{"id":"https://openalex.org/W4206214475","doi":"https://doi.org/10.1155/2022/8046620","title":"Density Peaks Clustering Based on Feature Reduction and Quasi-Monte Carlo","display_name":"Density Peaks Clustering Based on Feature Reduction and Quasi-Monte Carlo","publication_year":2022,"publication_date":"2022-01-06","ids":{"openalex":"https://openalex.org/W4206214475","doi":"https://doi.org/10.1155/2022/8046620"},"language":"en","primary_location":{"id":"doi:10.1155/2022/8046620","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2022/8046620","pdf_url":"https://downloads.hindawi.com/journals/sp/2022/8046620.pdf","source":{"id":"https://openalex.org/S166774750","display_name":"Scientific Programming","issn_l":"1058-9244","issn":["1058-9244","1875-919X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Programming","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://downloads.hindawi.com/journals/sp/2022/8046620.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038606050","display_name":"Zhihui Hu","orcid":"https://orcid.org/0000-0002-3002-8691"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihui Hu","raw_affiliation_strings":["Artificial Intelligence Research Center, Defense Innovation Institute, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Center, Defense Innovation Institute, Beijing, China","institution_ids":["https://openalex.org/I4210100255"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102149060","display_name":"Xiaoran Wei","orcid":"https://orcid.org/0009-0007-8323-4660"},"institutions":[{"id":"https://openalex.org/I31847773","display_name":"Zhejiang Ocean University","ror":"https://ror.org/03mys6533","country_code":"CN","type":"education","lineage":["https://openalex.org/I31847773"]},{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoran Wei","raw_affiliation_strings":["Ocean College, Zhejiang University, Zhoushan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ocean College, Zhejiang University, Zhoushan, China","institution_ids":["https://openalex.org/I31847773","https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101172866","display_name":"Xiaoxu Han","orcid":"https://orcid.org/0009-0001-7991-5881"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoxu Han","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079173360","display_name":"Guang Kou","orcid":"https://orcid.org/0000-0001-7224-1274"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guang Kou","raw_affiliation_strings":["Artificial Intelligence Research Center, Defense Innovation Institute, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7224-1274","affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Center, Defense Innovation Institute, Beijing, China","institution_ids":["https://openalex.org/I4210100255"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100425878","display_name":"Haoyu Zhang","orcid":"https://orcid.org/0000-0001-5070-7547"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoyu Zhang","raw_affiliation_strings":["Artificial Intelligence Research Center, Defense Innovation Institute, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Center, Defense Innovation Institute, Beijing, China","institution_ids":["https://openalex.org/I4210100255"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101535965","display_name":"Xueyi Liu","orcid":"https://orcid.org/0000-0002-8022-0761"},"institutions":[{"id":"https://openalex.org/I55538621","display_name":"China Jiliang University","ror":"https://ror.org/05v1y0t93","country_code":"CN","type":"education","lineage":["https://openalex.org/I55538621"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueyi Liu","raw_affiliation_strings":["College of Science, China Jiliang University, Hangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Science, China Jiliang University, Hangzhou, China","institution_ids":["https://openalex.org/I55538621"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029551265","display_name":"Yefei Bai","orcid":"https://orcid.org/0000-0003-3323-3348"},"institutions":[{"id":"https://openalex.org/I31847773","display_name":"Zhejiang Ocean University","ror":"https://ror.org/03mys6533","country_code":"CN","type":"education","lineage":["https://openalex.org/I31847773"]},{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yefei Bai","raw_affiliation_strings":["Ocean College, Zhejiang University, Zhoushan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ocean College, Zhejiang University, Zhoushan, China","institution_ids":["https://openalex.org/I31847773","https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5079173360"],"corresponding_institution_ids":["https://openalex.org/I4210100255"],"apc_list":{"value":1800,"currency":"USD","value_usd":1800},"apc_paid":{"value":1800,"currency":"USD","value_usd":1800},"fwci":0.2774,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.60340659,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"2022","issue":null,"first_page":"1","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9909999966621399,"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":0.9909999966621399,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9886999726295471,"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/T10057","display_name":"Face and Expression Recognition","score":0.9833999872207642,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.5940248966217041},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.5716493725776672},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5679352283477783},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5538366436958313},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5501959919929504},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42140763998031616},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3701896071434021},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.36391353607177734},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2711050510406494},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.22132456302642822},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20653793215751648}],"concepts":[{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.5940248966217041},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.5716493725776672},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5679352283477783},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5538366436958313},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5501959919929504},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42140763998031616},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3701896071434021},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.36391353607177734},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2711050510406494},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.22132456302642822},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20653793215751648},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1155/2022/8046620","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2022/8046620","pdf_url":"https://downloads.hindawi.com/journals/sp/2022/8046620.pdf","source":{"id":"https://openalex.org/S166774750","display_name":"Scientific Programming","issn_l":"1058-9244","issn":["1058-9244","1875-919X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Programming","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:94b506397d7a47e0b9f2b41547ab5db1","is_oa":true,"landing_page_url":"https://doaj.org/article/94b506397d7a47e0b9f2b41547ab5db1","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Scientific Programming, Vol 2022 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/2022/8046620","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2022/8046620","pdf_url":"https://downloads.hindawi.com/journals/sp/2022/8046620.pdf","source":{"id":"https://openalex.org/S166774750","display_name":"Scientific Programming","issn_l":"1058-9244","issn":["1058-9244","1875-919X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientific Programming","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7099961495","display_name":null,"funder_award_id":"No. 91948303","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8936065553","display_name":null,"funder_award_id":"91948303","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"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4206214475.pdf","grobid_xml":"https://content.openalex.org/works/W4206214475.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W225736130","https://openalex.org/W1673310716","https://openalex.org/W1841961408","https://openalex.org/W2009231757","https://openalex.org/W2017001763","https://openalex.org/W2100495367","https://openalex.org/W2127218421","https://openalex.org/W2130473611","https://openalex.org/W2165232124","https://openalex.org/W2165835468","https://openalex.org/W2187089797","https://openalex.org/W2268194897","https://openalex.org/W2293435807","https://openalex.org/W2295256067","https://openalex.org/W2520037496","https://openalex.org/W2549636757","https://openalex.org/W2789456849","https://openalex.org/W2792802466","https://openalex.org/W2900089459","https://openalex.org/W2921385201","https://openalex.org/W2955505172","https://openalex.org/W2955986943","https://openalex.org/W2992469153","https://openalex.org/W2997574370","https://openalex.org/W3006505613","https://openalex.org/W3007362259","https://openalex.org/W3007826101","https://openalex.org/W3022506809","https://openalex.org/W3097854746","https://openalex.org/W3120740533","https://openalex.org/W3129084361","https://openalex.org/W3168668299","https://openalex.org/W6681330998"],"related_works":["https://openalex.org/W4298130764","https://openalex.org/W2804364458","https://openalex.org/W2393870460","https://openalex.org/W2132641928","https://openalex.org/W4310225030","https://openalex.org/W2090259340","https://openalex.org/W1926736923","https://openalex.org/W2254578859","https://openalex.org/W4284894156","https://openalex.org/W2005266888"],"abstract_inverted_index":{"Density":[0],"peaks":[1,94],"clustering":[2,8,55,95,234],"(DPC)":[3],"is":[4,156,214,236,312],"a":[5,137,225],"well-known":[6],"density-based":[7],"algorithm":[9,250,334],"that":[10,218,331],"can":[11,251,335],"deal":[12],"with":[13,164,245],"nonspherical":[14],"clusters":[15],"well.":[16],"However,":[17],"DPC":[18,61],"has":[19],"high":[20],"computational":[21,82,133,254,339],"complexity":[22,25,255],"and":[23,35,101,121,193,306,341],"space":[24,155],"in":[26,128,151],"calculating":[27],"local":[28],"density":[29,93],"<a:math":[30],"xmlns:a=\"http://www.w3.org/1998/Math/MathML\"":[31],"id=\"M1\">":[32],"<a:mi>\u03c1</a:mi>":[33],"</a:math>":[34],"distance":[36],"<c:math":[37],"xmlns:c=\"http://www.w3.org/1998/Math/MathML\"":[38],"id=\"M2\">":[39],"<c:mi>\u03b4</c:mi>":[40],"</c:math>":[41],",":[42,292],"which":[43,97],"makes":[44],"it":[45],"suitable":[46],"only":[47,70],"for":[48,54,142],"small-scale":[49],"data":[50,68,73,102,110,139,149,203,222,242,317],"sets.":[51],"In":[52,205],"addition,":[53],"high-dimensional":[56,109],"data,":[57],"the":[58,72,86,108,132,143,148,152,159,168,180,201,207,210,220,231,240,253,300,313,332,338,343],"performance":[59],"of":[60,107,200,209,219,302,315],"still":[62],"needs":[63],"to":[64,80,130,175,186,238,277],"be":[65],"improved.":[66],"High-dimensional":[67],"not":[69],"make":[71],"distribution":[74,150],"more":[75,81],"complex":[76],"but":[77],"also":[78],"lead":[79],"overheads.":[83],"To":[84],"address":[85],"above":[87],"issues,":[88],"we":[89,135],"propose":[90,136],"an":[91],"improved":[92],"algorithm,":[96],"combines":[98],"feature":[99,145,154],"reduction":[100],"sampling":[103,140],"strategy.":[104],"Specifically,":[105],"features":[106],"are":[111,172,184],"automatically":[112],"extracted":[113],"by":[114,158],"principal":[115],"component":[116],"analysis":[117],"(PCA),":[118],"auto-encoder":[119],"(AE),":[120],"t-distributed":[122],"stochastic":[123],"neighbor":[124],"embedding":[125],"(t-SNE).":[126],"Next,":[127,179],"order":[129],"reduce":[131,252,337],"overhead,":[134],"novel":[138],"method":[141],"low-dimensional":[144,153],"data.":[146],"Firstly,":[147],"estimated":[157],"Quasi-Monte":[160],"Carlo":[161],"(QMC)":[162],"sequence":[163],"low-discrepancy":[165],"characteristics.":[166],"Then,":[167],"representative":[169],"QMC":[170,182,212,232,304],"points":[171,183,213,233,305],"selected":[173,181,211,303],"according":[174],"their":[176],"cell":[177],"densities.":[178],"used":[185],"calculate":[187],"<e:math":[188],"xmlns:e=\"http://www.w3.org/1998/Math/MathML\"":[189],"id=\"M3\">":[190],"<e:mi>\u03c1</e:mi>":[191],"</e:math>":[192],"<g:math":[194],"xmlns:g=\"http://www.w3.org/1998/Math/MathML\"":[195],"id=\"M4\">":[196],"<g:mi>\u03b4</g:mi>":[197],"</g:math>":[198],"instead":[199],"original":[202,241,316],"points.":[204],"general,":[206],"number":[208,301],"much":[215],"smaller":[216],"than":[217],"initial":[221],"set.":[223,243],"Finally,":[224],"two-stage":[226],"classification":[227],"strategy":[228],"based":[229],"on":[230],"results":[235,329],"proposed":[237,249,333],"classify":[239],"Compared":[244],"current":[246],"works,":[247],"our":[248],"from":[256],"<i:math":[257],"xmlns:i=\"http://www.w3.org/1998/Math/MathML\"":[258],"id=\"M5\">":[259],"<i:mi>O</i:mi>":[260],"<i:mfenced":[261],"open=\"(\"":[262,283],"close=\")\"":[263,284],"separators=\"|\">":[264,285],"<i:mrow>":[265,267,270],"<i:msup>":[266],"<i:mi>n</i:mi>":[268],"</i:mrow>":[269,272,274],"<i:mn>2</i:mn>":[271],"</i:msup>":[273],"</i:mfenced>":[275],"</i:math>":[276],"<n:math":[278],"xmlns:n=\"http://www.w3.org/1998/Math/MathML\"":[279],"id=\"M6\">":[280],"<n:mi>O</n:mi>":[281],"<n:mfenced":[282],"<n:mrow>":[286],"<n:mi>N</n:mi>":[287],"<n:mi>n</n:mi>":[288],"</n:mrow>":[289],"</n:mfenced>":[290],"</n:math>":[291],"where":[293],"<s:math":[294],"xmlns:s=\"http://www.w3.org/1998/Math/MathML\"":[295],"id=\"M7\">":[296],"<s:mi>N</s:mi>":[297],"</s:math>":[298],"denotes":[299],"<u:math":[307],"xmlns:u=\"http://www.w3.org/1998/Math/MathML\"":[308],"id=\"M8\">":[309],"<u:mi>n</u:mi>":[310],"</u:math>":[311],"size":[314],"set,":[318],"typically":[319],"<w:math":[320],"xmlns:w=\"http://www.w3.org/1998/Math/MathML\"":[321],"id=\"M9\">":[322],"<w:mi>N</w:mi>":[323],"<w:mo>\u226a</w:mo>":[324],"<w:mi>n</w:mi>":[325],"</w:math>":[326],".":[327],"Experimental":[328],"demonstrate":[330],"effectively":[336],"overhead":[340],"improve":[342],"model":[344],"performance.":[345]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
