{"id":"https://openalex.org/W2601313309","doi":"https://doi.org/10.1142/s2425038416300147","title":"Bayesian networks: Theory, applications and sensitivity issues","display_name":"Bayesian networks: Theory, applications and sensitivity issues","publication_year":2017,"publication_date":"2017-03-01","ids":{"openalex":"https://openalex.org/W2601313309","doi":"https://doi.org/10.1142/s2425038416300147","mag":"2601313309"},"language":"en","primary_location":{"id":"doi:10.1142/s2425038416300147","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s2425038416300147","pdf_url":null,"source":{"id":"https://openalex.org/S4210216749","display_name":"Encyclopedia with Semantic Computing and Robotic Intelligence","issn_l":"2529-7376","issn":["2529-7376","2529-7392"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Encyclopedia with Semantic Computing and Robotic Intelligence","raw_type":"journal-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/A5038915241","display_name":"Ron S. Kenett","orcid":"https://orcid.org/0000-0003-2315-0477"},"institutions":[{"id":"https://openalex.org/I55143463","display_name":"University of Turin","ror":"https://ror.org/048tbm396","country_code":"IT","type":"education","lineage":["https://openalex.org/I55143463"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Ron S. Kenett","raw_affiliation_strings":["KPA Ltd., Raanana, Israel","University of Turin, Turin, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KPA Ltd., Raanana, Israel","institution_ids":[]},{"raw_affiliation_string":"University of Turin, Turin, Italy","institution_ids":["https://openalex.org/I55143463"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5038915241"],"corresponding_institution_ids":["https://openalex.org/I55143463"],"apc_list":null,"apc_paid":null,"fwci":1.2485,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.84701418,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"01","issue":"01","first_page":"1630014","last_page":"1630014"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9790999889373779,"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"}},{"id":"https://openalex.org/T11357","display_name":"Risk and Safety Analysis","score":0.9484000205993652,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"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":0.7197475433349609},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.648899495601654},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.6336117386817932},{"id":"https://openalex.org/keywords/scope","display_name":"Scope (computer science)","score":0.570523202419281},{"id":"https://openalex.org/keywords/information-quality","display_name":"Information quality","score":0.5213279128074646},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5045732259750366},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4939761757850647},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.4841664433479309},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.41648930311203003},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4133462607860565},{"id":"https://openalex.org/keywords/information-system","display_name":"Information system","score":0.3914813697338104},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2677028775215149},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15232589840888977}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7197475433349609},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.648899495601654},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.6336117386817932},{"id":"https://openalex.org/C2778012447","wikidata":"https://www.wikidata.org/wiki/Q1034415","display_name":"Scope (computer science)","level":2,"score":0.570523202419281},{"id":"https://openalex.org/C45983554","wikidata":"https://www.wikidata.org/wiki/Q3412851","display_name":"Information quality","level":3,"score":0.5213279128074646},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5045732259750366},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4939761757850647},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.4841664433479309},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.41648930311203003},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4133462607860565},{"id":"https://openalex.org/C180198813","wikidata":"https://www.wikidata.org/wiki/Q121182","display_name":"Information system","level":2,"score":0.3914813697338104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2677028775215149},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15232589840888977},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"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/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"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/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s2425038416300147","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s2425038416300147","pdf_url":null,"source":{"id":"https://openalex.org/S4210216749","display_name":"Encyclopedia with Semantic Computing and Robotic Intelligence","issn_l":"2529-7376","issn":["2529-7376","2529-7392"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Encyclopedia with Semantic Computing and Robotic Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W78876396","https://openalex.org/W605286721","https://openalex.org/W1499806586","https://openalex.org/W1540788150","https://openalex.org/W1551562311","https://openalex.org/W1819075170","https://openalex.org/W1956772396","https://openalex.org/W1968972075","https://openalex.org/W1980452149","https://openalex.org/W1984754084","https://openalex.org/W1986807275","https://openalex.org/W1989667435","https://openalex.org/W2012571754","https://openalex.org/W2028217358","https://openalex.org/W2038588106","https://openalex.org/W2040110745","https://openalex.org/W2063830632","https://openalex.org/W2088796930","https://openalex.org/W2108984353","https://openalex.org/W2133554893","https://openalex.org/W2143891888","https://openalex.org/W2158326792","https://openalex.org/W2159080219","https://openalex.org/W2161648820","https://openalex.org/W2183559229","https://openalex.org/W2263806212","https://openalex.org/W2327528498","https://openalex.org/W2460132942","https://openalex.org/W2483217698","https://openalex.org/W2507861678","https://openalex.org/W3125555312","https://openalex.org/W4213122772","https://openalex.org/W4239354461","https://openalex.org/W4251690560","https://openalex.org/W4253881831","https://openalex.org/W4256617328","https://openalex.org/W4298191365","https://openalex.org/W4299670631","https://openalex.org/W4313729847"],"related_works":["https://openalex.org/W2183133984","https://openalex.org/W2891233567","https://openalex.org/W3216334995","https://openalex.org/W2400064296","https://openalex.org/W45106814","https://openalex.org/W604614931","https://openalex.org/W2115713508","https://openalex.org/W2967493338","https://openalex.org/W2105381387","https://openalex.org/W2136860952"],"abstract_inverted_index":{"This":[0,83],"chapter":[1,166],"is":[2,17,40,174,197,207,226,231,245],"about":[3,18],"an":[4,202,234,246],"important":[5],"tool":[6,110],"in":[7,123,164,169,182,190,261],"the":[8,34,46,50,59,90,103,165,183,199,284],"data":[9,24,38,64,124,209,228],"science":[10,16],"workbench,":[11],"Bayesian":[12],"networks":[13],"(BNs).":[14],"Data":[15,148],"generating":[19],"information":[20,35,73,99,132],"from":[21,37,198],"a":[22,95,108,113,191,208,253,274],"given":[23],"set":[25],"using":[26],"applications":[27,278],"of":[28,33,48,92,98,105,116,147,180,185,201,239,269,276],"statistical":[29,109,117],"methods.":[30],"The":[31,145,160,171,194,223,242],"quality":[32,133],"derived":[36],"analysis":[39,118,218,268],"dependent":[41],"on":[42,129,176,233,256],"various":[43,63],"dimensions,":[44],"including":[45],"communication":[47],"results,":[49],"ability":[51],"to":[52,61,151,248],"translate":[53],"results":[54],"into":[55],"actionable":[56],"tasks":[57],"and":[58,69,111,140,149,156,206,219,230],"capability":[60],"integrate":[62],"sources":[65],"[R.":[66,137],"S.":[67,138],"Kenett":[68,139],"G.":[70,141],"Shmueli,":[71,142],"On":[72],"quality,":[74],"J.":[75],"R.":[76],"Stat.":[77],"Soc.":[78],"A":[79],"177(1),":[80],"3":[81],"(2014).]":[82],"paper":[84],"demonstrates,":[85],"with":[86,134],"three":[87,161],"examples,":[88],"how":[89],"application":[91,211],"BNs":[93,106,135],"provides":[94,112,252],"high":[96,131],"level":[97],"quality.":[100],"It":[101],"expands":[102],"treatment":[104],"as":[107],"wider":[114],"scope":[115],"that":[119,212],"matches":[120],"current":[121],"trends":[122],"science.":[125],"For":[126],"more":[127],"examples":[128,162],"deriving":[130],"see":[136],"Information":[143],"Quality:":[144],"Potential":[146],"Analytics":[150],"Generate":[152],"Knowledge":[153],"(John":[154],"Wiley":[155],"Sons,":[157],"2016),":[158],"www.wiley.com/go/information_quality.]":[159],"used":[163],"are":[167,259],"complementary":[168],"scope.":[170],"first":[172,243],"example":[173,196,225],"based":[175,232],"expert":[177,214],"opinion":[178],"assessments":[179],"risks":[181],"operation":[184],"health":[186],"care":[187],"monitoring":[188,200],"systems":[189],"hospital":[192],"environment.":[193],"second":[195],"open":[203],"source":[204],"community":[205],"rich":[210],"combines":[213],"opinion,":[215],"social":[216],"network":[217],"continuous":[220],"operational":[221],"variables.":[222],"third":[224],"totally":[227],"driven":[229],"extensive":[235],"customer":[236],"satisfaction":[237],"survey":[238],"airline":[240],"customers.":[241],"section":[244],"introduction":[247],"BNs,":[249,270],"Sec.":[250,262,271],"2":[251],"theoretical":[254],"background":[255],"BN.":[257],"Examples":[258],"provided":[260],"3.":[263],"Section":[264,281],"4":[265],"discusses":[266],"sensitivity":[267],"5":[272],"lists":[273],"range":[275],"software":[277],"implementing":[279],"BNs.":[280],"6":[282],"concludes":[283],"chapter.":[285]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2026-05-21T09:19:25.381259","created_date":"2025-10-10T00:00:00"}
