{"id":"https://openalex.org/W4389731194","doi":"https://doi.org/10.3233/faia231085","title":"Learning of Bounded Treewidth Bayesian Networks via A-kg","display_name":"Learning of Bounded Treewidth Bayesian Networks via A-kg","publication_year":2023,"publication_date":"2023-12-12","ids":{"openalex":"https://openalex.org/W4389731194","doi":"https://doi.org/10.3233/faia231085"},"language":"en","primary_location":{"id":"doi:10.3233/faia231085","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3233/faia231085","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA231085","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA231085","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108885852","display_name":"Ronghao Su","orcid":null},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]},{"id":"https://openalex.org/I4210134929","display_name":"Jilin Province Science and Technology Department","ror":"https://ror.org/049x38272","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210134929"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ronghao Su","raw_affiliation_strings":["College of Computer Science and Technology, Jilin University, Changchun, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Jilin University, Changchun, China","institution_ids":["https://openalex.org/I4210134929","https://openalex.org/I194450716"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101647838","display_name":"Yungang Zhu","orcid":"https://orcid.org/0000-0002-8305-4092"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]},{"id":"https://openalex.org/I4210134929","display_name":"Jilin Province Science and Technology Department","ror":"https://ror.org/049x38272","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210134929"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yungang Zhu","raw_affiliation_strings":["College of Computer Science and Technology, Jilin University, Changchun, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Jilin University, Changchun, China","institution_ids":["https://openalex.org/I4210134929","https://openalex.org/I194450716"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101647838"],"corresponding_institution_ids":["https://openalex.org/I194450716","https://openalex.org/I4210134929"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.46712075,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9991999864578247,"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":0.9991999864578247,"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":0.9641000032424927,"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/T11719","display_name":"Data Quality and Management","score":0.9524999856948853,"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/treewidth","display_name":"Treewidth","score":0.9240645170211792},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.8047672510147095},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.7094386219978333},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.6957972049713135},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5291869044303894},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5270246267318726},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5038568377494812},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48015087842941284},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.4594403803348541},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.44681575894355774},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3870668411254883},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3667728900909424},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.29086244106292725},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.2546667754650116},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.13586443662643433}],"concepts":[{"id":"https://openalex.org/C132569581","wikidata":"https://www.wikidata.org/wiki/Q5067368","display_name":"Treewidth","level":5,"score":0.9240645170211792},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8047672510147095},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.7094386219978333},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.6957972049713135},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5291869044303894},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5270246267318726},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5038568377494812},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48015087842941284},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4594403803348541},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.44681575894355774},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3870668411254883},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3667728900909424},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.29086244106292725},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.2546667754650116},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.13586443662643433},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.0},{"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/C43517604","wikidata":"https://www.wikidata.org/wiki/Q7144893","display_name":"Pathwidth","level":4,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/faia231085","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3233/faia231085","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA231085","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.3233/faia231085","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3233/faia231085","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA231085","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4389731194.pdf","grobid_xml":"https://content.openalex.org/works/W4389731194.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W1511963917","https://openalex.org/W1530964327","https://openalex.org/W1554371395","https://openalex.org/W1964821516","https://openalex.org/W2118196167","https://openalex.org/W2556787926","https://openalex.org/W3037235681","https://openalex.org/W3154114438","https://openalex.org/W3196761082","https://openalex.org/W3208810447","https://openalex.org/W3213823339","https://openalex.org/W4206248313"],"related_works":["https://openalex.org/W2407375987","https://openalex.org/W2505726097","https://openalex.org/W2950975704","https://openalex.org/W3049691116","https://openalex.org/W2010643158","https://openalex.org/W2106867672","https://openalex.org/W4310268968","https://openalex.org/W3081214562","https://openalex.org/W2753713401","https://openalex.org/W2053745677"],"abstract_inverted_index":{"Bounded-treewidth":[0],"Bayesian":[1,16,45,62,71],"networks":[2,17,63],"can":[3],"reduce":[4],"overfitting":[5],"and":[6],"exact":[7],"inference":[8],"complexity.":[9],"Several":[10],"known":[11],"methods":[12],"learn":[13],"bounded":[14,43],"treewidth":[15,44],"by":[18],"learning":[19,42],"from":[20],"k-trees.":[21],"However,":[22],"they":[23],"adopt":[24,79],"an":[25,30,36,57],"approximate":[26,96],"method":[27],"instead":[28],"of":[29,50],"accurate":[31,37,58],"method.":[32],"This":[33],"work":[34],"presents":[35],"algorithm":[38,59],"called":[39],"A-kg":[40,89],"for":[41],"networks.":[46],"Our":[47],"approach":[48],"consists":[49],"two":[51],"parts.":[52],"The":[53],"first":[54],"part":[55],"is":[56],"that":[60],"learns":[61],"with":[64],"high":[65],"BIC":[66],"scores,":[67],"which":[68],"measures":[69],"the":[70,75,80],"network\u2019s":[72],"quality.":[73],"In":[74],"second":[76],"part,":[77],"we":[78],"greedy":[81],"strategy":[82],"to":[83,94],"perform":[84],"parent":[85],"set":[86],"selection":[87],"efficiently.":[88],"achieves":[90],"better":[91],"performance":[92],"compared":[93],"some":[95],"solutions":[97],"in":[98],"small":[99],"domains.":[100]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
