{"id":"https://openalex.org/W4385220940","doi":"https://doi.org/10.3390/sym15071461","title":"A Novel Algorithm for Merging Bayesian Networks","display_name":"A Novel Algorithm for Merging Bayesian Networks","publication_year":2023,"publication_date":"2023-07-22","ids":{"openalex":"https://openalex.org/W4385220940","doi":"https://doi.org/10.3390/sym15071461"},"language":"en","primary_location":{"id":"doi:10.3390/sym15071461","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym15071461","pdf_url":"https://www.mdpi.com/2073-8994/15/7/1461/pdf?version=1690174376","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"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":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/15/7/1461/pdf?version=1690174376","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021093643","display_name":"Miroslav Vani\u0161","orcid":"https://orcid.org/0000-0002-7589-6206"},"institutions":[{"id":"https://openalex.org/I44504214","display_name":"Czech Technical University in Prague","ror":"https://ror.org/03kqpb082","country_code":"CZ","type":"education","lineage":["https://openalex.org/I44504214"]}],"countries":["CZ"],"is_corresponding":true,"raw_author_name":"Miroslav Vani\u0161","raw_affiliation_strings":["Faculty of Transportation Sciences, Czech Technical University in Prague, 110 00 Prague, Czech Republic"],"raw_orcid":"https://orcid.org/0000-0002-7589-6206","affiliations":[{"raw_affiliation_string":"Faculty of Transportation Sciences, Czech Technical University in Prague, 110 00 Prague, Czech Republic","institution_ids":["https://openalex.org/I44504214"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053098905","display_name":"Zden\u011bk Lokaj","orcid":"https://orcid.org/0000-0002-0624-0430"},"institutions":[{"id":"https://openalex.org/I44504214","display_name":"Czech Technical University in Prague","ror":"https://ror.org/03kqpb082","country_code":"CZ","type":"education","lineage":["https://openalex.org/I44504214"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Zden\u011bk Lokaj","raw_affiliation_strings":["Faculty of Transportation Sciences, Czech Technical University in Prague, 110 00 Prague, Czech Republic"],"raw_orcid":"https://orcid.org/0000-0002-0624-0430","affiliations":[{"raw_affiliation_string":"Faculty of Transportation Sciences, Czech Technical University in Prague, 110 00 Prague, Czech Republic","institution_ids":["https://openalex.org/I44504214"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031243399","display_name":"Martin \u0160rot\u00fd\u0159","orcid":"https://orcid.org/0000-0003-0049-4381"},"institutions":[{"id":"https://openalex.org/I44504214","display_name":"Czech Technical University in Prague","ror":"https://ror.org/03kqpb082","country_code":"CZ","type":"education","lineage":["https://openalex.org/I44504214"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Martin \u0160rot\u00fd\u0159","raw_affiliation_strings":["Faculty of Transportation Sciences, Czech Technical University in Prague, 110 00 Prague, Czech Republic"],"raw_orcid":"https://orcid.org/0000-0003-0049-4381","affiliations":[{"raw_affiliation_string":"Faculty of Transportation Sciences, Czech Technical University in Prague, 110 00 Prague, Czech Republic","institution_ids":["https://openalex.org/I44504214"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5021093643"],"corresponding_institution_ids":["https://openalex.org/I44504214"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":1.5337,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.86045441,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"15","issue":"7","first_page":"1461","last_page":"1461"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9984999895095825,"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":0.9984999895095825,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.98089998960495,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9695000052452087,"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/computer-science","display_name":"Computer science","score":0.8071537017822266},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.6514737606048584},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5702962875366211},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5537124276161194},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5258926749229431},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4482194185256958},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4417971968650818},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4331498146057129},{"id":"https://openalex.org/keywords/czech","display_name":"Czech","score":0.4131307303905487},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41031110286712646}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8071537017822266},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.6514737606048584},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5702962875366211},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5537124276161194},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5258926749229431},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4482194185256958},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4417971968650818},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4331498146057129},{"id":"https://openalex.org/C2777842544","wikidata":"https://www.wikidata.org/wiki/Q9056","display_name":"Czech","level":2,"score":0.4131307303905487},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41031110286712646},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/sym15071461","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym15071461","pdf_url":"https://www.mdpi.com/2073-8994/15/7/1461/pdf?version=1690174376","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"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":"Symmetry","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:6913b70165f74b7d814c4cbd569a2ba0","is_oa":true,"landing_page_url":"https://doaj.org/article/6913b70165f74b7d814c4cbd569a2ba0","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry, Vol 15, Iss 7, p 1461 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2073-8994/15/7/1461/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/sym15071461","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":"Symmetry; Volume 15; Issue 7; Pages: 1461","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/sym15071461","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym15071461","pdf_url":"https://www.mdpi.com/2073-8994/15/7/1461/pdf?version=1690174376","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"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":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.75}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309972","display_name":"\u010cesk\u00e9 Vysok\u00e9 U\u010den\u00ed Technick\u00e9 v Praze","ror":"https://ror.org/03kqpb082"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385220940.pdf"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W1535430927","https://openalex.org/W1822300807","https://openalex.org/W1987205573","https://openalex.org/W2031583116","https://openalex.org/W2049633694","https://openalex.org/W2100805904","https://openalex.org/W2118382442","https://openalex.org/W2135293965","https://openalex.org/W2142635246","https://openalex.org/W2168175751","https://openalex.org/W2501634593","https://openalex.org/W2736160176","https://openalex.org/W2923807584","https://openalex.org/W2947197489","https://openalex.org/W2963290226","https://openalex.org/W3191585256","https://openalex.org/W4251708881","https://openalex.org/W4302423442","https://openalex.org/W4360869630"],"related_works":["https://openalex.org/W1485297680","https://openalex.org/W2782410293","https://openalex.org/W305958151","https://openalex.org/W2724504120","https://openalex.org/W2614400517","https://openalex.org/W2939805521","https://openalex.org/W4360856886","https://openalex.org/W4378675964","https://openalex.org/W578757760","https://openalex.org/W2547738291"],"abstract_inverted_index":{"The":[0,26,69,86],"article":[1],"presents":[2],"a":[3,23,37,100],"novel":[4],"algorithm":[5,27,70,97,121,137],"for":[6],"merging":[7],"Bayesian":[8,148],"networks":[9],"generated":[10],"by":[11,65],"different":[12,84,143],"methods,":[13],"such":[14],"as":[15,63],"expert":[16,95],"knowledge":[17,146],"and":[18,40,54,72,96,103,126],"data-driven":[19],"approaches,":[20],"while":[21],"leveraging":[22],"symmetry-based":[24],"approach.":[25],"combines":[28],"the":[29,51,77,94,107,112,120,128,135,139],"strengths":[30],"of":[31,106,130,141,145],"each":[32],"input":[33],"network":[34,149],"to":[35,122],"create":[36],"more":[38,101],"comprehensive":[39,102],"accurate":[41,104],"network.":[42],"Evaluations":[43],"on":[44,56,118],"traffic":[45],"accident":[46],"data":[47],"from":[48,92],"Prague":[49],"in":[50,111,147],"Czech":[52],"Republic":[53],"accidents":[55],"railway":[57],"crossings":[58],"demonstrate":[59],"superior":[60],"predictive":[61],"performance,":[62],"measured":[64],"prediction":[66],"error":[67],"metric.":[68],"identifies":[71],"incorporates":[73],"symmetric":[74],"nodes":[75,90],"into":[76],"final":[78],"network,":[79,88],"ensuring":[80],"consistent":[81],"representations":[82],"across":[83],"methods.":[85],"merged":[87],"incorporating":[89],"selected":[91],"both":[93],"networks,":[98],"provides":[99],"representation":[105],"relationships":[108],"among":[109],"variables":[110],"dataset.":[113],"Future":[114],"research":[115],"could":[116],"focus":[117],"extending":[119],"deal":[123],"with":[124],"cycles":[125],"improving":[127],"handling":[129],"conditional":[131],"probability":[132],"tables.":[133],"Overall,":[134],"proposed":[136],"demonstrates":[138],"effectiveness":[140],"combining":[142],"sources":[144],"modeling.":[150]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}
