{"id":"https://openalex.org/W4388186810","doi":"https://doi.org/10.1145/3581783.3612196","title":"Propagation is All You Need: A New Framework for Representation Learning and Classifier Training on Graphs","display_name":"Propagation is All You Need: A New Framework for Representation Learning and Classifier Training on Graphs","publication_year":2023,"publication_date":"2023-10-26","ids":{"openalex":"https://openalex.org/W4388186810","doi":"https://doi.org/10.1145/3581783.3612196"},"language":"en","primary_location":{"id":"doi:10.1145/3581783.3612196","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3612196","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","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":null,"display_name":"Jiaming Zhuo","orcid":"https://orcid.org/0009-0008-1229-7987"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiaming Zhuo","raw_affiliation_strings":["Hebei University of Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0009-0008-1229-7987","affiliations":[{"raw_affiliation_string":"Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076336508","display_name":"Can Cui","orcid":"https://orcid.org/0009-0001-7656-9776"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Can Cui","raw_affiliation_strings":["Hebei University of Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0009-0001-7656-9776","affiliations":[{"raw_affiliation_string":"Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102735318","display_name":"Kun Fu","orcid":"https://orcid.org/0000-0001-8399-9101"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Fu","raw_affiliation_strings":["Hebei University of Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0001-8399-9101","affiliations":[{"raw_affiliation_string":"Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010726730","display_name":"Bingxin Niu","orcid":"https://orcid.org/0000-0002-8125-5472"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bingxin Niu","raw_affiliation_strings":["Hebei University of Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-8125-5472","affiliations":[{"raw_affiliation_string":"Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009013876","display_name":"Dongxiao He","orcid":"https://orcid.org/0000-0002-1915-4179"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongxiao He","raw_affiliation_strings":["Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-1915-4179","affiliations":[{"raw_affiliation_string":"Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030187602","display_name":"Yuanfang Guo","orcid":"https://orcid.org/0000-0003-4592-8083"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanfang Guo","raw_affiliation_strings":["Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4592-8083","affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100422246","display_name":"Zhen Wang","orcid":"https://orcid.org/0000-0001-5007-6327"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Wang","raw_affiliation_strings":["Northwestern Polytechnical University, Xi'an, China"],"raw_orcid":"https://orcid.org/0000-0001-5007-6327","affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100443616","display_name":"Chuan Wang","orcid":"https://orcid.org/0000-0003-3856-7646"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210156404","display_name":"Institute of Information Engineering","ror":"https://ror.org/04r53se39","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210156404"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuan Wang","raw_affiliation_strings":["Institute of Information Engineering Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-3856-7646","affiliations":[{"raw_affiliation_string":"Institute of Information Engineering Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210156404","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068837264","display_name":"Xiaochun Cao","orcid":"https://orcid.org/0000-0001-7141-708X"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaochun Cao","raw_affiliation_strings":["Sun Yat-Sen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-7141-708X","affiliations":[{"raw_affiliation_string":"Sun Yat-Sen University, Shenzhen, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003769188","display_name":"Liang Yang","orcid":"https://orcid.org/0000-0001-6291-4359"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Yang","raw_affiliation_strings":["Hebei University of Technology, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0001-6291-4359","affiliations":[{"raw_affiliation_string":"Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":10,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I184843921"],"apc_list":null,"apc_paid":null,"fwci":0.3408,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.6671905,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"481","last_page":"489"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T12292","display_name":"Graph Theory and Algorithms","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9929999709129333,"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/computer-science","display_name":"Computer science","score":0.7053715586662292},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5874841809272766},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5688848495483398},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5655473470687866},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.516154408454895},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4628623425960541},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3231312334537506}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7053715586662292},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5874841809272766},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5688848495483398},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5655473470687866},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.516154408454895},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4628623425960541},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3231312334537506},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3581783.3612196","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3581783.3612196","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2741201074","https://openalex.org/W2788919350","https://openalex.org/W3128443161","https://openalex.org/W3152560880","https://openalex.org/W3160872503","https://openalex.org/W3169253336","https://openalex.org/W3175164304","https://openalex.org/W3208180646","https://openalex.org/W4285412155","https://openalex.org/W4304092048","https://openalex.org/W4318812135","https://openalex.org/W4382239624","https://openalex.org/W6604346090"],"related_works":["https://openalex.org/W4394050964","https://openalex.org/W2981877337","https://openalex.org/W2551249631","https://openalex.org/W3203938600","https://openalex.org/W2169074127","https://openalex.org/W83146503","https://openalex.org/W2163707935","https://openalex.org/W202723009","https://openalex.org/W2145955964","https://openalex.org/W2188612292"],"abstract_inverted_index":{"Graph":[0],"Neural":[1,38],"Networks":[2,39],"(GNNs)":[3],"have":[4],"been":[5],"the":[6,42,56,68,72,76,94,102,118,126,160,176,183,192,212,215,224,228,231],"standard":[7],"toolkit":[8],"for":[9,26,124,159],"processing":[10],"non-euclidean":[11],"spatial":[12],"data":[13],"since":[14,31],"their":[15,23,197],"powerful":[16],"capability":[17],"in":[18,59],"graph":[19,207],"representation":[20],"learning.":[21],"Unfortunately,":[22],"training":[24,135],"strategy":[25],"network":[27,63],"parameters":[28,61,146,194],"is":[29,33,99,137,201],"inefficient":[30],"it":[32],"directly":[34],"inherited":[35],"from":[36,101,105],"classic":[37],"(NNs),":[40],"ignoring":[41],"characteristic":[43],"of":[44,75,96,179,214,230],"GNNs.":[45,220],"To":[46],"alleviate":[47],"this":[48],"issue,":[49],"experimental":[50],"analyses":[51],"are":[52,80,121,157],"performed":[53],"to":[54,107,196,203,218],"investigate":[55],"knowledge":[57],"captured":[58],"classifier":[60,77,145,185,193],"during":[62],"training.":[64],"We":[65],"conclude":[66,92],"that":[67,93,113],"parameter":[69,78,119],"features,":[70],"i.e.,":[71],"column":[73],"vectors":[74],"matrix,":[79],"cluster":[81,116],"representations":[82,143],"with":[83,115,182,191],"high":[84],"discriminability.":[85],"And":[86],"after":[87],"a":[88,132,148,205],"theoretical":[89],"analysis,":[90],"we":[91],"discriminability":[95],"these":[97],"features":[98,120],"obtained":[100],"feature":[103,127,150,177],"propagation":[104,128,151,178],"nodes":[106,190],"parameters.":[108,186],"Furthermore,":[109],"an":[110],"experiment":[111],"verifies":[112],"compared":[114],"centroids,":[117],"more":[122],"potential":[123],"augmenting":[125],"between":[129],"nodes.":[130],"Accordingly,":[131],"novel":[133,206],"GNN-specific":[134],"framework":[136,217],"proposed":[138,216,232],"by":[139],"simultaneously":[140],"updating":[141],"node":[142,181],"and":[144,167,227],"via":[147],"unified":[149],"scheme.":[152],"Moreover,":[153],"two":[154],"augmentation":[155],"schemes":[156],"implemented":[158],"framework,":[161],"named":[162],"Full":[163,169],"Propagation":[164,170],"Augmentation":[165,171],"(FPA)":[166],"Simplified":[168],"(SFPA).":[172],"Specifically,":[173],"FPA":[174,200],"augmentates":[175],"each":[180],"updated":[184],"SFPA":[187],"only":[188],"augments":[189],"corresponding":[195],"clusters.":[198],"Theoretically,":[199],"equivalent":[202],"optimizing":[204],"learning":[208],"objective,":[209],"which":[210],"demonstrates":[211],"universality":[213,229],"existing":[219],"Extensive":[221],"experiments":[222],"demonstrate":[223],"superior":[225],"performance":[226],"framework.":[233]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}