{"id":"https://openalex.org/W4414270315","doi":"https://doi.org/10.1109/tsipn.2025.3611172","title":"A Hybrid Supervised and Self-Supervised Graph Neural Network for Edge-Centric Applications","display_name":"A Hybrid Supervised and Self-Supervised Graph Neural Network for Edge-Centric Applications","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414270315","doi":"https://doi.org/10.1109/tsipn.2025.3611172"},"language":"en","primary_location":{"id":"doi:10.1109/tsipn.2025.3611172","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsipn.2025.3611172","pdf_url":null,"source":{"id":"https://openalex.org/S4306422866","display_name":"IEEE Transactions on Signal and Information Processing over Networks","issn_l":"2373-776X","issn":["2373-776X","2373-7778"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Signal and Information Processing over Networks","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/A5038064678","display_name":"Eugenio Borzone","orcid":null},"institutions":[{"id":"https://openalex.org/I4210150023","display_name":"Computational Intelligence and Information Systems Lab","ror":"https://ror.org/04fqqys39","country_code":"AR","type":"facility","lineage":["https://openalex.org/I4210150023"]}],"countries":["AR"],"is_corresponding":false,"raw_author_name":"Eugenio Borzone","raw_affiliation_strings":["Research institute for signals, systems and computational intelligence (sinc(i)), Santa Fe, Argentina","Research institute for signals, systems and computational intelligence (sinc(i)), Argentina"],"raw_orcid":"https://orcid.org/0009-0007-3345-6417","affiliations":[{"raw_affiliation_string":"Research institute for signals, systems and computational intelligence (sinc(i)), Santa Fe, Argentina","institution_ids":["https://openalex.org/I4210150023"]},{"raw_affiliation_string":"Research institute for signals, systems and computational intelligence (sinc(i)), Argentina","institution_ids":["https://openalex.org/I4210150023"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030230762","display_name":"Leandro E. Di Persia","orcid":"https://orcid.org/0000-0002-0331-6989"},"institutions":[{"id":"https://openalex.org/I4210150023","display_name":"Computational Intelligence and Information Systems Lab","ror":"https://ror.org/04fqqys39","country_code":"AR","type":"facility","lineage":["https://openalex.org/I4210150023"]}],"countries":["AR"],"is_corresponding":false,"raw_author_name":"Leandro Di Persia","raw_affiliation_strings":["Research institute for signals, systems and computational intelligence (sinc(i)), Santa Fe, Argentina","Research institute for signals, systems and computational intelligence (sinc(i)), Argentina"],"raw_orcid":"https://orcid.org/0000-0002-0331-6989","affiliations":[{"raw_affiliation_string":"Research institute for signals, systems and computational intelligence (sinc(i)), Santa Fe, Argentina","institution_ids":["https://openalex.org/I4210150023"]},{"raw_affiliation_string":"Research institute for signals, systems and computational intelligence (sinc(i)), Argentina","institution_ids":["https://openalex.org/I4210150023"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048439836","display_name":"M. G\u00e9rard","orcid":"https://orcid.org/0000-0001-5145-5943"},"institutions":[{"id":"https://openalex.org/I4210150023","display_name":"Computational Intelligence and Information Systems Lab","ror":"https://ror.org/04fqqys39","country_code":"AR","type":"facility","lineage":["https://openalex.org/I4210150023"]}],"countries":["AR"],"is_corresponding":false,"raw_author_name":"Matias Gerard","raw_affiliation_strings":["Research institute for signals, systems and computational intelligence (sinc(i)), Santa Fe, Argentina","Research institute for signals, systems and computational intelligence (sinc(i)), Argentina"],"raw_orcid":"https://orcid.org/0000-0001-5145-5943","affiliations":[{"raw_affiliation_string":"Research institute for signals, systems and computational intelligence (sinc(i)), Santa Fe, Argentina","institution_ids":["https://openalex.org/I4210150023"]},{"raw_affiliation_string":"Research institute for signals, systems and computational intelligence (sinc(i)), Argentina","institution_ids":["https://openalex.org/I4210150023"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210150023"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12471873,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":null,"first_page":"1268","last_page":"1277"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.7585999965667725,"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/T10320","display_name":"Neural Networks and Applications","score":0.7585999965667725,"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/node","display_name":"Node (physics)","score":0.5788999795913696},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5665000081062317},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5295000076293945},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.48080000281333923},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4729999899864197},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4187000095844269},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.38690000772476196},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.3666999936103821},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3450999855995178}],"concepts":[{"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/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.625},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5788999795913696},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5665000081062317},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5295000076293945},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.48080000281333923},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4729999899864197},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4187000095844269},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.38690000772476196},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3774000108242035},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.3666999936103821},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3450999855995178},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.33899998664855957},{"id":"https://openalex.org/C47702885","wikidata":"https://www.wikidata.org/wiki/Q5441227","display_name":"Feedforward neural network","level":3,"score":0.33640000224113464},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.33180001378059387},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3133000135421753},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.3019999861717224},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.29829999804496765},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2928999960422516},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.28850001096725464},{"id":"https://openalex.org/C104122410","wikidata":"https://www.wikidata.org/wiki/Q1416406","display_name":"Network model","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.26339998841285706},{"id":"https://openalex.org/C38858127","wikidata":"https://www.wikidata.org/wiki/Q5441228","display_name":"Feed forward","level":2,"score":0.2581000030040741},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.2515999972820282},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsipn.2025.3611172","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsipn.2025.3611172","pdf_url":null,"source":{"id":"https://openalex.org/S4306422866","display_name":"IEEE Transactions on Signal and Information Processing over Networks","issn_l":"2373-776X","issn":["2373-776X","2373-7778"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Signal and Information Processing over Networks","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1550211845","https://openalex.org/W1888005072","https://openalex.org/W1982267716","https://openalex.org/W2021105899","https://openalex.org/W2036450478","https://openalex.org/W2055043387","https://openalex.org/W2101491865","https://openalex.org/W2103351706","https://openalex.org/W2117486996","https://openalex.org/W2127322768","https://openalex.org/W2150926065","https://openalex.org/W2151697120","https://openalex.org/W2154851992","https://openalex.org/W2200017991","https://openalex.org/W2512971201","https://openalex.org/W2558748708","https://openalex.org/W2887057068","https://openalex.org/W2907492528","https://openalex.org/W2957436444","https://openalex.org/W2962756421","https://openalex.org/W2964321699","https://openalex.org/W2989608901","https://openalex.org/W2997546679","https://openalex.org/W3034077950","https://openalex.org/W3045012301","https://openalex.org/W3152893301","https://openalex.org/W4224078189","https://openalex.org/W4229012946","https://openalex.org/W4236358448","https://openalex.org/W4312320925","https://openalex.org/W4385245566"],"related_works":[],"abstract_inverted_index":{"This":[0,36],"paper":[1],"presents":[2],"a":[3,86,103,148],"novel":[4],"graph-based":[5],"deep":[6],"learning":[7],"model":[8,37,106,120,137],"for":[9,46,126,144,150],"tasks":[10],"involving":[11],"relations":[12],"between":[13,27,158],"two":[14,78],"nodes":[15,30],"(edge-centric":[16],"tasks),":[17],"where":[18],"the":[19,47,50,108,113,151],"focus":[20],"lies":[21],"on":[22],"predicting":[23,156],"relationships":[24],"and":[25,40,53,56,70,83,130],"interactions":[26,128],"pairs":[28],"of":[29,155],"rather":[31],"than":[32],"node":[33,69,93,109,145],"properties":[34],"themselves.":[35],"combines":[38],"supervised":[39],"self-supervised":[41],"learning,":[42],"taking":[43],"into":[44,95],"account":[45],"loss":[48],"function":[49],"embeddings":[51,110],"learned":[52],"patterns":[54],"with":[55,141,160],"without":[57],"ground":[58],"truth.":[59],"Additionally":[60],"it":[61],"incorporates":[62],"an":[63],"attention":[64],"mechanism":[65],"that":[66,118],"leverages":[67],"both":[68],"edge":[71,100],"features.":[72],"The":[73,136],"architecture,":[74],"trained":[75],"end-to-end,":[76],"comprises":[77],"primary":[79],"components:":[80],"embedding":[81],"generation":[82],"prediction.":[84,135],"First,":[85],"graph":[87],"neural":[88,105],"network":[89],"(GNN)":[90],"transform":[91],"raw":[92],"features":[94],"dense,":[96],"low-dimensional":[97],"embeddings,":[98],"incorporating":[99],"attributes.":[101],"Then,":[102],"feedforward":[104],"processes":[107],"to":[111],"produce":[112],"final":[114],"output.":[115],"Experiments":[116],"demonstrate":[117],"our":[119],"matches":[121],"or":[122],"exceeds":[123],"existing":[124],"methods":[125],"protein-protein":[127],"prediction":[129],"Gene":[131],"Ontology":[132],"(GO)":[133],"terms":[134],"also":[138],"performs":[139],"effectively":[140],"one-hot":[142],"encoding":[143],"features,":[146],"providing":[147],"solution":[149],"previously":[152],"unsolved":[153],"problem":[154],"similarity":[157],"compounds":[159],"unknown":[161],"structures.":[162]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
