{"id":"https://openalex.org/W4210476371","doi":"https://doi.org/10.1109/tpami.2022.3147886","title":"Learning Representations by Graphical Mutual Information Estimation and Maximization","display_name":"Learning Representations by Graphical Mutual Information Estimation and Maximization","publication_year":2022,"publication_date":"2022-02-01","ids":{"openalex":"https://openalex.org/W4210476371","doi":"https://doi.org/10.1109/tpami.2022.3147886","pmid":"https://pubmed.ncbi.nlm.nih.gov/35104214"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2022.3147886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3147886","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","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/A5101954954","display_name":"Zhen Peng","orcid":"https://orcid.org/0000-0001-9791-6637"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhen Peng","raw_affiliation_strings":["School of Computer Science and Technology, Xi&#x0027;an Jiaotong University, Xi&#x0027;an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xi&#x0027;an Jiaotong University, Xi&#x0027;an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013911439","display_name":"Minnan Luo","orcid":"https://orcid.org/0000-0002-0140-7860"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minnan Luo","raw_affiliation_strings":["School of Computer Science and Technology, Xi&#x0027;an Jiaotong University, Xi&#x0027;an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xi&#x0027;an Jiaotong University, Xi&#x0027;an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032642601","display_name":"Wenbing Huang","orcid":"https://orcid.org/0000-0002-2566-4159"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenbing Huang","raw_affiliation_strings":["Institute for AI Industry Research, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute for AI Industry Research, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029588473","display_name":"Jundong Li","orcid":"https://orcid.org/0000-0002-1878-817X"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jundong Li","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA, USA","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041083459","display_name":"Qinghua Zheng","orcid":"https://orcid.org/0000-0002-8436-4754"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinghua Zheng","raw_affiliation_strings":["School of Computer Science and Technology, Xi&#x0027;an Jiaotong University, Xi&#x0027;an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xi&#x0027;an Jiaotong University, Xi&#x0027;an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055546056","display_name":"Fuchun Sun","orcid":"https://orcid.org/0000-0003-3546-6305"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fuchun Sun","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068865316","display_name":"Junzhou Huang","orcid":"https://orcid.org/0000-0002-9548-1227"},"institutions":[{"id":"https://openalex.org/I189196454","display_name":"The University of Texas at Arlington","ror":"https://ror.org/019kgqr73","country_code":"US","type":"education","lineage":["https://openalex.org/I189196454"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Junzhou Huang","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX, USA","institution_ids":["https://openalex.org/I189196454"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5101954954"],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":1.9885,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.87971105,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"45","issue":"1","first_page":"722","last_page":"737"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9994999766349792,"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":0.9887999892234802,"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/computer-science","display_name":"Computer science","score":0.679265558719635},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.6567502617835999},{"id":"https://openalex.org/keywords/graph-embedding","display_name":"Graph embedding","score":0.5683912634849548},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.5457952618598938},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.514318585395813},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.49510470032691956},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4840811789035797},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.46676796674728394},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.44687891006469727},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.43526941537857056},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4194856286048889},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.418204665184021},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.4157070517539978},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3980535864830017},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36182135343551636},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3591843843460083},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2517985701560974},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20253434777259827},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.0982198715209961}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.679265558719635},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.6567502617835999},{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.5683912634849548},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.5457952618598938},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.514318585395813},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.49510470032691956},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4840811789035797},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.46676796674728394},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.44687891006469727},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.43526941537857056},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4194856286048889},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.418204665184021},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.4157070517539978},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3980535864830017},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36182135343551636},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3591843843460083},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2517985701560974},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20253434777259827},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.0982198715209961}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2022.3147886","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3147886","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:35104214","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35104214","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 pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3265846782","display_name":null,"funder_award_id":"62006137","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4303215675","display_name":null,"funder_award_id":"62192781","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4896784468","display_name":null,"funder_award_id":"62137002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G568373945","display_name":null,"funder_award_id":"61872287","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6387986177","display_name":null,"funder_award_id":"61721002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6393000781","display_name":null,"funder_award_id":"62050194","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation 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/F4320330193","display_name":"Chinese Academy of Engineering","ror":"https://ror.org/00z3yke57"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":88,"referenced_works":["https://openalex.org/W1492581097","https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1593045043","https://openalex.org/W1662133657","https://openalex.org/W1677182931","https://openalex.org/W1836465849","https://openalex.org/W1874027545","https://openalex.org/W1888005072","https://openalex.org/W1987971958","https://openalex.org/W2012762214","https://openalex.org/W2030233188","https://openalex.org/W2033083678","https://openalex.org/W2089554624","https://openalex.org/W2090891622","https://openalex.org/W2101234009","https://openalex.org/W2108384452","https://openalex.org/W2114188922","https://openalex.org/W2114507260","https://openalex.org/W2117248802","https://openalex.org/W2122646361","https://openalex.org/W2125031621","https://openalex.org/W2130354913","https://openalex.org/W2134008243","https://openalex.org/W2134255060","https://openalex.org/W2139823104","https://openalex.org/W2153959628","https://openalex.org/W2154851992","https://openalex.org/W2167250030","https://openalex.org/W2187089797","https://openalex.org/W2393319904","https://openalex.org/W2402531259","https://openalex.org/W2415243320","https://openalex.org/W2419501139","https://openalex.org/W2624407581","https://openalex.org/W2735272571","https://openalex.org/W2741048099","https://openalex.org/W2741114205","https://openalex.org/W2761434131","https://openalex.org/W2764075199","https://openalex.org/W2788284887","https://openalex.org/W2808544127","https://openalex.org/W2887997457","https://openalex.org/W2888657195","https://openalex.org/W2891649471","https://openalex.org/W2906836970","https://openalex.org/W2944250323","https://openalex.org/W2953048569","https://openalex.org/W2962756421","https://openalex.org/W2963013895","https://openalex.org/W2963241951","https://openalex.org/W2963312446","https://openalex.org/W2963486145","https://openalex.org/W2963695795","https://openalex.org/W2963757395","https://openalex.org/W2964015378","https://openalex.org/W3012816161","https://openalex.org/W3104038788","https://openalex.org/W3104097132","https://openalex.org/W3189092450","https://openalex.org/W4232613155","https://openalex.org/W4291474301","https://openalex.org/W4293651439","https://openalex.org/W4294558607","https://openalex.org/W4297733535","https://openalex.org/W4297808394","https://openalex.org/W4320013936","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6635456232","https://openalex.org/W6638667902","https://openalex.org/W6675354045","https://openalex.org/W6678885109","https://openalex.org/W6680434193","https://openalex.org/W6699364125","https://openalex.org/W6717434760","https://openalex.org/W6726873649","https://openalex.org/W6738964360","https://openalex.org/W6744557953","https://openalex.org/W6744580074","https://openalex.org/W6747837047","https://openalex.org/W6748799445","https://openalex.org/W6748856961","https://openalex.org/W6749077313","https://openalex.org/W6754278344","https://openalex.org/W6757713970","https://openalex.org/W6766066096","https://openalex.org/W6844194202"],"related_works":["https://openalex.org/W3174759195","https://openalex.org/W3167013339","https://openalex.org/W4287121366","https://openalex.org/W60493759","https://openalex.org/W4308619659","https://openalex.org/W3213069564","https://openalex.org/W2997229301","https://openalex.org/W2794802664","https://openalex.org/W4389072551","https://openalex.org/W4378421684"],"abstract_inverted_index":{"The":[0],"rich":[1],"content":[2],"in":[3,128,185],"various":[4,186],"real-world":[5],"networks":[6,15],"such":[7,189],"as":[8,190],"social":[9],"networks,":[10,12],"biological":[11],"and":[13,33,61,77,109,138,153,166,195],"communication":[14],"provides":[16],"unprecedented":[17],"opportunities":[18],"for":[19,81],"unsupervised":[20,163],"machine":[21],"learning":[22],"on":[23],"graphs.":[24],"This":[25],"paper":[26],"investigates":[27],"the":[28,72,103,120,156,170],"fundamental":[29],"problem":[30],"of":[31,106,123,158],"preserving":[32],"extracting":[34],"abundant":[35],"information":[36,53,143],"from":[37,55,88],"graph-structured":[38],"data":[39],"into":[40],"embedding":[41,164],"space":[42,57],"without":[43],"external":[44],"supervision.":[45],"To":[46],"this":[47],"end,":[48],"we":[49,160],"generalize":[50],"conventional":[51],"mutual":[52,142],"computation":[54],"vector":[56],"to":[58,70,119,169],"graph":[59,76,86],"domain":[60],"present":[62],"a":[63,89],"novel":[64],"concept,":[65],"Graphical":[66],"Mutual":[67],"Information":[68],"(GMI),":[69],"measure":[71],"correlation":[73],"between":[74],"input":[75,124],"hidden":[78],"representation.":[79],"Except":[80],"standard":[82],"GMI":[83,108,180],"which":[84],"considers":[85],"structures":[87],"local":[90],"perspective,":[91],"our":[92,147,179],"further":[93],"proposed":[94],"GMI++":[95],"additionally":[96],"captures":[97],"global":[98],"topological":[99],"properties":[100],"by":[101,140],"analyzing":[102],"co-occurrence":[104],"relationship":[105],"nodes.":[107],"its":[110],"extension":[111],"exhibit":[112],"several":[113],"benefits:":[114],"First,":[115],"they":[116,133],"are":[117],"invariant":[118],"isomorphic":[121],"transformation":[122],"graphs-an":[125],"inevitable":[126],"constraint":[127],"many":[129],"existing":[130],"methods;":[131,145],"Second,":[132],"can":[134],"be":[135],"efficiently":[136],"estimated":[137],"maximized":[139],"current":[141],"estimation":[144],"Lastly,":[146],"theoretical":[148],"analysis":[149],"confirms":[150],"their":[151],"correctness":[152],"rationality.":[154],"With":[155],"aid":[157],"GMI,":[159],"develop":[161],"an":[162],"model":[165],"adapt":[167],"it":[168],"specific":[171],"anomaly":[172,196],"detection":[173],"task.":[174],"Extensive":[175],"experiments":[176],"indicate":[177],"that":[178],"methods":[181],"achieve":[182],"promising":[183],"performance":[184],"downstream":[187],"tasks,":[188],"node":[191],"classification,":[192],"link":[193],"prediction,":[194],"detection.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
