{"id":"https://openalex.org/W3189701585","doi":"https://doi.org/10.1145/3459637.3482345","title":"FedMatch","display_name":"FedMatch","publication_year":2021,"publication_date":"2021-10-26","ids":{"openalex":"https://openalex.org/W3189701585","doi":"https://doi.org/10.1145/3459637.3482345","mag":"3189701585"},"language":"en","primary_location":{"id":"doi:10.1145/3459637.3482345","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482345","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2108.05069","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Jiangui Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangui Chen","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ruqing Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruqing Zhang","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jiafeng Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiafeng Guo","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yixing Fan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yixing Fan","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":null,"display_name":"Xueqi Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueqi Cheng","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences & University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.4516,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.90713954,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"181","last_page":"190"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9973999857902527,"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"}},"topics":[{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9973999857902527,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9961000084877014,"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":0.9937000274658203,"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/benchmark","display_name":"Benchmark (surveying)","score":0.5648000240325928},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5286999940872192},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4359000027179718},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.4156000018119812},{"id":"https://openalex.org/keywords/dilemma","display_name":"Dilemma","score":0.39890000224113464},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3935000002384186},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.3305000066757202},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.32580000162124634}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8245000243186951},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5648000240325928},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5286999940872192},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4738999903202057},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4359000027179718},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.4156000018119812},{"id":"https://openalex.org/C2778496695","wikidata":"https://www.wikidata.org/wiki/Q254128","display_name":"Dilemma","level":2,"score":0.39890000224113464},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3935000002384186},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3495999872684479},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.33500000834465027},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.3305000066757202},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.32580000162124634},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.31630000472068787},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31119999289512634},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.310699999332428},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.30709999799728394},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.30709999799728394},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.3028999865055084},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.2994999885559082},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.2890999913215637},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.27000001072883606},{"id":"https://openalex.org/C31084985","wikidata":"https://www.wikidata.org/wiki/Q372650","display_name":"Common knowledge (logic)","level":5,"score":0.26260000467300415},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.2614000141620636}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3459637.3482345","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482345","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2108.05069","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2108.05069","pdf_url":"https://arxiv.org/pdf/2108.05069","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":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2108.05069","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2108.05069","pdf_url":"https://arxiv.org/pdf/2108.05069","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":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2117130368","https://openalex.org/W2186845332","https://openalex.org/W2461023463","https://openalex.org/W2538374209","https://openalex.org/W2760753016","https://openalex.org/W2798658104","https://openalex.org/W2803820154","https://openalex.org/W2809057686","https://openalex.org/W2963456518","https://openalex.org/W2964154091","https://openalex.org/W2970728484","https://openalex.org/W2980708516","https://openalex.org/W2988869004","https://openalex.org/W2997090102","https://openalex.org/W3080411117","https://openalex.org/W3102031770"],"related_works":[],"abstract_inverted_index":{"Question":[0],"Answering":[1],"(QA),":[2],"a":[3,13,52,57,111,120,196,206,227,246],"popular":[4],"and":[5,43,166,170,229],"promising":[6],"technique":[7,124],"for":[8,55,137,201,237],"intelligent":[9],"information":[10,236],"access,":[11],"faces":[12],"dilemma":[14,109],"about":[15],"data":[16,96,161],"as":[17,115],"most":[18],"other":[19,63],"AI":[20],"techniques.":[21],"On":[22,61],"one":[23],"hand,":[24,64],"modern":[25],"QA":[26,48,59,66,138,149,160,252],"methods":[27,178],"rely":[28],"on":[29,143,250],"deep":[30],"learning":[31,123,136,177],"models":[32,185],"which":[33,118],"are":[34,68,162],"typically":[35,69,163],"data-hungry.":[36],"Therefore,":[37],"it":[38,89],"is":[39,90,102,110,119,212,226],"expected":[40],"to":[41,78,82,93,107,133,155,213,232,257],"collect":[42],"fuse":[44],"all":[45,219,278],"the":[46,62,72,83,95,100,140,144,148,152,156,181,187,215,220,223,234,242,259,275,279],"available":[47],"datasets":[49,67,253],"together":[50],"in":[51,71,173,262],"common":[53,216],"site":[54],"developing":[56],"powerful":[58],"model.":[60],"real-world":[65],"distributed":[70,126],"form":[73],"of":[74,86,147,183,218],"isolated":[75],"islands":[76],"belonging":[77],"different":[79,255],"parties.":[80],"Due":[81],"increasing":[84],"awareness":[85],"privacy":[87],"security,":[88],"almost":[91],"impossible":[92],"integrate":[94],"scattered":[97],"around,":[98],"or":[99],"cost":[101],"prohibited.":[103],"A":[104],"possible":[105],"solution":[106],"this":[108,129,192],"new":[112],"approach":[113],"known":[114],"federated":[116,135,176],"learning,":[117],"privacy-preserving":[121],"machine":[122],"over":[125,277],"datasets.":[127,280],"In":[128],"work,":[130],"we":[131,194,244],"propose":[132,195],"adopt":[134],"with":[139,164,205],"special":[141],"concern":[142],"statistical":[145],"heterogeneity":[146,153],"data.":[150],"Here":[151],"refers":[154],"fact":[157],"that":[158,267],"annotated":[159],"non-identical":[165],"independent":[167],"distribution":[168],"(non-IID)":[169],"unbalanced":[171],"sizes":[172],"practice.":[174,263],"Traditional":[175],"may":[179],"sacrifice":[180],"accuracy":[182],"individual":[184],"under":[186],"heterogeneous":[188,260],"situation.":[189],"To":[190,240],"tackle":[191],"problem,":[193],"novel":[197],"Federated":[198],"Matching":[199],"framework":[200],"QA,":[202],"named":[203],"FedMatch,":[204],"backbone-patch":[207],"architecture.":[208],"The":[209],"shared":[210],"backbone":[211],"distill":[214],"knowledge":[217],"participants":[221],"while":[222],"private":[224],"patch":[225],"compact":[228],"efficient":[230],"module":[231],"retain":[233],"domain":[235],"each":[238],"participant.":[239],"facilitate":[241],"evaluation,":[243],"build":[245],"benchmark":[247],"collection":[248],"based":[249],"several":[251],"from":[254],"domains":[256],"simulate":[258],"situation":[261],"Empirical":[264],"studies":[265],"demonstrate":[266],"our":[268],"model":[269],"can":[270],"achieve":[271],"significant":[272],"improvements":[273],"against":[274],"baselines":[276]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2021-08-16T00:00:00"}