{"id":"https://openalex.org/W4280591200","doi":"https://doi.org/10.1109/tcyb.2022.3169327","title":"OPP-Miner: Order-Preserving Sequential Pattern Mining for Time Series","display_name":"OPP-Miner: Order-Preserving Sequential Pattern Mining for Time Series","publication_year":2022,"publication_date":"2022-05-13","ids":{"openalex":"https://openalex.org/W4280591200","doi":"https://doi.org/10.1109/tcyb.2022.3169327","pmid":"https://pubmed.ncbi.nlm.nih.gov/35560099"},"language":"en","primary_location":{"id":"doi:10.1109/tcyb.2022.3169327","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2022.3169327","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"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 Cybernetics","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/A5034766193","display_name":"Youxi Wu","orcid":"https://orcid.org/0000-0001-5314-3468"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Youxi Wu","raw_affiliation_strings":["School of Artificial Intelligence and the Hebei Key Laboratory of Big Data Computing, Hebei University of Technology, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence and the Hebei Key Laboratory of Big Data Computing, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100620325","display_name":"Qian Hu","orcid":"https://orcid.org/0000-0001-7831-899X"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qian Hu","raw_affiliation_strings":["School of Artificial Intelligence, Hebei University of Technology, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100380302","display_name":"Yan Li","orcid":"https://orcid.org/0000-0002-1126-9772"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Li","raw_affiliation_strings":["School of Economics and Management, Hebei University of Technology, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Economics and Management, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032245448","display_name":"Lei Guo","orcid":"https://orcid.org/0000-0003-3427-8222"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Guo","raw_affiliation_strings":["State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084641325","display_name":"Xingquan Zhu","orcid":"https://orcid.org/0000-0003-4129-9611"},"institutions":[{"id":"https://openalex.org/I63772739","display_name":"Florida Atlantic University","ror":"https://ror.org/05p8w6387","country_code":"US","type":"education","lineage":["https://openalex.org/I63772739"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xingquan Zhu","raw_affiliation_strings":["Department of Computer, Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer, Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, USA","institution_ids":["https://openalex.org/I63772739"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080738591","display_name":"Xindong Wu","orcid":"https://orcid.org/0000-0003-2396-1704"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]},{"id":"https://openalex.org/I4401726980","display_name":"Mininglamp (China)","ror":"https://ror.org/04tb90x61","country_code":"CN","type":"company","lineage":["https://openalex.org/I4401726980"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xindong Wu","raw_affiliation_strings":["Key Laboratory of Knowledge Engineering With Big Data (Ministry of Education of China), Hefei University of Technology, Hefei, China","Mininglamp Academy of Sciences, Mininglamp Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Knowledge Engineering With Big Data (Ministry of Education of China), Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]},{"raw_affiliation_string":"Mininglamp Academy of Sciences, Mininglamp Technology, Beijing, China","institution_ids":["https://openalex.org/I4401726980"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5034766193"],"corresponding_institution_ids":["https://openalex.org/I184843921"],"apc_list":null,"apc_paid":null,"fwci":10.8407,"has_fulltext":false,"cited_by_count":36,"citation_normalized_percentile":{"value":0.9836019,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"53","issue":"5","first_page":"3288","last_page":"3300"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11106","display_name":"Data Management and Algorithms","score":0.9872999787330627,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/series","display_name":"Series (stratigraphy)","score":0.7700742483139038},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.649276614189148},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6156758666038513},{"id":"https://openalex.org/keywords/discretization","display_name":"Discretization","score":0.6044107675552368},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5944574475288391},{"id":"https://openalex.org/keywords/order","display_name":"Order (exchange)","score":0.5273888111114502},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5190554261207581},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5133939981460571},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.46996328234672546},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.45713862776756287},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4520067572593689},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.44718044996261597},{"id":"https://openalex.org/keywords/pattern-matching","display_name":"Pattern matching","score":0.4134313762187958},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2946245074272156},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.241334468126297},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2371414303779602},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1127079427242279}],"concepts":[{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.7700742483139038},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.649276614189148},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6156758666038513},{"id":"https://openalex.org/C73000952","wikidata":"https://www.wikidata.org/wiki/Q17007827","display_name":"Discretization","level":2,"score":0.6044107675552368},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5944574475288391},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.5273888111114502},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5190554261207581},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5133939981460571},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.46996328234672546},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.45713862776756287},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4520067572593689},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.44718044996261597},{"id":"https://openalex.org/C68859911","wikidata":"https://www.wikidata.org/wiki/Q1503724","display_name":"Pattern matching","level":2,"score":0.4134313762187958},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2946245074272156},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.241334468126297},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2371414303779602},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1127079427242279},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tcyb.2022.3169327","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2022.3169327","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"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 Cybernetics","raw_type":"journal-article"},{"id":"pmid:35560099","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35560099","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 cybernetics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.8199999928474426,"display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G1450990713","display_name":null,"funder_award_id":"91746209","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1685043895","display_name":null,"funder_award_id":"E2020202033","funder_id":"https://openalex.org/F4320322163","funder_display_name":"Natural Science Foundation of Hebei Province"},{"id":"https://openalex.org/G2086940843","display_name":null,"funder_award_id":"52077056","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5992500747","display_name":null,"funder_award_id":"61976240","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7447526626","display_name":null,"funder_award_id":"2016YFB1000901","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G7820485183","display_name":null,"funder_award_id":"F2020202013","funder_id":"https://openalex.org/F4320322163","funder_display_name":"Natural Science Foundation of Hebei Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322163","display_name":"Natural Science Foundation of Hebei Province","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W1515650950","https://openalex.org/W1565746575","https://openalex.org/W1907451052","https://openalex.org/W1968655052","https://openalex.org/W1974814405","https://openalex.org/W1981211771","https://openalex.org/W1983595396","https://openalex.org/W2017575427","https://openalex.org/W2029955663","https://openalex.org/W2064118757","https://openalex.org/W2077578233","https://openalex.org/W2105550931","https://openalex.org/W2107633943","https://openalex.org/W2120043163","https://openalex.org/W2159410589","https://openalex.org/W2163336863","https://openalex.org/W2164274563","https://openalex.org/W2291052887","https://openalex.org/W2360114527","https://openalex.org/W2512805377","https://openalex.org/W2550062805","https://openalex.org/W2562596959","https://openalex.org/W2567142519","https://openalex.org/W2754880706","https://openalex.org/W2758905143","https://openalex.org/W2758942695","https://openalex.org/W2762034449","https://openalex.org/W2799813871","https://openalex.org/W2801870222","https://openalex.org/W2830579703","https://openalex.org/W2894761743","https://openalex.org/W2907464021","https://openalex.org/W2908474881","https://openalex.org/W2909794169","https://openalex.org/W2913287122","https://openalex.org/W2994717931","https://openalex.org/W3001790167","https://openalex.org/W3007713653","https://openalex.org/W3013769259","https://openalex.org/W3021053579","https://openalex.org/W3036726025","https://openalex.org/W3041954559","https://openalex.org/W3046961612","https://openalex.org/W3091751937","https://openalex.org/W3169551350","https://openalex.org/W3177259441","https://openalex.org/W3191240255","https://openalex.org/W3203005438","https://openalex.org/W3210621838","https://openalex.org/W3210712593","https://openalex.org/W4200373901","https://openalex.org/W4206197977","https://openalex.org/W4210655911","https://openalex.org/W4210775951","https://openalex.org/W4210951666","https://openalex.org/W4308222521","https://openalex.org/W6633774736","https://openalex.org/W6680970901","https://openalex.org/W6688615434"],"related_works":["https://openalex.org/W2006251942","https://openalex.org/W2364741597","https://openalex.org/W1492103595","https://openalex.org/W1864774435","https://openalex.org/W946352265","https://openalex.org/W3020787026","https://openalex.org/W2943461603","https://openalex.org/W3210429500","https://openalex.org/W3217252310","https://openalex.org/W4286894112"],"abstract_inverted_index":{"Traditional":[0],"sequential":[1,33,85],"pattern":[2,34,86,169],"mining":[3,35],"methods":[4,36],"were":[5],"designed":[6],"for":[7],"symbolic":[8,26,98],"sequence.":[9],"As":[10],"a":[11,18,80,122],"collection":[12],"of":[13,52,61,108,114,121,132],"measurements":[14],"in":[15,41,147,204,218],"chronological":[16],"order,":[17],"time":[19,42,62,95,109,123,136,148,205],"series":[20,96,124,149],"needs":[21],"to":[22,37,93,143,162,172,184],"be":[23,126,237],"discretized":[24],"into":[25,97],"sequences,":[27],"and":[28,100,159,166,227,234],"then":[29],"users":[30],"can":[31,125,199,236],"apply":[32],"discover":[38,201],"interesting":[39],"patterns":[40,102,146],"series.":[43,110,137,206],"The":[44,232],"discretization":[45],"will":[46],"not":[47,91,195],"only":[48,196],"cause":[49],"the":[50,59,67,105,119,129,133,151,157,164,168,178,186,220,229],"loss":[51],"some":[53],"important":[54],"information,":[55],"which":[56,89],"partially":[57],"destroys":[58],"continuity":[60],"series,":[63],"but":[64,198],"also":[65,182,200],"ignore":[66],"order":[68,106,131],"relations":[69,107],"between":[70],"time-series":[71],"values.":[72],"Inspired":[73],"by":[74,128,223],"order-preserving":[75,84],"matching,":[76],"this":[77],"article":[78],"explores":[79],"new":[81],"method":[82],"called":[83],"(OPP)":[87],"mining,":[88],"does":[90],"need":[92],"discretize":[94],"sequences":[99],"represents":[101],"based":[103],"on":[104],"An":[111],"inherent":[112],"advantage":[113],"such":[115],"representation":[116],"is":[117,194],"that":[118,192,212],"trend":[120],"represented":[127],"relative":[130,153],"values":[134],"underneath":[135],"We":[138],"propose":[139],"an":[140],"OPP-Miner":[141,155,193],"algorithm":[142],"mine":[144],"frequent":[145],"with":[150],"same":[152],"order.":[154],"employs":[156],"filtration":[158],"verification":[160],"strategies":[161],"calculate":[163],"support":[165],"uses":[167],"fusion":[170],"strategy":[171],"generate":[173],"candidate":[174],"patterns.":[175],"To":[176],"compress":[177],"result":[179],"set,":[180],"we":[181],"study":[183],"find":[185],"maximal":[187],"OPPs.":[188],"Experimental":[189],"results":[190],"validate":[191],"efficient":[197],"similar":[202],"subsequences":[203],"In":[207],"addition,":[208],"case":[209],"studies":[210],"show":[211],"our":[213],"algorithms":[214,233],"have":[215],"high":[216],"utility":[217],"analyzing":[219],"COVID-19":[221],"epidemic":[222],"identifying":[224],"critical":[225],"trends":[226],"improve":[228],"clustering":[230],"performance.":[231],"data":[235],"downloaded":[238],"from":[239],"https://github.com/wuc567/Pattern-Mining/tree/master/OPP-Miner.":[240]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":4}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}
