"source":{"id":"https://openalex.org/S69141925","display_name":"IEEE Transactions on Mobile Computing","issn_l":"1536-1233","issn":["1536-1233","1558-0660","2161-9875"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Mobile Computing","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/A5120948950","display_name":"Yunpeng Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunpeng Xiao","raw_affiliation_strings":["School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-2846-3571","affiliations":[{"raw_affiliation_string":"School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yun Lu","orcid":"https://orcid.org/0009-0002-4800-0141"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Lu","raw_affiliation_strings":["School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0009-0002-4800-0141","affiliations":[{"raw_affiliation_string":"School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101921140","display_name":"Fei Tang","orcid":"https://orcid.org/0000-0002-0048-9876"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Tang","raw_affiliation_strings":["School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-0048-9876","affiliations":[{"raw_affiliation_string":"School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078016618","display_name":"Rong Xue Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rong Wang","raw_affiliation_strings":["School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-7963-1766","affiliations":[{"raw_affiliation_string":"School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031220156","display_name":"Guoyin Wang","orcid":"https://orcid.org/0000-0002-8521-5232"},"institutions":[{"id":"https://openalex.org/I126924076","display_name":"Chongqing Normal University","ror":"https://ror.org/01dcw5w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I126924076"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoyin Wang","raw_affiliation_strings":["Chongqing Key Laboratory of Brain-Inspired Cognitive Computing and Educational Rehabilitation for Children with Special Needs, Chongqing Normal University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-8521-5232","affiliations":[{"raw_affiliation_string":"Chongqing Key Laboratory of Brain-Inspired Cognitive Computing and Educational Rehabilitation for Children with Special Needs, Chongqing Normal University, Chongqing, China","institution_ids":["https://openalex.org/I126924076"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.71992426,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"25","issue":"6","first_page":"8597","last_page":"8610"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.7583000063896179,"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":0.7583000063896179,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.029200000688433647,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.0284000001847744,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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":0.7965999841690063},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7766000032424927},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6740000247955322},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.5210000276565552},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.4341999888420105},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.4309999942779541}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9041000008583069},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.7965999841690063},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7766000032424927},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6740000247955322},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.5210000276565552},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4408000111579895},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43950000405311584},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.4341999888420105},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.4309999942779541},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42149999737739563},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.3788999915122986},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.33239999413490295},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.3240000009536743},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.30820000171661377},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.3052000105381012},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.2827000021934509}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmc.2025.3649484","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmc.2025.3649484","pdf_url":null,"source":{"id":"https://openalex.org/S69141925","display_name":"IEEE Transactions on Mobile Computing","issn_l":"1536-1233","issn":["1536-1233","1558-0660","2161-9875"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Mobile Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8746658283","display_name":null,"funder_award_id":"CSTB2025NSCQ-LZX0148","funder_id":"https://openalex.org/F4320323172","funder_display_name":"Natural Science Foundation of Chongqing"}],"funders":[{"id":"https://openalex.org/F4320323172","display_name":"Natural Science Foundation of Chongqing","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W3174653434","https://openalex.org/W3200418702","https://openalex.org/W3201529712","https://openalex.org/W3205970722","https://openalex.org/W3217045679","https://openalex.org/W4221030341","https://openalex.org/W4224322662","https://openalex.org/W4226479888","https://openalex.org/W4281258536","https://openalex.org/W4285241255","https://openalex.org/W4293452925","https://openalex.org/W4309795480","https://openalex.org/W4312517097","https://openalex.org/W4313525830","https://openalex.org/W4318757201","https://openalex.org/W4323338428","https://openalex.org/W4367047287","https://openalex.org/W4378419441","https://openalex.org/W4380685566","https://openalex.org/W4383753813","https://openalex.org/W4385187849","https://openalex.org/W4386730046","https://openalex.org/W4386869584","https://openalex.org/W4387010736","https://openalex.org/W4387846171","https://openalex.org/W4388631551","https://openalex.org/W4389366386","https://openalex.org/W4389544915","https://openalex.org/W4391149309","https://openalex.org/W4392024995","https://openalex.org/W4392796562","https://openalex.org/W4393372151","https://openalex.org/W4394717692","https://openalex.org/W4394994587","https://openalex.org/W4396927180","https://openalex.org/W4399666057","https://openalex.org/W4400261185","https://openalex.org/W4400644893","https://openalex.org/W4401544324","https://openalex.org/W4403582576","https://openalex.org/W4408998396","https://openalex.org/W4409364585","https://openalex.org/W4410088775","https://openalex.org/W4410358938","https://openalex.org/W4412394835","https://openalex.org/W4414463166","https://openalex.org/W7133216270"],"related_works":[],"abstract_inverted_index":{"Recommender":[0],"systems":[1],"enhance":[2,138],"user":[3,26,61],"experience":[4],"by":[5],"delivering":[6],"personalized":[7],"suggestions":[8],"derived":[9],"from":[10],"users'":[11],"historical":[12],"behavior.":[13],"However,":[14],"conventional":[15,93],"approaches":[16],"face":[17],"challenges":[18],"in":[19,111,160,163,166,172,181,188],"processing":[20],"large-scale":[21],"data":[22,124],"while":[23],"simultaneously":[24],"preserving":[25],"privacy":[27,187],"and":[28,90,104,126,140,168,186],"maintaining":[29],"stable":[30,106],"training.":[31],"To":[32],"address":[33],"these":[34],"issues,":[35],"we":[36],"propose":[37],"Fed-MWAE,":[38],"a":[39,52,112,169],"novel":[40],"federated":[41,113,189],"variational":[42],"autoencoder":[43],"(VAE)":[44],"framework":[45,50],"for":[46],"recommendation":[47],"tasks.":[48],"The":[49],"incorporates":[51],"sparsely":[53],"activated":[54],"Mixture-of-Experts":[55],"(MoE)":[56],"module":[57],"to":[58,85,122,137],"model":[59],"diverse":[60],"behavior":[62],"patterns":[63],"across":[64],"expert":[65,72],"subnetworks.":[66],"A":[67],"top-$k$gating":[68],"mechanism":[69],"selectively":[70],"aggregates":[71],"outputs,":[73],"thereby":[74],"improving":[75],"computational":[76],"efficiency":[77],"without":[78],"compromising":[79],"accuracy.":[80],"Furthermore,":[81],"Fed-MWAE":[82,151,180],"employs":[83],"VAEs":[84],"capture":[86],"complex":[87],"latent":[88],"structures":[89],"replaces":[91],"the":[92,98,127,132,177],"Kullback-Leibler":[94],"(KL)":[95],"divergence":[96],"with":[97],"Wasserstein":[99],"distance,":[100],"enabling":[101],"smoother":[102],"optimization":[103],"more":[105],"convergence.":[107],"Training":[108],"is":[109],"conducted":[110],"learning":[114],"setting,":[115],"where":[116],"local":[117],"clients":[118],"perform":[119],"on-device":[120],"updates":[121,128],"safeguard":[123],"privacy,":[125],"are":[129],"aggregated":[130],"using":[131],"Federated":[133],"Averaging":[134],"(FedAvg)":[135],"algorithm":[136],"scalability":[139],"communication":[141],"efficiency.":[142],"Extensive":[143],"experiments":[144],"on":[145],"four":[146],"public":[147],"datasets":[148],"demonstrate":[149],"that":[150],"consistently":[152],"outperforms":[153],"strong":[154],"baselines,":[155],"achieving":[156],"improvements":[157],"of":[158,179],"5.46%":[159],"NDCG,":[161],"0.66%":[162],"Recall@20,":[164],"4.85%":[165],"Recall@50,":[167],"2.99%":[170],"reduction":[171],"loss.":[173],"These":[174],"results":[175],"validate":[176],"effectiveness":[178],"balancing":[182],"accuracy,":[183],"efficiency,":[184],"stability,":[185],"recommender":[190],"systems.":[191]},"counts_by_year":[],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-12-31T00:00:00"}
