{"id":"https://openalex.org/W4407953592","doi":"https://doi.org/10.1145/3701551.3703493","title":"FedGF: Enhancing Structural Knowledge via Graph Factorization for Federated Graph Learning","display_name":"FedGF: Enhancing Structural Knowledge via Graph Factorization for Federated Graph Learning","publication_year":2025,"publication_date":"2025-02-26","ids":{"openalex":"https://openalex.org/W4407953592","doi":"https://doi.org/10.1145/3701551.3703493"},"language":"en","primary_location":{"id":"doi:10.1145/3701551.3703493","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3701551.3703493","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-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/A5030260615","display_name":"Pengyang Zhou","orcid":"https://orcid.org/0000-0002-7219-0937"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengyang Zhou","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-7219-0937","affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028791879","display_name":"Chaochao Chen","orcid":"https://orcid.org/0000-0003-1419-964X"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaochao Chen","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-1419-964X","affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007858277","display_name":"Weiming Liu","orcid":"https://orcid.org/0000-0002-4115-7667"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiming Liu","raw_affiliation_strings":["Zhejiang university, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-4115-7667","affiliations":[{"raw_affiliation_string":"Zhejiang university, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071445044","display_name":"Xinting Liao","orcid":"https://orcid.org/0000-0002-8257-2381"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinting Liao","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-8257-2381","affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076938046","display_name":"Feihong Yu","orcid":"https://orcid.org/0009-0005-0491-1869"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fengyuan Yu","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0005-0491-1869","affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103471639","display_name":"Z. F. Fu","orcid":"https://orcid.org/0009-0003-3512-9656"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhihui Fu","raw_affiliation_strings":["OPPO Research Institute, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0003-3512-9656","affiliations":[{"raw_affiliation_string":"OPPO Research Institute, Shenzhen, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033117282","display_name":"Xingyu Lou","orcid":"https://orcid.org/0009-0003-3180-0668"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xingyu Lou","raw_affiliation_strings":["OPPO, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0003-3180-0668","affiliations":[{"raw_affiliation_string":"OPPO, Shenzhen, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111877488","display_name":"Wu Wen","orcid":"https://orcid.org/0009-0008-1235-1816"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wu Wen","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0008-1235-1816","affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074603286","display_name":"Xiaolin Zheng","orcid":"https://orcid.org/0000-0001-5483-0366"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolin Zheng","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-5483-0366","affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100384677","display_name":"Jun Wang","orcid":"https://orcid.org/0000-0002-0481-5341"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jun Wang","raw_affiliation_strings":["OPPO Research Institute, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-0481-5341","affiliations":[{"raw_affiliation_string":"OPPO Research Institute, Shenzhen, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":10,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.5175,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.91865109,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"448","last_page":"456"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9994000196456909,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9994000196456909,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9940000176429749,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9908000230789185,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7651175260543823},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.619762122631073},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.613960325717926},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.41445302963256836},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.40368807315826416},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2711857557296753},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.09689447283744812}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7651175260543823},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.619762122631073},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.613960325717926},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.41445302963256836},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.40368807315826416},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2711857557296753},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.09689447283744812}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3701551.3703493","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3701551.3703493","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eighteenth 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/G185240960","display_name":null,"funder_award_id":"2022YFF0902704","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"}],"funders":[{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W2292080738","https://openalex.org/W2559655401","https://openalex.org/W2606882085","https://openalex.org/W2744999500","https://openalex.org/W2907492528","https://openalex.org/W2964881778","https://openalex.org/W3038022836","https://openalex.org/W3102834148","https://openalex.org/W3173716304","https://openalex.org/W3174135700","https://openalex.org/W3217045679","https://openalex.org/W4213437519","https://openalex.org/W4220902683","https://openalex.org/W4225982766","https://openalex.org/W4226092233","https://openalex.org/W4233762729","https://openalex.org/W4281686206","https://openalex.org/W4311080353","https://openalex.org/W4319990461","https://openalex.org/W4382318655","https://openalex.org/W4382463479","https://openalex.org/W4385764191","https://openalex.org/W4385764392","https://openalex.org/W4385767875","https://openalex.org/W4385768033","https://openalex.org/W4386150329","https://openalex.org/W4393148126","https://openalex.org/W4402727563","https://openalex.org/W6600120041","https://openalex.org/W6600168703","https://openalex.org/W6601817979","https://openalex.org/W6759238902","https://openalex.org/W6797220997"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Federated":[0,42],"graph":[1,5,52,83,120],"learning":[2],"involves":[3],"training":[4],"neural":[6],"networks":[7],"distributively":[8],"on":[9,132],"local":[10,34,64,98,114],"graphs":[11,77],"and":[12,27,68,85,113,122],"aggregating":[13],"model":[14],"parameters":[15],"in":[16],"a":[17,79],"central":[18],"server.":[19],"However,":[20],"existing":[21],"methods":[22],"fail":[23],"to":[24,88,116],"effectively":[25],"capture":[26,89],"leverage":[28],"the":[29,90,97,111,119,126,137],"inherent":[30],"global":[31,60,112],"structures,":[32],"hindering":[33],"structural":[35,48,128],"modeling.":[36,129],"To":[37],"address":[38],"this,":[39],"we":[40],"propose":[41],"Graph":[43],"Factorization":[44],"(FedGF),":[45],"which":[46],"enhances":[47],"knowledge":[49],"via":[50],"privacy-preserving":[51],"factorization.":[53],"Specifically,":[54],"FedGF":[55],"includes":[56],"three":[57],"modules,":[58],"i.e.,":[59],"structure":[61,65,70,115],"reconstruction":[62,87],"(GSR),":[63],"exploration":[66],"(LSE),":[67],"global-local":[69],"alignment":[71],"(GLSA).":[72],"Firstly,":[73],"GSR":[74],"factorizes":[75],"client":[76,106],"into":[78],"series":[80],"of":[81,139],"learnable":[82],"atoms":[84,121],"conducts":[86],"globally":[91],"shared":[92],"structure.":[93],"Then,":[94],"LSE":[95],"explores":[96],"structure,":[99],"mining":[100],"potential":[101],"but":[102],"unrevealed":[103],"connections":[104],"within":[105],"subgraphs.":[107],"GLSA":[108],"further":[109],"aligns":[110],"alternatively":[117],"refine":[118],"GNN":[123],"model,":[124],"enhancing":[125],"overall":[127],"Extensive":[130],"experiments":[131],"six":[133],"datasets":[134],"consistently":[135],"validate":[136],"effectiveness":[138],"\\modelname.":[140]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}