{"id":"https://openalex.org/W4406458635","doi":"https://doi.org/10.1109/bigdata62323.2024.10825886","title":"Federated Learning on Knowledge Graph Embeddings via Contrastive Alignment","display_name":"Federated Learning on Knowledge Graph Embeddings via Contrastive Alignment","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406458635","doi":"https://doi.org/10.1109/bigdata62323.2024.10825886"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825886","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","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/A5075278301","display_name":"Asif Mahmud","orcid":"https://orcid.org/0000-0002-6403-6630"},"institutions":[{"id":"https://openalex.org/I186803428","display_name":"Brock University","ror":"https://ror.org/056am2717","country_code":"CA","type":"education","lineage":["https://openalex.org/I186803428"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Antor Mahmud","raw_affiliation_strings":["Brock University,Computer Science,St Catharines,Canada"],"affiliations":[{"raw_affiliation_string":"Brock University,Computer Science,St Catharines,Canada","institution_ids":["https://openalex.org/I186803428"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078237873","display_name":"Renata Dividino","orcid":null},"institutions":[{"id":"https://openalex.org/I186803428","display_name":"Brock University","ror":"https://ror.org/056am2717","country_code":"CA","type":"education","lineage":["https://openalex.org/I186803428"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Renata Dividino","raw_affiliation_strings":["Brock University,Computer Science,St Catharines,Canada"],"affiliations":[{"raw_affiliation_string":"Brock University,Computer Science,St Catharines,Canada","institution_ids":["https://openalex.org/I186803428"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5075278301"],"corresponding_institution_ids":["https://openalex.org/I186803428"],"apc_list":null,"apc_paid":null,"fwci":0.3637,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.70831208,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"3466","last_page":"3474"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9997000098228455,"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":0.9997000098228455,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9997000098228455,"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":0.9757000207901001,"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":0.7761522531509399},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.6687450408935547},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49869513511657715},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.459220826625824},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.43816015124320984},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.33691778779029846}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7761522531509399},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.6687450408935547},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49869513511657715},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.459220826625824},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.43816015124320984},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33691778779029846}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825886","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","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":37,"referenced_works":["https://openalex.org/W68132019","https://openalex.org/W1583837637","https://openalex.org/W1975517671","https://openalex.org/W2184957013","https://openalex.org/W2604314403","https://openalex.org/W2728059831","https://openalex.org/W2915480215","https://openalex.org/W2963819344","https://openalex.org/W2995022099","https://openalex.org/W3010336026","https://openalex.org/W3033161486","https://openalex.org/W3035524453","https://openalex.org/W3193800853","https://openalex.org/W3210948155","https://openalex.org/W4207076851","https://openalex.org/W4252707176","https://openalex.org/W4285606599","https://openalex.org/W4287332481","https://openalex.org/W4292830177","https://openalex.org/W4295308640","https://openalex.org/W4297808394","https://openalex.org/W4366307881","https://openalex.org/W4367046960","https://openalex.org/W4385574365","https://openalex.org/W4389983478","https://openalex.org/W4391528856","https://openalex.org/W6608344535","https://openalex.org/W6631964550","https://openalex.org/W6678830454","https://openalex.org/W6678846912","https://openalex.org/W6718112784","https://openalex.org/W6728757088","https://openalex.org/W6765541894","https://openalex.org/W6772406930","https://openalex.org/W6774314701","https://openalex.org/W6844194202","https://openalex.org/W6859867309"],"related_works":["https://openalex.org/W3188962172","https://openalex.org/W2772917594","https://openalex.org/W4312825515","https://openalex.org/W4306742369","https://openalex.org/W4303457083","https://openalex.org/W2131146434","https://openalex.org/W2951359407","https://openalex.org/W4376623224","https://openalex.org/W4387849428","https://openalex.org/W3204019825"],"abstract_inverted_index":{"In":[0],"conventional":[1],"federated":[2,106],"learning":[3,102],"(FL)":[4],"frameworks":[5],"for":[6,105],"knowledge":[7],"graph":[8],"embedding":[9],"(KGE),":[10],"individual":[11],"clients":[12,120],"independently":[13],"train":[14],"their":[15],"local":[16],"KGE":[17,99],"models.":[18],"A":[19],"trusted":[20],"server":[21,49],"then":[22],"collects":[23],"and":[24,84],"aggregates":[25],"the":[26,48,69,116],"locally":[27],"computed":[28],"embeddings":[29,79,114],"(e.g.,":[30],"by":[31],"averaging)":[32],"to":[33,55,82,112],"generate":[34],"a":[35,97],"consolidated,":[36],"shared":[37],"model.":[38],"This":[39],"process":[40],"maintains":[41],"data":[42,59,64],"privacy":[43],"throughout":[44],"FL":[45,72],"training,":[46],"as":[47],"does":[50],"not":[51],"require":[52],"direct":[53],"access":[54],"client":[56],"data.":[57],"However,":[58],"heterogeneity":[60],"(i.e.,":[61],"non-identically":[62],"distributed":[63],"across":[65,119],"clients)":[66],"significantly":[67],"challenges":[68],"performance":[70],"of":[71,86,115,153],"global":[73],"averaging-based":[74],"aggregation":[75,147],"algorithms,":[76,148],"where":[77],"averaging":[78],"can":[80],"lead":[81],"oversmoothing":[83],"loss":[85],"relational":[87],"patterns":[88],"among":[89],"entities.":[90],"To":[91],"address":[92],"these":[93],"challenges,":[94],"we":[95],"introduce":[96],"supervised,":[98],"model-agnostic":[100],"contrastive":[101],"(CL)":[103],"approach":[104,109],"settings.":[107],"Our":[108],"uses":[110],"CL":[111],"align":[113],"same":[117],"entity":[118],"while":[121],"maintaining":[122],"distinctions":[123],"between":[124],"different":[125],"entities,":[126],"thus":[127],"preserving":[128],"both":[129],"intra-and":[130],"inter-entity":[131],"relationships":[132],"during":[133],"aggregation.":[134],"Experiments":[135],"on":[136],"benchmark":[137],"datasets":[138],"demonstrate":[139],"that":[140],"our":[141],"proposed":[142],"model":[143],"outperforms":[144],"state-of-the-art":[145],"FL-KGE":[146],"particularly":[149],"with":[150],"large":[151],"numbers":[152],"clients.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
