{"id":"https://openalex.org/W1991783464","doi":"https://doi.org/10.1109/grc.2009.5255111","title":"On designing approximate inference algorithms for multiply sectioned Bayesian networks","display_name":"On designing approximate inference algorithms for multiply sectioned Bayesian networks","publication_year":2009,"publication_date":"2009-08-01","ids":{"openalex":"https://openalex.org/W1991783464","doi":"https://doi.org/10.1109/grc.2009.5255111","mag":"1991783464"},"language":"en","primary_location":{"id":"doi:10.1109/grc.2009.5255111","is_oa":false,"landing_page_url":"https://doi.org/10.1109/grc.2009.5255111","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Granular Computing","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/A5112755161","display_name":"Karen H. Jin","orcid":null},"institutions":[{"id":"https://openalex.org/I74413500","display_name":"University of Windsor","ror":"https://ror.org/01gw3d370","country_code":"CA","type":"education","lineage":["https://openalex.org/I74413500"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Karen H. Jin","raw_affiliation_strings":["School of Computer Science, University of Windsor, Windsor, Canada","School of Computer Science, University Of Windsor, Canada"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Windsor, Windsor, Canada","institution_ids":["https://openalex.org/I74413500"]},{"raw_affiliation_string":"School of Computer Science, University Of Windsor, Canada","institution_ids":["https://openalex.org/I74413500"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065647746","display_name":"Dan Wu","orcid":"https://orcid.org/0000-0002-2722-8676"},"institutions":[{"id":"https://openalex.org/I74413500","display_name":"University of Windsor","ror":"https://ror.org/01gw3d370","country_code":"CA","type":"education","lineage":["https://openalex.org/I74413500"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Dan Wu","raw_affiliation_strings":["School of Computer Science, University of Windsor, Windsor, Canada","School of Computer Science, University Of Windsor, Canada"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Windsor, Windsor, Canada","institution_ids":["https://openalex.org/I74413500"]},{"raw_affiliation_string":"School of Computer Science, University Of Windsor, Canada","institution_ids":["https://openalex.org/I74413500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108047844","display_name":"Libing Wu","orcid":"https://orcid.org/0000-0001-9897-1953"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Libing Wu","raw_affiliation_strings":["School of Computer, Wuhan University of China, Wuhan, China","School of Computer, Wuhan university, China"],"affiliations":[{"raw_affiliation_string":"School of Computer, Wuhan University of China, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Computer, Wuhan university, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5112755161"],"corresponding_institution_ids":["https://openalex.org/I74413500"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.07519458,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"294","last_page":"299"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":1.0,"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":1.0,"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/T11010","display_name":"Logic, Reasoning, and Knowledge","score":0.9722999930381775,"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/T11719","display_name":"Data Quality and Management","score":0.970300018787384,"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":0.7639251947402954},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7219329476356506},{"id":"https://openalex.org/keywords/subnet","display_name":"Subnet","score":0.6393691301345825},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.548891007900238},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4900892972946167},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4770709276199341},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.47431182861328125},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.45550063252449036},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.44591760635375977},{"id":"https://openalex.org/keywords/approximate-inference","display_name":"Approximate inference","score":0.4246608018875122},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.42317354679107666},{"id":"https://openalex.org/keywords/suite","display_name":"Suite","score":0.4151079058647156},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.37830230593681335},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3515697419643402},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33764275908470154},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.3347380757331848},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13834479451179504}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7639251947402954},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7219329476356506},{"id":"https://openalex.org/C21099817","wikidata":"https://www.wikidata.org/wiki/Q7631721","display_name":"Subnet","level":2,"score":0.6393691301345825},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.548891007900238},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4900892972946167},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4770709276199341},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47431182861328125},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.45550063252449036},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.44591760635375977},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.4246608018875122},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.42317354679107666},{"id":"https://openalex.org/C79581498","wikidata":"https://www.wikidata.org/wiki/Q1367530","display_name":"Suite","level":2,"score":0.4151079058647156},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.37830230593681335},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3515697419643402},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33764275908470154},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.3347380757331848},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13834479451179504},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/grc.2009.5255111","is_oa":false,"landing_page_url":"https://doi.org/10.1109/grc.2009.5255111","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Conference on Granular Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41999998688697815,"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W42277732","https://openalex.org/W1484324861","https://openalex.org/W1526990002","https://openalex.org/W1561981064","https://openalex.org/W1593793857","https://openalex.org/W1980452149","https://openalex.org/W2049073556","https://openalex.org/W2062122868","https://openalex.org/W2084247237","https://openalex.org/W2102753033","https://openalex.org/W2114909350","https://openalex.org/W2134480729","https://openalex.org/W2150344704","https://openalex.org/W2159080219","https://openalex.org/W2950966842","https://openalex.org/W3105307699","https://openalex.org/W4254833237","https://openalex.org/W6601773074","https://openalex.org/W6631435758","https://openalex.org/W6633541872","https://openalex.org/W6666091668"],"related_works":["https://openalex.org/W4293094099","https://openalex.org/W4388716341","https://openalex.org/W2963960970","https://openalex.org/W4221153946","https://openalex.org/W2548353158","https://openalex.org/W2963071676","https://openalex.org/W2099667085","https://openalex.org/W4302573481","https://openalex.org/W2505308168","https://openalex.org/W2775655892"],"abstract_inverted_index":{"An":[0],"increasing":[1],"number":[2],"of":[3,13,21,89,102],"applications":[4],"require":[5],"cooperative":[6,53],"agents":[7],"to":[8,86],"reason":[9],"about":[10],"the":[11,48,62,83,87,94],"state":[12],"an":[14,114],"distributed":[15,120],"uncertainty":[16],"domain.":[17],"However,":[18],"inference":[19,91],"process":[20,118],"such":[22],"system":[23],"could":[24],"become":[25],"overly":[26],"slow":[27],"for":[28,52,67,93,104],"practical":[29],"applications,":[30],"and":[31,119],"there":[32],"has":[33],"been":[34],"significant":[35],"interest":[36],"in":[37,55,76,109],"developing":[38],"faster":[39],"approximation":[40],"techniques.":[41],"In":[42],"this":[43],"paper,":[44],"we":[45,81],"focus":[46],"on":[47,123],"existing":[49,70],"MSBN":[50,95,115,124],"models":[51],"reasoning":[54,108],"multi-agent":[56,106],"environments.":[57],"We":[58,97],"show":[59],"that,":[60],"while":[61],"MSBNs":[63],"provide":[64],"a":[65,100],"framework":[66],"exact":[68],"inference,":[69],"algorithms":[71,103],"are":[72],"usually":[73],"not":[74],"feasible":[75],"larger":[77],"problem":[78],"domains.":[79],"Therefore,":[80],"investigate":[82],"issues":[84],"related":[85],"design":[88],"efficient":[90],"algorithm":[92],"model.":[96],"then":[98],"propose":[99],"suite":[101],"approximate":[105],"probabilistic":[107],"MSBNs.":[110],"Our":[111],"approach":[112],"includes":[113],"subnet":[116],"calibration":[117],"stochastic":[121],"sampling":[122],"LJFs.":[125]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
