{"id":"https://openalex.org/W2137222605","doi":"https://doi.org/10.1145/2396761.2398408","title":"Non-stationary bayesian networks based on perfect simulation","display_name":"Non-stationary bayesian networks based on perfect simulation","publication_year":2012,"publication_date":"2012-10-29","ids":{"openalex":"https://openalex.org/W2137222605","doi":"https://doi.org/10.1145/2396761.2398408","mag":"2137222605"},"language":"en","primary_location":{"id":"doi:10.1145/2396761.2398408","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2396761.2398408","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21st ACM international conference on Information and knowledge management","raw_type":"proceedings-article"},"type":"article","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/A5055837216","display_name":"Yi Jia","orcid":"https://orcid.org/0000-0001-8171-5849"},"institutions":[{"id":"https://openalex.org/I146416000","display_name":"University of Kansas","ror":"https://ror.org/001tmjg57","country_code":"US","type":"education","lineage":["https://openalex.org/I146416000"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yi Jia","raw_affiliation_strings":["University of Kansas, Lawrence, KS, USA"],"affiliations":[{"raw_affiliation_string":"University of Kansas, Lawrence, KS, USA","institution_ids":["https://openalex.org/I146416000"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038574302","display_name":"Wenrong Zeng","orcid":null},"institutions":[{"id":"https://openalex.org/I146416000","display_name":"University of Kansas","ror":"https://ror.org/001tmjg57","country_code":"US","type":"education","lineage":["https://openalex.org/I146416000"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wenrong Zeng","raw_affiliation_strings":["University of Kansas, Lawrence, KS, USA"],"affiliations":[{"raw_affiliation_string":"University of Kansas, Lawrence, KS, USA","institution_ids":["https://openalex.org/I146416000"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5105352906","display_name":"Jun Huan","orcid":"https://orcid.org/0000-0003-4929-2617"},"institutions":[{"id":"https://openalex.org/I146416000","display_name":"University of Kansas","ror":"https://ror.org/001tmjg57","country_code":"US","type":"education","lineage":["https://openalex.org/I146416000"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jun Huan","raw_affiliation_strings":["University of Kansas, Lawrence, KS, USA"],"affiliations":[{"raw_affiliation_string":"University of Kansas, Lawrence, KS, USA","institution_ids":["https://openalex.org/I146416000"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5055837216"],"corresponding_institution_ids":["https://openalex.org/I146416000"],"apc_list":null,"apc_paid":null,"fwci":0.4281,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.73288402,"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":"1095","last_page":"1104"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9988999962806702,"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":0.9988999962806702,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9847999811172485,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10836","display_name":"Metabolomics and Mass Spectrometry Studies","score":0.9656000137329102,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/dynamic-bayesian-network","display_name":"Dynamic Bayesian network","score":0.8127539753913879},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6906762719154358},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5785170197486877},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4983654022216797},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4947590231895447},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.48670485615730286},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.4788546562194824},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.46911054849624634},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.44835859537124634},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43726634979248047},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.4165942668914795},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39540499448776245},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3921997547149658},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.377354234457016},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09190541505813599}],"concepts":[{"id":"https://openalex.org/C82142266","wikidata":"https://www.wikidata.org/wiki/Q3456604","display_name":"Dynamic Bayesian network","level":3,"score":0.8127539753913879},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6906762719154358},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5785170197486877},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4983654022216797},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4947590231895447},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.48670485615730286},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.4788546562194824},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.46911054849624634},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.44835859537124634},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43726634979248047},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.4165942668914795},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39540499448776245},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3921997547149658},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.377354234457016},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09190541505813599},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2396761.2398408","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2396761.2398408","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 21st ACM international conference on Information and knowledge management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320329559","display_name":"Technische Universit\u00e4t Dortmund","ror":"https://ror.org/01k97gp34"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W129077257","https://openalex.org/W602633559","https://openalex.org/W1560368109","https://openalex.org/W1586003574","https://openalex.org/W1759730364","https://openalex.org/W1967042859","https://openalex.org/W1972555382","https://openalex.org/W2005884645","https://openalex.org/W2006877085","https://openalex.org/W2011863452","https://openalex.org/W2029275361","https://openalex.org/W2040575507","https://openalex.org/W2044646840","https://openalex.org/W2074021914","https://openalex.org/W2082313778","https://openalex.org/W2095622082","https://openalex.org/W2106706098","https://openalex.org/W2107017568","https://openalex.org/W2113166878","https://openalex.org/W2119556746","https://openalex.org/W2121306063","https://openalex.org/W2121787035","https://openalex.org/W2121812493","https://openalex.org/W2123321939","https://openalex.org/W2124288003","https://openalex.org/W2129505753","https://openalex.org/W2138280093","https://openalex.org/W2139954840","https://openalex.org/W2142277116","https://openalex.org/W2143943607","https://openalex.org/W2148534890","https://openalex.org/W2153337510","https://openalex.org/W2155205047","https://openalex.org/W2160400978","https://openalex.org/W2163830119","https://openalex.org/W2170112109","https://openalex.org/W2328968168","https://openalex.org/W2542256003","https://openalex.org/W4238995646","https://openalex.org/W4285719527","https://openalex.org/W6618295873","https://openalex.org/W6681383220"],"related_works":["https://openalex.org/W3128072696","https://openalex.org/W2578973671","https://openalex.org/W2215058820","https://openalex.org/W2097663773","https://openalex.org/W1602184117","https://openalex.org/W2413421635","https://openalex.org/W2511198839","https://openalex.org/W2061193177","https://openalex.org/W1966557338","https://openalex.org/W2366931106"],"abstract_inverted_index":{"Non-stationary":[0],"Dynamic":[1],"Bayesian":[2],"Networks":[3],"(Non-stationary":[4],"DBNs)":[5],"are":[6],"widely":[7],"used":[8],"to":[9,120],"model":[10,117,130],"the":[11,24,57,126,129],"temporal":[12],"changes":[13],"of":[14,128],"directed":[15],"dependency":[16],"structures":[17],"from":[18,69],"multivariate":[19],"time":[20],"series":[21],"data.":[22],"However,":[23],"existing":[25],"change-points":[26],"based":[27,55],"non-stationary":[28,49,85],"DBNs":[29,50,86],"methods":[30,99],"have":[31],"several":[32],"drawbacks":[33],"including":[34],"excessive":[35],"computational":[36,102],"cost,":[37],"and":[38,72,78,104],"low":[39],"convergence":[40],"speed.":[41],"In":[42],"this":[43,63],"paper":[44],"we":[45],"proposed":[46],"a":[47],"novel":[48],"method.":[51],"Our":[52],"method":[53,94],"is":[54,118],"on":[56],"perfect":[58],"simulation":[59],"model.":[60],"We":[61],"applied":[62],"approach":[64],"for":[65],"network":[66],"structure":[67,105],"inference":[68],"synthetic":[70],"data":[71,77],"biological":[73],"microarray":[74],"gene":[75],"expression":[76],"compared":[79],"it":[80],"with":[81],"other":[82,97],"two":[83,96],"state-of-the-art":[84,98],"methods.":[87],"The":[88,108],"experimental":[89],"results":[90],"demonstrated":[91],"that":[92,113],"our":[93,116],"outperformed":[95],"in":[100],"both":[101],"cost":[103],"prediction":[106],"accuracy.":[107],"further":[109],"sensitivity":[110],"analysis":[111],"showed":[112],"once":[114],"converged":[115],"robust":[119],"large":[121],"parameter":[122],"ranges,":[123],"which":[124],"reduces":[125],"uncertainty":[127],"behavior.":[131]},"counts_by_year":[{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}