{"id":"https://openalex.org/W4414437638","doi":"https://doi.org/10.1007/978-3-032-05134-9_2","title":"Classifying Control Room Operators\u2019 Performance Using Bayesian Networks","display_name":"Classifying Control Room Operators\u2019 Performance Using Bayesian Networks","publication_year":2025,"publication_date":"2025-09-23","ids":{"openalex":"https://openalex.org/W4414437638","doi":"https://doi.org/10.1007/978-3-032-05134-9_2"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-032-05134-9_2","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-032-05134-9_2","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","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/A5092928402","display_name":"Houda Briwa","orcid":null},"institutions":[{"id":"https://openalex.org/I4210144925","display_name":"Technological University Dublin","ror":"https://ror.org/04t0qbt32","country_code":"IE","type":"education","lineage":["https://openalex.org/I4210144925"]}],"countries":["IE"],"is_corresponding":true,"raw_author_name":"Houda Briwa","raw_affiliation_strings":["Technological University Dublin, Dublin, Ireland"],"raw_orcid":"https://orcid.org/0009-0005-3741-8325","affiliations":[{"raw_affiliation_string":"Technological University Dublin, Dublin, Ireland","institution_ids":["https://openalex.org/I4210144925"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084283099","display_name":"Anders L. Madsen","orcid":"https://orcid.org/0000-0003-0633-9411"},"institutions":[{"id":"https://openalex.org/I4210148437","display_name":"Hugin Expert (Denmark)","ror":"https://ror.org/053pt1j04","country_code":"DK","type":"company","lineage":["https://openalex.org/I4210148437"]},{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Anders L. Madsen","raw_affiliation_strings":["Aalborg University, Aalborg, Denmark","HUGIN EXPERT A/S, Aalborg, Denmark"],"raw_orcid":"https://orcid.org/0000-0003-0633-9411","affiliations":[{"raw_affiliation_string":"Aalborg University, Aalborg, Denmark","institution_ids":["https://openalex.org/I891191580"]},{"raw_affiliation_string":"HUGIN EXPERT A/S, Aalborg, Denmark","institution_ids":["https://openalex.org/I4210148437"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061312792","display_name":"Maria Chiara Leva","orcid":"https://orcid.org/0000-0002-6770-8332"},"institutions":[{"id":"https://openalex.org/I4210144925","display_name":"Technological University Dublin","ror":"https://ror.org/04t0qbt32","country_code":"IE","type":"education","lineage":["https://openalex.org/I4210144925"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Maria Chiara Leva","raw_affiliation_strings":["Technological University Dublin, Dublin, Ireland"],"raw_orcid":"https://orcid.org/0000-0002-6770-8332","affiliations":[{"raw_affiliation_string":"Technological University Dublin, Dublin, Ireland","institution_ids":["https://openalex.org/I4210144925"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5092928402"],"corresponding_institution_ids":["https://openalex.org/I4210144925"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.4102107,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"17","last_page":"30"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9857000112533569,"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":0.9857000112533569,"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9754999876022339,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13248","display_name":"Healthcare Technology and Patient Monitoring","score":0.9696999788284302,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.7818999886512756},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5770000219345093},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5638999938964844},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.550599992275238},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.49889999628067017},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4674000144004822},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.4302999973297119},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4251999855041504},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.3970000147819519}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8539000153541565},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.7818999886512756},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5918999910354614},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5770000219345093},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5638999938964844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5573999881744385},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.550599992275238},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.49889999628067017},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48350000381469727},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4674000144004822},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.4302999973297119},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4251999855041504},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.3970000147819519},{"id":"https://openalex.org/C127043819","wikidata":"https://www.wikidata.org/wiki/Q16243608","display_name":"Bayesian programming","level":5,"score":0.36480000615119934},{"id":"https://openalex.org/C82142266","wikidata":"https://www.wikidata.org/wiki/Q3456604","display_name":"Dynamic Bayesian network","level":3,"score":0.35659998655319214},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.35370001196861267},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.31349998712539673},{"id":"https://openalex.org/C40343088","wikidata":"https://www.wikidata.org/wiki/Q3059012","display_name":"Recursive Bayesian estimation","level":3,"score":0.3089999854564667},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.30329999327659607},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.2976999878883362},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.2727999985218048},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.26589998602867126},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.2554999887943268},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.25519999861717224},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2542000114917755},{"id":"https://openalex.org/C2779119184","wikidata":"https://www.wikidata.org/wiki/Q294350","display_name":"ALARM","level":2,"score":0.2515000104904175}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/978-3-032-05134-9_2","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-032-05134-9_2","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},{"id":"pmh:oai:pure.atira.dk:publications/769dc568-ba3e-4806-9364-d052b69a4c0a","is_oa":false,"landing_page_url":"https://vbn.aau.dk/da/publications/769dc568-ba3e-4806-9364-d052b69a4c0a","pdf_url":null,"source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Briwa, H, Madsen, A L & Leva, M C 2025, Classifying Control Room Operators\u2019 Performance Using Bayesian Networks. in K Sauerwald & M Thimm (eds), Symbolic and Quantitative Approaches to Reasoning with Uncertainty : 18th European Conference, ECSQARU 2025, Hagen, Germany, September 23\u201326, 2025, Proceedings. Springer, Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence subseries), vol. 16099, pp. 17-30, 18th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2025, Hagen, Germany, 23/09/2025. https://doi.org/10.1007/978-3-032-05134-9_2","raw_type":"info:eu-repo/semantics/publishedVersion"}],"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/W1002297076","https://openalex.org/W1511986666","https://openalex.org/W1513732820","https://openalex.org/W1523646822","https://openalex.org/W1817561967","https://openalex.org/W2002412017","https://openalex.org/W2020679471","https://openalex.org/W2029800614","https://openalex.org/W2092939357","https://openalex.org/W2132434674","https://openalex.org/W2163166770","https://openalex.org/W2266451181","https://openalex.org/W2768908797","https://openalex.org/W3183007303","https://openalex.org/W3184969790","https://openalex.org/W4206609292","https://openalex.org/W4249247926","https://openalex.org/W4280615096","https://openalex.org/W4285234304","https://openalex.org/W4292322170","https://openalex.org/W4306404081","https://openalex.org/W4385872478","https://openalex.org/W4386987255","https://openalex.org/W4388209567","https://openalex.org/W4391597754","https://openalex.org/W6967289325"],"related_works":[],"abstract_inverted_index":null,"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}