{"id":"https://openalex.org/W2899431500","doi":"https://doi.org/10.1109/tsmc.2018.2876202","title":"Enhanced Ensemble Clustering via Fast Propagation of Cluster-Wise Similarities","display_name":"Enhanced Ensemble Clustering via Fast Propagation of Cluster-Wise Similarities","publication_year":2018,"publication_date":"2018-11-06","ids":{"openalex":"https://openalex.org/W2899431500","doi":"https://doi.org/10.1109/tsmc.2018.2876202","mag":"2899431500"},"language":"en","primary_location":{"id":"doi:10.1109/tsmc.2018.2876202","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmc.2018.2876202","pdf_url":null,"source":{"id":"https://openalex.org/S4210209078","display_name":"IEEE Transactions on Systems Man and Cybernetics Systems","issn_l":"2168-2216","issn":["2168-2216","2168-2232"],"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 Systems, Man, and Cybernetics: Systems","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1810.12544","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Dong Huang","orcid":"https://orcid.org/0000-0003-3923-8828"},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Huang","raw_affiliation_strings":["College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-3923-8828","affiliations":[{"raw_affiliation_string":"College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China","institution_ids":["https://openalex.org/I101479585"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chang-Dong Wang","orcid":"https://orcid.org/0000-0001-5972-559X"},"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":"Chang-Dong Wang","raw_affiliation_strings":["School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-5972-559X","affiliations":[{"raw_affiliation_string":"School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hongxing Peng","orcid":"https://orcid.org/0000-0002-1872-8855"},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongxing Peng","raw_affiliation_strings":["College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-1872-8855","affiliations":[{"raw_affiliation_string":"College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China","institution_ids":["https://openalex.org/I101479585"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jianhuang Lai","orcid":"https://orcid.org/0000-0003-3883-2024"},"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":"Jianhuang Lai","raw_affiliation_strings":["School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-3883-2024","affiliations":[{"raw_affiliation_string":"School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":null,"display_name":"Chee-Keong Kwoh","orcid":"https://orcid.org/0000-0002-8547-6387"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Chee-Keong Kwoh","raw_affiliation_strings":["School of Computer Science and Engineering, Nanyang Technological University, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-8547-6387","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.5338,"has_fulltext":false,"cited_by_count":203,"citation_normalized_percentile":{"value":0.96535227,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"51","issue":"1","first_page":"508","last_page":"520"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.5630000233650208,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.5630000233650208,"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":0.10939999669790268,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.10599999874830246,"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":0.7498999834060669},{"id":"https://openalex.org/keywords/jaccard-index","display_name":"Jaccard index","score":0.5252000093460083},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5045999884605408},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49810001254081726},{"id":"https://openalex.org/keywords/assortativity","display_name":"Assortativity","score":0.4936999976634979},{"id":"https://openalex.org/keywords/clustering-coefficient","display_name":"Clustering coefficient","score":0.4641000032424927},{"id":"https://openalex.org/keywords/consensus-clustering","display_name":"Consensus clustering","score":0.4296000003814697},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.4212999939918518},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.37929999828338623},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.367000013589859}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7498999834060669},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.572700023651123},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5482000112533569},{"id":"https://openalex.org/C203519979","wikidata":"https://www.wikidata.org/wiki/Q865360","display_name":"Jaccard index","level":3,"score":0.5252000093460083},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5045999884605408},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49810001254081726},{"id":"https://openalex.org/C89694873","wikidata":"https://www.wikidata.org/wiki/Q4810299","display_name":"Assortativity","level":3,"score":0.4936999976634979},{"id":"https://openalex.org/C22047676","wikidata":"https://www.wikidata.org/wiki/Q898680","display_name":"Clustering coefficient","level":3,"score":0.4641000032424927},{"id":"https://openalex.org/C186767784","wikidata":"https://www.wikidata.org/wiki/Q5162841","display_name":"Consensus clustering","level":5,"score":0.4296000003814697},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.4212999939918518},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40470001101493835},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.37929999828338623},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.367000013589859},{"id":"https://openalex.org/C22648726","wikidata":"https://www.wikidata.org/wiki/Q7523744","display_name":"Single-linkage clustering","level":5,"score":0.34950000047683716},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.3449000120162964},{"id":"https://openalex.org/C121194460","wikidata":"https://www.wikidata.org/wiki/Q856741","display_name":"Random walk","level":2,"score":0.3416000008583069},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.3330000042915344},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32109999656677246},{"id":"https://openalex.org/C111208986","wikidata":"https://www.wikidata.org/wiki/Q901698","display_name":"Distance matrix","level":2,"score":0.3206000030040741},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.3197999894618988},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.31940001249313354},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.3142000138759613},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.30869999527931213},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.29789999127388},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.2971000075340271},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.28929999470710754},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2777999937534332},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.2718000113964081},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.2685999870300293},{"id":"https://openalex.org/C54540088","wikidata":"https://www.wikidata.org/wiki/Q3498041","display_name":"Intersection graph","level":4,"score":0.2556999921798706},{"id":"https://openalex.org/C111442797","wikidata":"https://www.wikidata.org/wiki/Q7291446","display_name":"Rand index","level":3,"score":0.2540999948978424},{"id":"https://openalex.org/C49555168","wikidata":"https://www.wikidata.org/wiki/Q176583","display_name":"Stochastic matrix","level":3,"score":0.25380000472068787}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tsmc.2018.2876202","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmc.2018.2876202","pdf_url":null,"source":{"id":"https://openalex.org/S4210209078","display_name":"IEEE Transactions on Systems Man and Cybernetics Systems","issn_l":"2168-2216","issn":["2168-2216","2168-2232"],"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 Systems, Man, and Cybernetics: Systems","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1810.12544","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1810.12544","pdf_url":"https://arxiv.org/pdf/1810.12544","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1810.12544","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1810.12544","pdf_url":"https://arxiv.org/pdf/1810.12544","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3887459543","display_name":null,"funder_award_id":"2016A030306014","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G4381255454","display_name":null,"funder_award_id":"2016A030310457","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G5259213742","display_name":null,"funder_award_id":"61573387","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5409299611","display_name":null,"funder_award_id":"61876193","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5802173662","display_name":null,"funder_award_id":"61502543","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7751653729","display_name":null,"funder_award_id":"61602189","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/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W160698270","https://openalex.org/W1517123091","https://openalex.org/W1599173567","https://openalex.org/W1608127741","https://openalex.org/W1648123822","https://openalex.org/W1919721856","https://openalex.org/W1965841419","https://openalex.org/W1967168896","https://openalex.org/W1967761844","https://openalex.org/W1971750638","https://openalex.org/W1977442405","https://openalex.org/W1990063425","https://openalex.org/W1994002853","https://openalex.org/W2011430131","https://openalex.org/W2025549250","https://openalex.org/W2028899393","https://openalex.org/W2035379061","https://openalex.org/W2037984690","https://openalex.org/W2039944676","https://openalex.org/W2080909935","https://openalex.org/W2086320398","https://openalex.org/W2095293504","https://openalex.org/W2098509290","https://openalex.org/W2105268089","https://openalex.org/W2112796928","https://openalex.org/W2115346774","https://openalex.org/W2116984363","https://openalex.org/W2121947440","https://openalex.org/W2122869529","https://openalex.org/W2127615881","https://openalex.org/W2129395028","https://openalex.org/W2137813581","https://openalex.org/W2138810473","https://openalex.org/W2139280638","https://openalex.org/W2161669108","https://openalex.org/W2165232124","https://openalex.org/W2262682506","https://openalex.org/W2301166038","https://openalex.org/W2344304498","https://openalex.org/W2404760654","https://openalex.org/W2416590358","https://openalex.org/W2514885441","https://openalex.org/W2520619240","https://openalex.org/W2561609067","https://openalex.org/W2568618480","https://openalex.org/W2601026776","https://openalex.org/W2605427894","https://openalex.org/W2610204566","https://openalex.org/W2746272230","https://openalex.org/W2753315806","https://openalex.org/W2756806229","https://openalex.org/W2767141167","https://openalex.org/W2952171869","https://openalex.org/W3101747232","https://openalex.org/W6684050148"],"related_works":[],"abstract_inverted_index":{"Ensemble":[0],"clustering":[1,31,103,241],"has":[2],"been":[3],"a":[4,100,118,146,177,246],"popular":[5],"research":[6],"topic":[7],"in":[8,18,27,77,90,228],"data":[9],"mining":[10],"and":[11,130,255],"machine":[12],"learning.":[13],"Despite":[14],"its":[15],"significant":[16],"progress":[17],"recent":[19],"years,":[20],"there":[21],"are":[22,235],"still":[23],"two":[24,95,231],"challenging":[25],"issues":[26],"the":[28,36,42,46,51,55,68,78,85,123,131,138,143,155,163,170,187,191,200,203,217,224,239,253],"current":[29],"ensemble":[30,43,102],"research.":[32],"First,":[33],"most":[34],"of":[35,61,109,248,257],"existing":[37],"algorithms":[38],"tend":[39],"to":[40,53,136,161,202,205,214,237],"investigate":[41],"information":[44,57],"at":[45,58],"object-level,":[47],"yet":[48],"often":[49],"lack":[50],"ability":[52],"explore":[54],"rich":[56],"higher":[59],"levels":[60],"granularity.":[62],"Second,":[63],"they":[64],"mostly":[65],"focus":[66],"on":[67,106,153,245],"direct":[69,72],"connections":[70],"(e.g.,":[71],"intersection":[73],"or":[74],"pair-wise":[75],"co-occurrence)":[76],"multiple":[79],"base":[80,124],"clusterings,":[81],"but":[82],"generally":[83],"neglect":[84],"multiscale":[86,225],"indirect":[87],"relationship":[88,220,227],"hidden":[89],"them.":[91],"To":[92],"address":[93],"these":[94],"issues,":[96],"this":[97],"paper":[98],"presents":[99],"novel":[101,232],"approach":[104],"based":[105,152],"fast":[107],"propagation":[108],"cluster-wise":[110,132,179,194,226],"similarities":[111],"via":[112],"random":[113,156],"walks.":[114],"We":[115],"first":[116],"construct":[117],"cluster":[119],"similarity":[120,180,195],"graph":[121,128,164],"with":[122],"clusters":[125],"treated":[126],"as":[127,221,223],"nodes":[129],"Jaccard":[133],"coefficient":[134],"exploited":[135],"compute":[137],"initial":[139],"edge":[140],"weights.":[141],"Upon":[142],"constructed":[144],"graph,":[145],"transition":[147],"probability":[148],"matrix":[149,181,196],"is":[150,159,197,212],"defined,":[151],"which":[154,211],"walk":[157],"process":[158],"conducted":[160],"propagate":[162],"structural":[165],"information.":[166],"Specifically,":[167],"by":[168,185],"investigating":[169],"propagating":[171],"trajectories":[172],"starting":[173],"from":[174,199],"different":[175],"nodes,":[176],"new":[178],"can":[182],"be":[183],"derived":[184],"considering":[186],"trajectory":[188],"relationship.":[189],"Then,":[190],"newly":[192],"obtained":[193],"mapped":[198],"cluster-level":[201],"object-level":[204],"achieve":[206],"an":[207],"enhanced":[208],"co-association":[209],"matrix,":[210],"able":[213],"simultaneously":[215],"capture":[216],"object-wise":[218],"co-occurrence":[219],"well":[222],"ensembles.":[229],"Finally,":[230],"consensus":[233,240],"functions":[234],"proposed":[236],"obtain":[238],"result.":[242],"Extensive":[243],"experiments":[244],"variety":[247],"real-world":[249],"datasets":[250],"have":[251],"demonstrated":[252],"effectiveness":[254],"efficiency":[256],"our":[258],"approach.":[259]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":36},{"year":2024,"cited_by_count":42},{"year":2023,"cited_by_count":61},{"year":2022,"cited_by_count":26},{"year":2021,"cited_by_count":17},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":6}],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2018-11-09T00:00:00"}
