{"id":"https://openalex.org/W2888605635","doi":"https://doi.org/10.3390/e20080620","title":"A Hybrid Structure Learning Algorithm for Bayesian Network Using Experts\u2019 Knowledge","display_name":"A Hybrid Structure Learning Algorithm for Bayesian Network Using Experts\u2019 Knowledge","publication_year":2018,"publication_date":"2018-08-20","ids":{"openalex":"https://openalex.org/W2888605635","doi":"https://doi.org/10.3390/e20080620","mag":"2888605635","pmid":"https://pubmed.ncbi.nlm.nih.gov/33265709"},"language":"en","primary_location":{"id":"doi:10.3390/e20080620","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e20080620","pdf_url":"https://www.mdpi.com/1099-4300/20/8/620/pdf","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"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":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/20/8/620/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100602276","display_name":"Hongru Li","orcid":"https://orcid.org/0000-0003-4700-962X"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongru Li","raw_affiliation_strings":["Information Science and Engineering, Northeastern University, P.O. Box 135, No. 11 St. 3, Wenhua Road, Heping District, Shenyang 110819, China"],"raw_orcid":"https://orcid.org/0000-0003-4700-962X","affiliations":[{"raw_affiliation_string":"Information Science and Engineering, Northeastern University, P.O. Box 135, No. 11 St. 3, Wenhua Road, Heping District, Shenyang 110819, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027618460","display_name":"Huiping Guo","orcid":"https://orcid.org/0000-0002-6695-2982"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Huiping Guo","raw_affiliation_strings":["Information Science and Engineering, Northeastern University, P.O. Box 135, No. 11 St. 3, Wenhua Road, Heping District, Shenyang 110819, China"],"raw_orcid":"https://orcid.org/0000-0002-6695-2982","affiliations":[{"raw_affiliation_string":"Information Science and Engineering, Northeastern University, P.O. Box 135, No. 11 St. 3, Wenhua Road, Heping District, Shenyang 110819, China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5027618460"],"corresponding_institution_ids":["https://openalex.org/I9224756"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.8448,"has_fulltext":true,"cited_by_count":17,"citation_normalized_percentile":{"value":0.80534938,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"20","issue":"8","first_page":"620","last_page":"620"},"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9581999778747559,"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/T10050","display_name":"Multi-Criteria Decision Making","score":0.9472000002861023,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.730480432510376},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.7139976620674133},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5780897736549377},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5688677430152893},{"id":"https://openalex.org/keywords/wake-sleep-algorithm","display_name":"Wake-sleep algorithm","score":0.46016642451286316},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.42656582593917847},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.21208456158638}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.730480432510376},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.7139976620674133},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5780897736549377},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5688677430152893},{"id":"https://openalex.org/C17061570","wikidata":"https://www.wikidata.org/wiki/Q7960888","display_name":"Wake-sleep algorithm","level":4,"score":0.46016642451286316},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42656582593917847},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.21208456158638},{"id":"https://openalex.org/C117765406","wikidata":"https://www.wikidata.org/wiki/Q5362437","display_name":"Generalization error","level":3,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/e20080620","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e20080620","pdf_url":"https://www.mdpi.com/1099-4300/20/8/620/pdf","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"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":"Entropy","raw_type":"journal-article"},{"id":"pmid:33265709","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33265709","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":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:099d1e893eef47c3b4fcbe442f3d7d9b","is_oa":true,"landing_page_url":"https://doaj.org/article/099d1e893eef47c3b4fcbe442f3d7d9b","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":"Entropy, Vol 20, Iss 8, p 620 (2018)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1099-4300/20/8/620/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/e20080620","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":"Entropy","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:7513154","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7513154","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e20080620","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e20080620","pdf_url":"https://www.mdpi.com/1099-4300/20/8/620/pdf","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"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":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4233788764","display_name":"\u6d41\u7a0b\u5de5\u4e1a\u4f18\u5316\u63a7\u5236\u4e0e\u5b89\u5168\u8fd0\u884c\u77e5\u8bc6\u81ea\u52a8\u5316\u7cfb\u7edf\u8bbe\u8ba1\u65b9\u6cd5\u4e0e\u5e94\u7528\u7814\u7a76","funder_award_id":"61533007","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/W2888605635.pdf","grobid_xml":"https://content.openalex.org/works/W2888605635.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W793342979","https://openalex.org/W1517993545","https://openalex.org/W1975856432","https://openalex.org/W1978267297","https://openalex.org/W1985026895","https://openalex.org/W2000621750","https://openalex.org/W2031111980","https://openalex.org/W2055037429","https://openalex.org/W2057384819","https://openalex.org/W2076753758","https://openalex.org/W2108468952","https://openalex.org/W2137651144","https://openalex.org/W2143451896","https://openalex.org/W2165190832","https://openalex.org/W2169288958","https://openalex.org/W2317613476","https://openalex.org/W2467634557","https://openalex.org/W2505999616","https://openalex.org/W2529268610","https://openalex.org/W2556112123","https://openalex.org/W2560486644","https://openalex.org/W4238177049","https://openalex.org/W6680484008","https://openalex.org/W6681091204"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4313488044","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W3209574120"],"abstract_inverted_index":{"Bayesian":[0,24,51],"network":[1,25,138],"structure":[2,26,54,70,110,139,166],"learning":[3,111,167],"from":[4],"data":[5],"has":[6],"been":[7],"proved":[8],"to":[9,134],"be":[10],"a":[11,98,113],"NP-hard":[12],"(Non-deterministic":[13],"Polynomial-hard)":[14],"problem.":[15],"An":[16],"effective":[17],"method":[18,100,162],"of":[19,23,32,101,115,120],"improving":[20],"the":[21,45,57,65,73,79,92,128,142,165],"accuracy":[22],"is":[27,85],"using":[28,34,102],"experts'":[29,37,105,121],"knowledge":[30,38,75,106,122],"instead":[31],"only":[33,72],"data.":[35],"Some":[36],"(named":[39,59],"here":[40,60],"explicit":[41,74],"knowledge)":[42,62],"can":[43,163],"make":[44],"causal":[46],"relationship":[47],"between":[48],"nodes":[49],"in":[50,91],"Networks":[52],"(BN)":[53],"clear,":[55],"while":[56],"others":[58],"vague":[61,80],"cannot.":[63],"In":[64],"previous":[66],"algorithms":[67],"for":[68],"BN":[69],"learning,":[71],"was":[76,83],"used,":[77],"but":[78],"knowledge,":[81],"which":[82],"ignored,":[84],"also":[86],"valuable":[87],"and":[88,125,140,151],"often":[89],"exists":[90],"real":[93],"world.":[94],"Therefore":[95],"we":[96,146],"propose":[97],"new":[99],"more":[103],"comprehensive":[104],"based":[107],"on":[108],"hybrid":[109,129],"algorithm,":[112],"kind":[114],"two-stage":[116],"algorithm.":[117,130],"Two":[118],"types":[119],"are":[123],"defined":[124],"incorporated":[126],"into":[127,154],"We":[131],"formulate":[132],"rules":[133],"generate":[135],"better":[136],"initial":[137],"improve":[141,164],"scoring":[143],"function.":[144],"Furthermore,":[145],"take":[147],"expert":[148],"level":[149],"difference":[150],"opinion":[152],"conflict":[153],"account.":[155],"Experimental":[156],"results":[157],"show":[158],"that":[159],"our":[160],"proposed":[161],"performance.":[168]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2}],"updated_date":"2026-06-06T09:05:17.133730","created_date":"2025-10-10T00:00:00"}
