{"id":"https://openalex.org/W4386845186","doi":"https://doi.org/10.1145/3624479","title":"Feature Selection for Efficient Local-to-global Bayesian Network Structure Learning","display_name":"Feature Selection for Efficient Local-to-global Bayesian Network Structure Learning","publication_year":2023,"publication_date":"2023-09-19","ids":{"openalex":"https://openalex.org/W4386845186","doi":"https://doi.org/10.1145/3624479"},"language":"en","primary_location":{"id":"doi:10.1145/3624479","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3624479","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3624479","source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3624479","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100719462","display_name":"Kui Yu","orcid":"https://orcid.org/0000-0003-2442-4572"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kui Yu","raw_affiliation_strings":["Hefei University of Technology, China"],"raw_orcid":"https://orcid.org/0000-0003-2442-4572","affiliations":[{"raw_affiliation_string":"Hefei University of Technology, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088982563","display_name":"Zhaolong Ling","orcid":"https://orcid.org/0000-0003-4812-6676"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaolong Ling","raw_affiliation_strings":["Anhui University, China"],"raw_orcid":"https://orcid.org/0000-0003-4812-6676","affiliations":[{"raw_affiliation_string":"Anhui University, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100383342","display_name":"Lin Liu","orcid":"https://orcid.org/0000-0003-2843-5738"},"institutions":[{"id":"https://openalex.org/I170239107","display_name":"University of South Australia","ror":"https://ror.org/01p93h210","country_code":"AU","type":"education","lineage":["https://openalex.org/I170239107"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Lin Liu","raw_affiliation_strings":["University of South Australia, Australia"],"raw_orcid":"https://orcid.org/0000-0003-2843-5738","affiliations":[{"raw_affiliation_string":"University of South Australia, Australia","institution_ids":["https://openalex.org/I170239107"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100371517","display_name":"Peipei Li","orcid":"https://orcid.org/0000-0001-9142-448X"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peipei Li","raw_affiliation_strings":["Hefei University of Technology, China"],"raw_orcid":"https://orcid.org/0000-0001-9142-448X","affiliations":[{"raw_affiliation_string":"Hefei University of Technology, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100618086","display_name":"Hao Wang","orcid":"https://orcid.org/0009-0009-3916-0822"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Wang","raw_affiliation_strings":["Hefei University of Technology, China"],"raw_orcid":"https://orcid.org/0009-0009-3916-0822","affiliations":[{"raw_affiliation_string":"Hefei University of Technology, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012177739","display_name":"Jiuyong Li","orcid":"https://orcid.org/0000-0002-9023-1878"},"institutions":[{"id":"https://openalex.org/I170239107","display_name":"University of South Australia","ror":"https://ror.org/01p93h210","country_code":"AU","type":"education","lineage":["https://openalex.org/I170239107"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jiuyong Li","raw_affiliation_strings":["University of South Australia, Australia"],"raw_orcid":"https://orcid.org/0000-0002-9023-1878","affiliations":[{"raw_affiliation_string":"University of South Australia, Australia","institution_ids":["https://openalex.org/I170239107"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3088,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.84023127,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"18","issue":"2","first_page":"1","last_page":"27"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9531999826431274,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9128000140190125,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/markov-blanket","display_name":"Markov blanket","score":0.8304901123046875},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7020987868309021},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6469116806983948},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6357495188713074},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6214801073074341},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.5511958003044128},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4925259053707123},{"id":"https://openalex.org/keywords/conditional-independence","display_name":"Conditional independence","score":0.47043558955192566},{"id":"https://openalex.org/keywords/directed-acyclic-graph","display_name":"Directed acyclic graph","score":0.4541579484939575},{"id":"https://openalex.org/keywords/online-machine-learning","display_name":"Online machine learning","score":0.43064558506011963},{"id":"https://openalex.org/keywords/instance-based-learning","display_name":"Instance-based learning","score":0.4285416603088379},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4284496307373047},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.42825931310653687},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.33875975012779236},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.3361431360244751},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32840871810913086},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2530374526977539},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.1813676655292511}],"concepts":[{"id":"https://openalex.org/C123867240","wikidata":"https://www.wikidata.org/wiki/Q3001792","display_name":"Markov blanket","level":5,"score":0.8304901123046875},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7020987868309021},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6469116806983948},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6357495188713074},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6214801073074341},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.5511958003044128},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4925259053707123},{"id":"https://openalex.org/C79772020","wikidata":"https://www.wikidata.org/wiki/Q5159264","display_name":"Conditional independence","level":2,"score":0.47043558955192566},{"id":"https://openalex.org/C74197172","wikidata":"https://www.wikidata.org/wiki/Q1195339","display_name":"Directed acyclic graph","level":2,"score":0.4541579484939575},{"id":"https://openalex.org/C115903097","wikidata":"https://www.wikidata.org/wiki/Q7094097","display_name":"Online machine learning","level":3,"score":0.43064558506011963},{"id":"https://openalex.org/C24138899","wikidata":"https://www.wikidata.org/wiki/Q17141258","display_name":"Instance-based learning","level":3,"score":0.4285416603088379},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4284496307373047},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.42825931310653687},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.33875975012779236},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.3361431360244751},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32840871810913086},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2530374526977539},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.1813676655292511},{"id":"https://openalex.org/C189973286","wikidata":"https://www.wikidata.org/wiki/Q176695","display_name":"Markov property","level":4,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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:10.1145/3624479","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3624479","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3624479","source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"},{"id":"pmh:oai:urm_publish:9916812628201831","is_oa":false,"landing_page_url":"https://find.library.unisa.edu.au/discovery/fulldisplay/alma9916812628201831/61USOUTHAUS_INST:ROR","pdf_url":null,"source":{"id":"https://openalex.org/S4306402528","display_name":"UniSA Research Outputs Repository (University of South Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I170239107","host_organization_name":"University of South Australia","host_organization_lineage":["https://openalex.org/I170239107"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3624479","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3624479","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3624479","source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2263702567","display_name":null,"funder_award_id":"62376085","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4473816824","display_name":null,"funder_award_id":"62376087","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6120589624","display_name":null,"funder_award_id":"62306002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6427254828","display_name":null,"funder_award_id":"2020AAA0106100","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G6815705898","display_name":null,"funder_award_id":"62376087, 62306002, 62376085","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/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386845186.pdf","grobid_xml":"https://content.openalex.org/works/W4386845186.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W398859631","https://openalex.org/W1530398305","https://openalex.org/W1615454278","https://openalex.org/W1982634635","https://openalex.org/W1983690667","https://openalex.org/W2013374740","https://openalex.org/W2031779765","https://openalex.org/W2064901349","https://openalex.org/W2099900459","https://openalex.org/W2133091666","https://openalex.org/W2134240743","https://openalex.org/W2143022451","https://openalex.org/W2146531590","https://openalex.org/W2147881172","https://openalex.org/W2151226328","https://openalex.org/W2154053567","https://openalex.org/W2165190832","https://openalex.org/W2295033578","https://openalex.org/W2324228145","https://openalex.org/W2525748243","https://openalex.org/W2611370172","https://openalex.org/W2781935813","https://openalex.org/W2798149936","https://openalex.org/W2925608410","https://openalex.org/W2948579453","https://openalex.org/W2963290226","https://openalex.org/W2964137960","https://openalex.org/W2980507899","https://openalex.org/W2998265369","https://openalex.org/W3086148890","https://openalex.org/W3091533194","https://openalex.org/W4289236186","https://openalex.org/W4302423442","https://openalex.org/W6681517296"],"related_works":["https://openalex.org/W2098239572","https://openalex.org/W184546935","https://openalex.org/W1986633584","https://openalex.org/W3033485676","https://openalex.org/W36398315","https://openalex.org/W3210156800","https://openalex.org/W2429093498","https://openalex.org/W1756896031","https://openalex.org/W2130903752","https://openalex.org/W1571236831"],"abstract_inverted_index":{"Local-to-global":[0],"learning":[1,15,28,55,70,87,93,116,196,215],"approach":[2,94,114,136,144,149,176],"plays":[3],"an":[4,90,129],"essential":[5],"role":[6],"in":[7,41,47,67,76,160,205],"Bayesian":[8],"network":[9],"(BN)":[10],"structure":[11,86,134,140,214],"learning.":[12,141],"Existing":[13],"local-to-global":[14,69,92,138,194],"algorithms":[16,204],"first":[17,101,145],"construct":[18],"the":[19,29,48,74,103,106,125,147,152,161,174,192,198,202,218],"skeleton":[20,153],"of":[21,38,105,120,154],"a":[22,42,63,117,121,155],"DAG":[23],"(directed":[24],"acyclic":[25],"graph)":[26],"by":[27],"MB":[30,52],"(Markov":[31],"blanket)":[32],"or":[33,53,166],"PC":[34,54,118],"(parents":[35],"and":[36,88,109,185,211],"children)":[37],"each":[39],"variable":[40],"dataset,":[43],"then":[44,157],"orient":[45],"edges":[46,159],"skeleton.":[49,162],"However,":[50],"existing":[51],"methods":[56],"are":[57,208],"often":[58],"computationally":[59],"expensive":[60],"especially":[61],"with":[62,83],"large-sized":[64],"BN,":[65],"resulting":[66],"inefficient":[68],"algorithms.":[71,220],"To":[72],"tackle":[73],"problem,":[75],"this":[77,206],"article,":[78],"we":[79,100,127,172],"link":[80],"feature":[81,97,112],"selection":[82,113],"local":[84],"BN":[85,139,195],"develop":[89],"efficient":[91,130,210],"using":[95],"filtering":[96],"selection.":[98],"Specifically,":[99],"analyze":[102],"rationale":[104],"well-known":[107],"Minimum-Redundancy":[108],"Maximum-Relevance":[110],"(MRMR)":[111],"for":[115,169],"set":[119],"variable.":[122],"Based":[123],"on":[124],"analysis,":[126],"propose":[128],"F2SL":[131,143,175],"(feature":[132],"selection-based":[133],"learning)":[135],"to":[137,150,191],"The":[142],"employs":[146],"MRMR":[148],"learn":[151],"DAG,":[156],"orients":[158],"Employing":[163],"independence":[164,183],"tests":[165],"score":[167,188],"functions":[168],"orienting":[170],"edges,":[171],"instantiate":[173],"into":[177],"two":[178],"new":[179],"algorithms,":[180,197],"F2SL-c":[181],"(using":[182,187],"tests)":[184],"F2SL-s":[186],"functions).":[189],"Compared":[190],"state-of-the-art":[193],"experiments":[199],"validated":[200],"that":[201],"proposed":[203],"article":[207],"more":[209],"provide":[212],"competitive":[213],"quality":[216],"than":[217],"compared":[219]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2}],"updated_date":"2026-08-24T07:32:12.397491","created_date":"2023-09-20T00:00:00"}