{"id":"https://openalex.org/W2980253934","doi":"https://doi.org/10.3390/s19204400","title":"PEnBayes: A Multi-Layered Ensemble Approach for Learning Bayesian Network Structure from Big Data","display_name":"PEnBayes: A Multi-Layered Ensemble Approach for Learning Bayesian Network Structure from Big Data","publication_year":2019,"publication_date":"2019-10-11","ids":{"openalex":"https://openalex.org/W2980253934","doi":"https://doi.org/10.3390/s19204400","mag":"2980253934","pmid":"https://pubmed.ncbi.nlm.nih.gov/31614544"},"language":"en","primary_location":{"id":"doi:10.3390/s19204400","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s19204400","pdf_url":"https://www.mdpi.com/1424-8220/19/20/4400/pdf?version=1570859575","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","datacite","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/19/20/4400/pdf?version=1570859575","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026602746","display_name":"Yan Tang","orcid":"https://orcid.org/0000-0001-5239-5807"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yan Tang","raw_affiliation_strings":["Data Science and Knowledge Engineering Laboratory, College of Computer and Information, Hohai University, Nanjing 210036, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science and Knowledge Engineering Laboratory, College of Computer and Information, Hohai University, Nanjing 210036, China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101750217","display_name":"Jianwu Wang","orcid":"https://orcid.org/0000-0002-9933-1170"},"institutions":[{"id":"https://openalex.org/I79272384","display_name":"University of Maryland, Baltimore County","ror":"https://ror.org/02qskvh78","country_code":"US","type":"education","lineage":["https://openalex.org/I79272384"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jianwu Wang","raw_affiliation_strings":["Department of Information Systems, University of Maryland, Baltimore County, Baltimore, MD 21250, USA"],"raw_orcid":"https://orcid.org/0000-0002-9933-1170","affiliations":[{"raw_affiliation_string":"Department of Information Systems, University of Maryland, Baltimore County, Baltimore, MD 21250, USA","institution_ids":["https://openalex.org/I79272384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101845660","display_name":"Mai Thanh Thi Nguyen","orcid":"https://orcid.org/0000-0001-8006-4028"},"institutions":[{"id":"https://openalex.org/I181653535","display_name":"San Diego Supercomputer Center","ror":"https://ror.org/04mg3nk07","country_code":"US","type":"facility","lineage":["https://openalex.org/I181653535","https://openalex.org/I36258959"]},{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mai Nguyen","raw_affiliation_strings":["San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA","institution_ids":["https://openalex.org/I181653535","https://openalex.org/I36258959"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028701796","display_name":"\u0130lkay Alt\u0131nta\u015f","orcid":"https://orcid.org/0000-0002-2196-0305"},"institutions":[{"id":"https://openalex.org/I181653535","display_name":"San Diego Supercomputer Center","ror":"https://ror.org/04mg3nk07","country_code":"US","type":"facility","lineage":["https://openalex.org/I181653535","https://openalex.org/I36258959"]},{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ilkay Altintas","raw_affiliation_strings":["San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"San Diego Supercomputer Center, University of California, San Diego, La Jolla, CA 92093, USA","institution_ids":["https://openalex.org/I181653535","https://openalex.org/I36258959"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5026602746","https://openalex.org/A5101750217"],"corresponding_institution_ids":["https://openalex.org/I163340411","https://openalex.org/I79272384"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":1.8355,"has_fulltext":true,"cited_by_count":18,"citation_normalized_percentile":{"value":0.89194408,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"19","issue":"20","first_page":"4400","last_page":"4400"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9822999835014343,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9261999726295471,"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/computer-science","display_name":"Computer science","score":0.7852137088775635},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.7385514378547668},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.6781812310218811},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6683386564254761},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6202589273452759},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.5987077355384827},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5144736766815186},{"id":"https://openalex.org/keywords/data-structure","display_name":"Data structure","score":0.48599156737327576},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.458662211894989},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.45481762290000916},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4440236985683441},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4424270987510681},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.43087872862815857}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7852137088775635},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.7385514378547668},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6781812310218811},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6683386564254761},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6202589273452759},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.5987077355384827},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5144736766815186},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.48599156737327576},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.458662211894989},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.45481762290000916},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4440236985683441},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4424270987510681},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.43087872862815857},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":7,"locations":[{"id":"doi:10.3390/s19204400","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s19204400","pdf_url":"https://www.mdpi.com/1424-8220/19/20/4400/pdf?version=1570859575","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:31614544","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31614544","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":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:mdsoar.org:11603/31607","is_oa":true,"landing_page_url":"http://hdl.handle.net/11603/31607","pdf_url":"https://mdsoar.org/bitstreams/62919da8-9a0a-4a08-995d-7d70f94048b0/download","source":{"id":"https://openalex.org/S4306402556","display_name":"Maryland Shared Open Access Repository (USMAI Consortium)","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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:4776f69fb7ed4ea2bd6d8e9eb640187e","is_oa":true,"landing_page_url":"https://doaj.org/article/4776f69fb7ed4ea2bd6d8e9eb640187e","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":"Sensors, Vol 19, Iss 20, p 4400 (2019)","raw_type":"article"},{"id":"pmh:oai:europepmc.org:5830652","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6832728","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},{"id":"pmh:oai:mdpi.com:/1424-8220/19/20/4400/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/s19204400","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors","raw_type":"Text"},{"id":"doi:10.13016/m2ofze-u8yd","is_oa":true,"landing_page_url":"https://doi.org/10.13016/m2ofze-u8yd","pdf_url":null,"source":{"id":"https://openalex.org/S4306402644","display_name":"Digital Repository at the University of Maryland (University of Maryland College Park)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66946132","host_organization_name":"University of Maryland, College Park","host_organization_lineage":["https://openalex.org/I66946132"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"doi:10.3390/s19204400","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s19204400","pdf_url":"https://www.mdpi.com/1424-8220/19/20/4400/pdf?version=1570859575","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6446220806","display_name":null,"funder_award_id":"2017YFC0405805-04","funder_id":"https://openalex.org/F4320335774","funder_display_name":"Key Technologies Research and Development Program"},{"id":"https://openalex.org/G8549459522","display_name":null,"funder_award_id":"2017YFC0405805","funder_id":"https://openalex.org/F4320335774","funder_display_name":"Key Technologies Research and Development Program"}],"funders":[{"id":"https://openalex.org/F4320335774","display_name":"Key Technologies Research and Development Program","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1807198","https://openalex.org/W1505477995","https://openalex.org/W1517993545","https://openalex.org/W1702884067","https://openalex.org/W1801737117","https://openalex.org/W1861377444","https://openalex.org/W1899161704","https://openalex.org/W1935979693","https://openalex.org/W1978267297","https://openalex.org/W1979268377","https://openalex.org/W1983690667","https://openalex.org/W1983833794","https://openalex.org/W1990361999","https://openalex.org/W2003017496","https://openalex.org/W2022828327","https://openalex.org/W2029237784","https://openalex.org/W2045499798","https://openalex.org/W2060316012","https://openalex.org/W2090950090","https://openalex.org/W2099900459","https://openalex.org/W2115428292","https://openalex.org/W2123663722","https://openalex.org/W2128088446","https://openalex.org/W2154733731","https://openalex.org/W2155806188","https://openalex.org/W2159080219","https://openalex.org/W2161205483","https://openalex.org/W2161642932","https://openalex.org/W2165190832","https://openalex.org/W2166685976","https://openalex.org/W2170112109","https://openalex.org/W2188934299","https://openalex.org/W2224805104","https://openalex.org/W2406048721","https://openalex.org/W2485657344","https://openalex.org/W2501634593","https://openalex.org/W2521609604","https://openalex.org/W2605026288","https://openalex.org/W2636249423","https://openalex.org/W2793565101","https://openalex.org/W2798060819","https://openalex.org/W2888580379","https://openalex.org/W2899636728","https://openalex.org/W2921100033","https://openalex.org/W2969364596","https://openalex.org/W3020913839","https://openalex.org/W3191596906","https://openalex.org/W4212883601","https://openalex.org/W4302423442","https://openalex.org/W6631593755","https://openalex.org/W6799706721"],"related_works":["https://openalex.org/W2989490741","https://openalex.org/W3092506759","https://openalex.org/W2367545121","https://openalex.org/W4248881655","https://openalex.org/W2482165163","https://openalex.org/W3010890513","https://openalex.org/W120741642","https://openalex.org/W138569904","https://openalex.org/W2390914021","https://openalex.org/W2389417819"],"abstract_inverted_index":{"Discovering":[0],"the":[1,41,58,145,184,194,199,203],"Bayesian":[2,132],"network":[3,133,191],"(BN)":[4],"structure":[5,44,56,87,159,178,192,195],"from":[6,30,57,84,214],"big":[7,27,50,60,153,207],"datasets":[8],"containing":[9],"rich":[10],"causal":[11],"relationships":[12],"is":[13,62,77,98],"becoming":[14],"increasingly":[15],"valuable":[16],"for":[17,155],"modeling":[18],"and":[19,36,149,218,237],"reasoning":[20],"under":[21],"uncertainties":[22],"in":[23,69,170],"many":[24],"areas":[25],"with":[26,137,234,241],"data":[28,140,208,213],"gathered":[29],"sensors":[31],"due":[32,71],"to":[33,72,80,90],"high":[34],"volume":[35],"fast":[37,156],"veracity.":[38],"Most":[39],"of":[40,101,166],"current":[42],"BN":[43,55,86,109,115,168,186],"learning":[45,53,88,94,126,244],"algorithms":[46,89],"have":[47],"shortcomings":[48],"facing":[49],"data.":[51],"First,":[52],"a":[54,82,99,112,123,152,164,173,189,229],"entire":[59],"dataset":[61,154],"an":[63,102,138],"expensive":[64],"task":[65],"which":[66],"often":[67],"ends":[68],"failure":[70],"memory":[73],"constraints.":[74],"Second,":[75],"it":[76],"quite":[78],"difficult":[79],"select":[81],"learner":[83],"numerous":[85],"consistently":[91],"achieve":[92],"good":[93],"accuracy.":[95],"Lastly,":[96,181],"there":[97],"lack":[100],"intelligent":[103],"method":[104,197],"that":[105,143,226],"merges":[106,183],"separately":[107],"learned":[108],"structures":[110],"into":[111,188],"well":[113],"structured":[114],"network.":[116],"To":[117],"address":[118],"these":[119],"shortcomings,":[120],"we":[121,205],"introduce":[122],"novel":[124],"parallel":[125,171],"approach":[127],"called":[128],"PEnBayes":[129,135,162,182,227],"(Parallel":[130],"Ensemble-based":[131],"learning).":[134],"starts":[136],"adaptive":[139],"preprocessing":[141],"phase":[142],"calculates":[144],"Appropriate":[146],"Learning":[147],"Size":[148],"intelligently":[150],"divides":[151],"distributed":[157],"local":[158,167,185],"learning.":[160],"Then,":[161],"learns":[163],"collection":[165],"Structures":[169,187],"using":[172,193],"two-layered":[174],"weighted":[175],"adjacent":[176],"matrix-based":[177],"ensemble":[179,196],"method.":[180],"global":[190,200],"at":[198],"layer.":[201],"For":[202],"experiment,":[204],"generate":[206],"sets":[209],"by":[210],"simulating":[211],"sensor":[212],"patient":[215],"monitoring,":[216],"transportation,":[217],"disease":[219],"diagnosis":[220],"domains.":[221],"The":[222],"Experimental":[223],"results":[224,239],"show":[225],"achieves":[228],"significantly":[230],"improved":[231],"execution":[232],"performance":[233],"more":[235],"consistent":[236],"stable":[238],"compared":[240],"three":[242],"baseline":[243],"algorithms.":[245]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}