{"id":"https://openalex.org/W4400491188","doi":"https://doi.org/10.1109/cscwd61410.2024.10580417","title":"GMAE: Representation Learning on Graph via Masked Graph Autoencoders","display_name":"GMAE: Representation Learning on Graph via Masked Graph Autoencoders","publication_year":2024,"publication_date":"2024-05-08","ids":{"openalex":"https://openalex.org/W4400491188","doi":"https://doi.org/10.1109/cscwd61410.2024.10580417"},"language":"en","primary_location":{"id":"doi:10.1109/cscwd61410.2024.10580417","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/cscwd61410.2024.10580417","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101395911","display_name":"Chengbin Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengbin Zheng","raw_affiliation_strings":["Xiamen University,School of Informatics,Computer Science Department,Xiamen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xiamen University,School of Informatics,Computer Science Department,Xiamen,China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102019681","display_name":"Zhicheng Yang","orcid":"https://orcid.org/0000-0002-7580-5183"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhicheng Yang","raw_affiliation_strings":["Xiamen University,School of Informatics,Computer Science Department,Xiamen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xiamen University,School of Informatics,Computer Science Department,Xiamen,China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015745132","display_name":"Yang Lu","orcid":"https://orcid.org/0000-0002-3497-9611"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Lu","raw_affiliation_strings":["Xiamen University,School of Informatics,Computer Science Department,Xiamen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xiamen University,School of Informatics,Computer Science Department,Xiamen,China","institution_ids":["https://openalex.org/I191208505"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I191208505"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2515","last_page":"2521"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9990000128746033,"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":0.9990000128746033,"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":0.9800999760627747,"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/T10028","display_name":"Topic Modeling","score":0.9318000078201294,"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":0.6767494678497314},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6261748671531677},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46472862362861633},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4273757338523865},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.40786927938461304}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6767494678497314},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6261748671531677},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46472862362861633},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4273757338523865},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.40786927938461304},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cscwd61410.2024.10580417","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/cscwd61410.2024.10580417","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"self-supervised":[3,109,195],"learning,":[4],"particularly":[5],"autoencoders,":[6],"has":[7],"garnered":[8],"extensive":[9],"research":[10],"interest,":[11],"emerging":[12],"as":[13,149],"one":[14],"of":[15,65,165],"the":[16,62,114,122,126,137,146,150,157,163,170],"most":[17],"exciting":[18],"learning":[19],"paradigms":[20],"and":[21,27,91,95,168,193,216],"achieving":[22],"success":[23],"in":[24,40,81,124,184],"computer":[25],"vision":[26],"other":[28],"artificial":[29],"intelligence":[30],"domains.":[31],"However,":[32],"autoencoders":[33,183],"have":[34,204],"yet":[35,107],"to":[36,69,97,116,120,152,173],"demonstrate":[37],"their":[38],"potential":[39],"processing":[41],"graph":[42,49,67,75,166,182,186,202,217],"data":[43,187],"fully.":[44],"To":[45],"effectively":[46],"learn":[47,70],"from":[48,73,156],"data,":[50,76],"we":[51,85,130],"propose":[52],"a":[53,105,132,142,190],"novel":[54],"Masked":[55],"Graph":[56],"Autoencoder":[57],"(MGAE)":[58],"framework.":[59],"MGAE":[60],"utilizes":[61],"pretext":[63],"task":[64],"masked":[66,87,128],"reconstruction":[68],"high-quality":[71],"representations":[72],"unlabeled":[74],"incorporating":[77],"two":[78],"core":[79],"designs":[80],"its":[82],"structure.":[83],"Firstly,":[84],"randomly":[86],"numerous":[88],"node":[89,212],"features":[90],"edges":[92],"during":[93],"training":[94],"attempted":[96],"reconstruct":[98],"this":[99],"missing":[100],"information.":[101,177],"This":[102,160],"approach":[103],"creates":[104],"challenging":[106],"meaningful":[108],"task,":[110],"beneficial":[111],"for":[112,135],"applying":[113],"model":[115,123],"downstream":[117],"tasks.":[118],"Secondly,":[119],"aid":[121],"reconstructing":[125],"extensively":[127],"information,":[129],"introduce":[131],"new":[133],"module":[134],"matching":[136],"latent":[138],"representation":[139],"space,":[140],"utilizing":[141],"neural":[143],"network":[144],"with":[145],"same":[147],"structure":[148],"encoder":[151],"generate":[153],"predictive":[154],"targets":[155],"unmasked":[158],"graph.":[159],"design":[161],"mitigates":[162],"impact":[164],"masking":[167],"enhances":[169],"model\u2019s":[171],"capability":[172],"capture":[174],"high-level":[175],"semantic":[176],"Our":[178],"framework":[179],"outperforms":[180],"traditional":[181],"handling":[185],"by":[188],"offering":[189],"more":[191],"robust":[192],"reliable":[194],"mechanism.":[196],"Extensive":[197],"experiments":[198],"conducted":[199],"on":[200],"various":[201],"benchmarks":[203],"demonstrated":[205],"MGAE\u2019s":[206],"effectiveness":[207],"across":[208],"multiple":[209],"tasks,":[210],"including":[211],"classification,":[213],"link":[214],"prediction,":[215],"classification.":[218]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}