{"id":"https://openalex.org/W1982501137","doi":"https://doi.org/10.1109/coginf.2010.5599716","title":"Hybrid incremental learning algorithms for bayesian network structures","display_name":"Hybrid incremental learning algorithms for bayesian network structures","publication_year":2010,"publication_date":"2010-07-01","ids":{"openalex":"https://openalex.org/W1982501137","doi":"https://doi.org/10.1109/coginf.2010.5599716","mag":"1982501137"},"language":"en","primary_location":{"id":"doi:10.1109/coginf.2010.5599716","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coginf.2010.5599716","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"9th IEEE International Conference on Cognitive Informatics (ICCI'10)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102548881","display_name":"Da Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Da Shi","raw_affiliation_strings":["Center of Information, School of Electronics Engineering and Computer Science, Peking University, Beijing, China","Center for Information, School of Electronics, Engineering and Computer Science, Peking University, Beijing 100871, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center of Information, School of Electronics Engineering and Computer Science, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Center for Information, School of Electronics, Engineering and Computer Science, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100510526","display_name":"Shaohua Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaohua Tan","raw_affiliation_strings":["Center of Information, School of Electronics Engineering and Computer Science, Peking University, Beijing, China","Center for Information, School of Electronics, Engineering and Computer Science, Peking University, Beijing 100871, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center of Information, School of Electronics Engineering and Computer Science, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Center for Information, School of Electronics, Engineering and Computer Science, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.2725,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.47331723,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"345","last_page":"352"},"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":0.9365000128746033,"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":0.9265999794006348,"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/bayesian-network","display_name":"Bayesian network","score":0.7189087867736816},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7020177841186523},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.637564480304718},{"id":"https://openalex.org/keywords/hill-climbing","display_name":"Hill climbing","score":0.6239463090896606},{"id":"https://openalex.org/keywords/hybrid-algorithm","display_name":"Hybrid algorithm (constraint satisfaction)","score":0.5321815013885498},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4947321116924286},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.4907597005367279},{"id":"https://openalex.org/keywords/incremental-learning","display_name":"Incremental learning","score":0.48303112387657166},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4649215042591095},{"id":"https://openalex.org/keywords/time-complexity","display_name":"Time complexity","score":0.44598355889320374},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44149288535118103},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.435586154460907},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.4253595173358917},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.418316513299942},{"id":"https://openalex.org/keywords/constraint-satisfaction","display_name":"Constraint satisfaction","score":0.17628002166748047},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17409288883209229},{"id":"https://openalex.org/keywords/local-consistency","display_name":"Local consistency","score":0.10693761706352234},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.08570501208305359}],"concepts":[{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.7189087867736816},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7020177841186523},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.637564480304718},{"id":"https://openalex.org/C135450995","wikidata":"https://www.wikidata.org/wiki/Q820272","display_name":"Hill climbing","level":2,"score":0.6239463090896606},{"id":"https://openalex.org/C62469222","wikidata":"https://www.wikidata.org/wiki/Q17092103","display_name":"Hybrid algorithm (constraint satisfaction)","level":5,"score":0.5321815013885498},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4947321116924286},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.4907597005367279},{"id":"https://openalex.org/C2780735816","wikidata":"https://www.wikidata.org/wiki/Q28324931","display_name":"Incremental learning","level":2,"score":0.48303112387657166},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4649215042591095},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.44598355889320374},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44149288535118103},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.435586154460907},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.4253595173358917},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.418316513299942},{"id":"https://openalex.org/C44616089","wikidata":"https://www.wikidata.org/wiki/Q30158686","display_name":"Constraint satisfaction","level":3,"score":0.17628002166748047},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17409288883209229},{"id":"https://openalex.org/C137105694","wikidata":"https://www.wikidata.org/wiki/Q3407510","display_name":"Local consistency","level":4,"score":0.10693761706352234},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.08570501208305359},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/coginf.2010.5599716","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coginf.2010.5599716","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"9th IEEE International Conference on Cognitive Informatics (ICCI'10)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1486292173","https://openalex.org/W1517993545","https://openalex.org/W1530476443","https://openalex.org/W1547246444","https://openalex.org/W1722352548","https://openalex.org/W1769824028","https://openalex.org/W1973807737","https://openalex.org/W1983690667","https://openalex.org/W1988814833","https://openalex.org/W2105940436","https://openalex.org/W2123838014","https://openalex.org/W2129178015","https://openalex.org/W2137857056","https://openalex.org/W2154053567","https://openalex.org/W2163166770","https://openalex.org/W2168175751","https://openalex.org/W2170112109","https://openalex.org/W2173003644","https://openalex.org/W2397866408","https://openalex.org/W4211064163","https://openalex.org/W4300906944","https://openalex.org/W6631741591","https://openalex.org/W6636455871","https://openalex.org/W6637593493","https://openalex.org/W6644108911","https://openalex.org/W6680615814"],"related_works":["https://openalex.org/W2186944257","https://openalex.org/W2147164533","https://openalex.org/W2556112123","https://openalex.org/W2393852462","https://openalex.org/W2365855712","https://openalex.org/W1539889974","https://openalex.org/W2354062556","https://openalex.org/W1536658836","https://openalex.org/W348064518","https://openalex.org/W2794858631"],"abstract_inverted_index":{"Hybrid":[0],"learning":[1],"can":[2],"reduce":[3],"the":[4,35,51,58,63,66,91],"computational":[5,81],"complexity":[6,82],"of":[7,20,29,65],"incremental":[8,22,77,93],"algorithms":[9,23,31,78],"for":[10,45],"Bayesian":[11],"network":[12,60],"structures":[13],"significantly.":[14],"In":[15],"this":[16],"paper,":[17],"a":[18,41],"group":[19],"hybrid":[21,76],"are":[24],"proposed.":[25],"The":[26,70],"central":[27],"idea":[28],"these":[30],"is":[32],"to":[33,39,56,90],"use":[34],"polynomial-time":[36],"constraint-based":[37],"technique":[38],"build":[40],"candidate":[42,67],"parent":[43,68],"set":[44],"each":[46],"domain":[47],"variable,":[48],"followed":[49],"by":[50],"hill":[52],"climbing":[53],"search":[54],"procedure":[55],"refine":[57],"current":[59],"structure":[61],"under":[62],"guidance":[64],"sets.":[69],"experimental":[71],"results":[72],"show":[73],"that,":[74],"our":[75],"offer":[79],"considerable":[80],"savings":[83],"while":[84],"obtaining":[85],"better":[86],"model":[87],"accuracy":[88],"compared":[89],"existing":[92],"algorithms.":[94]},"counts_by_year":[{"year":2013,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
