{"id":"https://openalex.org/W3138232647","doi":"https://doi.org/10.1109/bigdata50022.2020.9378031","title":"Graph Clustering with Embedding Propagation","display_name":"Graph Clustering with Embedding Propagation","publication_year":2020,"publication_date":"2020-12-10","ids":{"openalex":"https://openalex.org/W3138232647","doi":"https://doi.org/10.1109/bigdata50022.2020.9378031","mag":"3138232647"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata50022.2020.9378031","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9378031","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","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/A5006897094","display_name":"Carl Yang","orcid":"https://orcid.org/0000-0001-9145-4531"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Carl Yang","raw_affiliation_strings":["Emory University, Atlanta, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Emory University, Atlanta, USA","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100657035","display_name":"Liyuan Liu","orcid":"https://orcid.org/0000-0003-2585-323X"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liyuan Liu","raw_affiliation_strings":["University of Illinois, Urbana Champaign, Urbana, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois, Urbana Champaign, Urbana, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076265126","display_name":"Mengxiong Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mengxiong Liu","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101431903","display_name":"Zongyi Wang","orcid":"https://orcid.org/0000-0002-3026-1557"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zongyi Wang","raw_affiliation_strings":["Google Inc., Mountain View, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google Inc., Mountain View, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100460272","display_name":"Chao Zhang","orcid":"https://orcid.org/0000-0003-3009-598X"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chao Zhang","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019539533","display_name":"Jiawei Han","orcid":"https://orcid.org/0000-0002-3629-2696"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiawei Han","raw_affiliation_strings":["University of Illinois, Urbana Champaign, Urbana, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois, Urbana Champaign, Urbana, USA","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"858","last_page":"867"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9995999932289124,"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":0.9995999932289124,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9829999804496765,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7884906530380249},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.7707068920135498},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7234293222427368},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5617978572845459},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.547698438167572},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.527394711971283},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4836060106754303},{"id":"https://openalex.org/keywords/graph-embedding","display_name":"Graph embedding","score":0.4568808972835541},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43450161814689636},{"id":"https://openalex.org/keywords/complex-network","display_name":"Complex network","score":0.4285215735435486},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3609165549278259},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3244406580924988}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7884906530380249},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7707068920135498},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7234293222427368},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5617978572845459},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.547698438167572},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.527394711971283},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4836060106754303},{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.4568808972835541},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43450161814689636},{"id":"https://openalex.org/C34947359","wikidata":"https://www.wikidata.org/wiki/Q665189","display_name":"Complex network","level":2,"score":0.4285215735435486},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3609165549278259},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3244406580924988},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata50022.2020.9378031","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9378031","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.49000000953674316,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332447","display_name":"U.S. Army","ror":"https://ror.org/00afsp483"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":114,"referenced_works":["https://openalex.org/W67413104","https://openalex.org/W82771173","https://openalex.org/W107622521","https://openalex.org/W179875071","https://openalex.org/W637153065","https://openalex.org/W1495750374","https://openalex.org/W1662382123","https://openalex.org/W1888005072","https://openalex.org/W1956559956","https://openalex.org/W1971421925","https://openalex.org/W1999192586","https://openalex.org/W2025266141","https://openalex.org/W2025768430","https://openalex.org/W2037603696","https://openalex.org/W2041157860","https://openalex.org/W2047013860","https://openalex.org/W2047940964","https://openalex.org/W2051322528","https://openalex.org/W2053522118","https://openalex.org/W2073749068","https://openalex.org/W2090891622","https://openalex.org/W2095705004","https://openalex.org/W2106545428","https://openalex.org/W2107107106","https://openalex.org/W2107961038","https://openalex.org/W2111565546","https://openalex.org/W2114544578","https://openalex.org/W2116341502","https://openalex.org/W2120480077","https://openalex.org/W2133291805","https://openalex.org/W2137962371","https://openalex.org/W2139694940","https://openalex.org/W2145658888","https://openalex.org/W2150442700","https://openalex.org/W2153959628","https://openalex.org/W2154851992","https://openalex.org/W2155461593","https://openalex.org/W2163605009","https://openalex.org/W2164998314","https://openalex.org/W2187089797","https://openalex.org/W2217442075","https://openalex.org/W2221409856","https://openalex.org/W2242161203","https://openalex.org/W2249925396","https://openalex.org/W2325227998","https://openalex.org/W2393319904","https://openalex.org/W2396031973","https://openalex.org/W2405933695","https://openalex.org/W2415243320","https://openalex.org/W2527187792","https://openalex.org/W2551441958","https://openalex.org/W2583803680","https://openalex.org/W2604366058","https://openalex.org/W2613171001","https://openalex.org/W2622489478","https://openalex.org/W2623187518","https://openalex.org/W2741943936","https://openalex.org/W2743289629","https://openalex.org/W2764075199","https://openalex.org/W2765741717","https://openalex.org/W2808466528","https://openalex.org/W2809496930","https://openalex.org/W2898322439","https://openalex.org/W2898475587","https://openalex.org/W2913312729","https://openalex.org/W2950898568","https://openalex.org/W2962756421","https://openalex.org/W2963312446","https://openalex.org/W2963365397","https://openalex.org/W2963416007","https://openalex.org/W2963493749","https://openalex.org/W2963686543","https://openalex.org/W2964015378","https://openalex.org/W2964074409","https://openalex.org/W2964145825","https://openalex.org/W2964199361","https://openalex.org/W2964311892","https://openalex.org/W2964321699","https://openalex.org/W2971325383","https://openalex.org/W2976859544","https://openalex.org/W2997342017","https://openalex.org/W3003757034","https://openalex.org/W3081306295","https://openalex.org/W3102647957","https://openalex.org/W3103254545","https://openalex.org/W3104097132","https://openalex.org/W3104717349","https://openalex.org/W3127524795","https://openalex.org/W6602764823","https://openalex.org/W6604396070","https://openalex.org/W6620673361","https://openalex.org/W6637178625","https://openalex.org/W6640862754","https://openalex.org/W6674330103","https://openalex.org/W6676274861","https://openalex.org/W6679848749","https://openalex.org/W6683180375","https://openalex.org/W6684191040","https://openalex.org/W6685380521","https://openalex.org/W6690230747","https://openalex.org/W6690815549","https://openalex.org/W6699364125","https://openalex.org/W6713582119","https://openalex.org/W6713590816","https://openalex.org/W6716303938","https://openalex.org/W6720006811","https://openalex.org/W6726873649","https://openalex.org/W6727554861","https://openalex.org/W6744043827","https://openalex.org/W6758976677","https://openalex.org/W6763813028","https://openalex.org/W6766066096","https://openalex.org/W6785880030","https://openalex.org/W6790055296"],"related_works":["https://openalex.org/W2129331923","https://openalex.org/W3036264823","https://openalex.org/W3206528106","https://openalex.org/W2912814903","https://openalex.org/W2123605750","https://openalex.org/W4393433587","https://openalex.org/W2088740331","https://openalex.org/W3038102983","https://openalex.org/W2950907416","https://openalex.org/W2734532915"],"abstract_inverted_index":{"In":[0,69],"the":[1,4,13,46,78,123,126,137,175,183,188,192,215],"past":[2],"decade,":[3],"amount":[5],"of":[6,15,49,80,140,177,191,217],"attributed":[7,51,85,172,225],"network":[8,34,99,117,127,165],"data":[9],"has":[10,21,53],"skyrocketed,":[11],"and":[12,29,67,82,101,132,155,206,213],"problem":[14],"identifying":[16],"their":[17],"underlying":[18,158],"group":[19],"structures":[20],"received":[22],"significant":[23,39],"attention.":[24],"By":[25],"leveraging":[26],"both":[27],"attribute":[28],"link":[30],"information,":[31],"recent":[32],"state-of-the-art":[33],"clustering":[35,81],"methods":[36],"have":[37],"achieved":[38],"improvements":[40],"on":[41,84,136,169],"relatively":[42],"clean":[43],"datasets.":[44],"However,":[45],"noisy":[47,221],"nature":[48],"real-world":[50,171,224],"networks":[52,173],"long":[54],"been":[55],"over-looked,":[56],"which":[57],"leads":[58],"to":[59,96,114,128,197,219],"degraded":[60],"performance":[61,190],"facing":[62],"missing":[63],"or":[64],"inaccurate":[65],"attributes":[66],"links.":[68],"this":[70],"work,":[71],"we":[72,88,147],"overcome":[73],"such":[74],"weaknesses":[75],"by":[76],"marrying":[77],"strengths":[79],"embedding":[83,141],"networks.":[86,226],"Specifically,":[87],"propose":[89],"GRACE":[90,150,178,186,218],"(GRAph":[91],"Clustering":[92],"with":[93,160],"Embedding":[94],"propagation),":[95],"simultaneously":[97],"learn":[98],"representations":[100],"identify":[102],"net-work":[103],"clusters":[104,134],"in":[105,125,151,223],"an":[106],"end-to-end":[107],"manner.":[108],"It":[109],"employs":[110],"deep":[111],"denoise":[112],"autoencoders":[113],"generate":[115],"robust":[116],"embeddings":[118,124],"from":[119,182,195],"node":[120,130],"attributes,":[121],"propagates":[122],"capture":[129],"interactions,":[131],"detects":[133],"based":[135],"stable":[138],"state":[139],"propagation.":[142],"To":[143],"provide":[144],"more":[145],"insight,":[146],"further":[148,209],"analyze":[149],"a":[152,200],"theoretical":[153],"manner":[154],"find":[156],"its":[157],"connections":[159],"two":[161],"canonical":[162],"approaches":[163],"for":[164],"modeling.":[166],"Extensive":[167],"experiments":[168,205],"six":[170],"demonstrate":[174,214],"superiority":[176],"over":[179],"various":[180],"baselines":[181],"state-of-the-art.":[184],"Remarkably,":[185],"improves":[187],"averaged":[189],"strongest":[193],"baseline":[194],"0.43":[196],"0.52,":[198],"yielding":[199],"21%":[201],"relative":[202],"improvement.":[203],"Controlled":[204],"case":[207],"studies":[208],"verify":[210],"our":[211],"intuitions":[212],"ability":[216],"handle":[220],"information":[222]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}