{"id":"https://openalex.org/W4304479925","doi":"https://doi.org/10.1109/tnnls.2022.3210370","title":"Seeing All From a Few: Nodes Selection Using Graph Pooling for Graph Clustering","display_name":"Seeing All From a Few: Nodes Selection Using Graph Pooling for Graph Clustering","publication_year":2022,"publication_date":"2022-10-10","ids":{"openalex":"https://openalex.org/W4304479925","doi":"https://doi.org/10.1109/tnnls.2022.3210370","pmid":"https://pubmed.ncbi.nlm.nih.gov/36215388"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3210370","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3210370","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5100377941","display_name":"Yiming Wang","orcid":"https://orcid.org/0000-0002-8765-7640"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiming Wang","raw_affiliation_strings":["Institute of Information Science, Beijing Jiaotong University, Beijing, China","Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8765-7640","affiliations":[{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037345013","display_name":"Dongxia Chang","orcid":"https://orcid.org/0000-0002-9718-4277"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongxia Chang","raw_affiliation_strings":["Institute of Information Science, Beijing Jiaotong University, Beijing, China","Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9718-4277","affiliations":[{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102923156","display_name":"Zhiqiang Fu","orcid":"https://orcid.org/0000-0002-8756-6423"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqiang Fu","raw_affiliation_strings":["Institute of Information Science, Beijing Jiaotong University, Beijing, China","Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8756-6423","affiliations":[{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100362745","display_name":"Yao Zhao","orcid":"https://orcid.org/0000-0002-8581-9554"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Zhao","raw_affiliation_strings":["Institute of Information Science, Beijing Jiaotong University, Beijing, China","Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8581-9554","affiliations":[{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":0.3936,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.66934817,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"35","issue":"5","first_page":"7231","last_page":"7237"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9980999827384949,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9876000285148621,"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/cluster-analysis","display_name":"Cluster analysis","score":0.6752850413322449},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5818400979042053},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.5166945457458496},{"id":"https://openalex.org/keywords/clustering-coefficient","display_name":"Clustering coefficient","score":0.448635995388031},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.419186532497406},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.37012577056884766},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24730688333511353}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6752850413322449},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5818400979042053},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5166945457458496},{"id":"https://openalex.org/C22047676","wikidata":"https://www.wikidata.org/wiki/Q898680","display_name":"Clustering coefficient","level":3,"score":0.448635995388031},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.419186532497406},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.37012577056884766},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24730688333511353}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3210370","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3210370","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:36215388","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36215388","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2782133125","display_name":null,"funder_award_id":"62272035","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3796867913","display_name":null,"funder_award_id":"2021YJS027","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G3910816902","display_name":null,"funder_award_id":"2018AAA0102100","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W2089923519","https://openalex.org/W2121947440","https://openalex.org/W2187089797","https://openalex.org/W2415243320","https://openalex.org/W2604942799","https://openalex.org/W2767404761","https://openalex.org/W2808409763","https://openalex.org/W2907101105","https://openalex.org/W2921065608","https://openalex.org/W2963066159","https://openalex.org/W2964732194","https://openalex.org/W2973511309","https://openalex.org/W2997997679","https://openalex.org/W3004349648","https://openalex.org/W3004946360","https://openalex.org/W3012918605","https://openalex.org/W3034531178","https://openalex.org/W3034681945","https://openalex.org/W3034903580","https://openalex.org/W3043238202","https://openalex.org/W3044498809","https://openalex.org/W3091336992","https://openalex.org/W3096520621","https://openalex.org/W3101709902","https://openalex.org/W3106616149","https://openalex.org/W3117762922","https://openalex.org/W3133780103","https://openalex.org/W3145608311","https://openalex.org/W6668990524","https://openalex.org/W6685380521","https://openalex.org/W6720006811","https://openalex.org/W6726873649","https://openalex.org/W6730084236","https://openalex.org/W6745537798","https://openalex.org/W6756192570","https://openalex.org/W6761665040","https://openalex.org/W6779032261","https://openalex.org/W6783712305"],"related_works":["https://openalex.org/W4387497383","https://openalex.org/W3183948672","https://openalex.org/W3173606202","https://openalex.org/W3110381201","https://openalex.org/W2948807893","https://openalex.org/W2935909890","https://openalex.org/W2778153218","https://openalex.org/W2758277628","https://openalex.org/W1531601525","https://openalex.org/W3015684221"],"abstract_inverted_index":{"Recently,":[0],"there":[1,37],"has":[2],"been":[3],"considerable":[4],"research":[5],"interest":[6],"in":[7,42],"graph":[8,15,30,44,50,66,86,96,101,107,218],"clustering":[9,71,127,197,208],"aimed":[10],"at":[11],"data":[12],"partition":[13],"using":[14,206],"information.":[16],"However,":[17,36],"one":[18],"limitation":[19],"of":[20,75,160,170,186,199,210,223],"most":[21,157],"graph-based":[22],"methods":[23],"is":[24,34,59,91,131,152,204],"that":[25,28,45,113],"they":[26],"assume":[27,112],"the":[29,43,60,65,73,106,125,147,156,163,168,177,184,187,191,196,207,211,221,224],"structure":[31],"to":[32,49,63,72,104,124,154,176,194],"operate":[33],"reliable.":[35],"are":[38,46,122],"inevitably":[39],"some":[40],"edges":[41,165,189],"not":[47],"conducive":[48],"clustering,":[51],"which":[52,90],"we":[53,81,111],"call":[54],"spurious":[55,188],"edges.":[56],"This":[57,180],"brief":[58],"first":[61],"attempt":[62],"employ":[64],"pooling":[67,102,150],"technique":[68],"for":[69],"node":[70,116,121,130],"best":[74],"our":[76],"knowledge.":[77],"In":[78,109],"this":[79,129,134,145],"brief,":[80],"propose":[82],"a":[83,94,100,115,140,202],"novel":[84],"dual":[85],"embedding":[87],"network":[88],"(DGEN),":[89],"designed":[92],"as":[93,139],"two-step":[95],"encoder":[97],"connected":[98],"by":[99],"layer":[103],"learn":[105],"embedding.":[108],"DGEN,":[110],"if":[114],"and":[117,133,162,172],"its":[118],"nearest":[119,174],"neighboring":[120],"close":[123],"same":[126],"center,":[128],"informative,":[132],"edge":[135],"can":[136,181],"be":[137],"considered":[138],"cluster-friendly":[141],"edge.":[142],"Based":[143],"on":[144,167,190,215],"assumption,":[146],"neighbor":[148],"cluster":[149,178],"(NCPool)":[151],"devised":[153],"select":[155],"informative":[158],"subset":[159],"nodes":[161,171],"corresponding":[164],"based":[166],"distance":[169],"their":[173],"neighbors":[175],"centers.":[179],"effectively":[182],"alleviate":[183],"impact":[185],"clustering.":[192],"Finally,":[193],"obtain":[195],"assignment":[198],"all":[200],"nodes,":[201],"classifier":[203],"trained":[205],"results":[209],"selected":[212],"nodes.":[213],"Experiments":[214],"five":[216],"benchmark":[217],"datasets":[219],"demonstrate":[220],"superiority":[222],"proposed":[225],"method":[226],"over":[227],"state-of-the-art":[228],"algorithms.":[229]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
