{"id":"https://openalex.org/W1996392605","doi":"https://doi.org/10.1109/ijcnn.2007.4371362","title":"Quantitative Bayesian Inference by Qualitative Knowledge Modeling","display_name":"Quantitative Bayesian Inference by Qualitative Knowledge Modeling","publication_year":2007,"publication_date":"2007-08-01","ids":{"openalex":"https://openalex.org/W1996392605","doi":"https://doi.org/10.1109/ijcnn.2007.4371362","mag":"1996392605"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2007.4371362","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2007.4371362","pdf_url":null,"source":{"id":"https://openalex.org/S4210195743","display_name":"IEEE International Conference on Neural Networks/IEEE ... International Conference on Neural Networks","issn_l":"1098-7576","issn":["1098-7576","1558-3902"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 International Joint Conference on Neural Networks","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/A5052637351","display_name":"Rui Chang","orcid":"https://orcid.org/0000-0001-7950-8920"},"institutions":[{"id":"https://openalex.org/I1325886976","display_name":"Siemens (Germany)","ror":"https://ror.org/059mq0909","country_code":"DE","type":"company","lineage":["https://openalex.org/I1325886976"]},{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Rui Chang","raw_affiliation_strings":["Corporate Technology, Information & Communications, Siemens AG, Munich, Germany","Department of Computer Science, Technical University Munich, Garching, Germany"],"affiliations":[{"raw_affiliation_string":"Corporate Technology, Information & Communications, Siemens AG, Munich, Germany","institution_ids":["https://openalex.org/I1325886976"]},{"raw_affiliation_string":"Department of Computer Science, Technical University Munich, Garching, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022342377","display_name":"M. Stetter","orcid":"https://orcid.org/0000-0003-4922-3099"},"institutions":[{"id":"https://openalex.org/I1325886976","display_name":"Siemens (Germany)","ror":"https://ror.org/059mq0909","country_code":"DE","type":"company","lineage":["https://openalex.org/I1325886976"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Martin Stetter","raw_affiliation_strings":["Corporate Technology, Information & Communications, Siemens AG, Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Corporate Technology, Information & Communications, Siemens AG, Munich, Germany","institution_ids":["https://openalex.org/I1325886976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5052637351"],"corresponding_institution_ids":["https://openalex.org/I1325886976","https://openalex.org/I62916508"],"apc_list":null,"apc_paid":null,"fwci":1.5223,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.81784261,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"50","issue":null,"first_page":"2563","last_page":"2568"},"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.9955000281333923,"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":0.9850999712944031,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7139042019844055},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6834386587142944},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.6282541751861572},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.5675405859947205},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5212217569351196},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5118517279624939},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4972124397754669},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4956322908401489},{"id":"https://openalex.org/keywords/bayesian-statistics","display_name":"Bayesian statistics","score":0.48216503858566284},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4792185425758362},{"id":"https://openalex.org/keywords/qualitative-reasoning","display_name":"Qualitative reasoning","score":0.4393021762371063}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7139042019844055},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6834386587142944},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.6282541751861572},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.5675405859947205},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5212217569351196},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5118517279624939},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4972124397754669},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4956322908401489},{"id":"https://openalex.org/C101112237","wikidata":"https://www.wikidata.org/wiki/Q4874481","display_name":"Bayesian statistics","level":4,"score":0.48216503858566284},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4792185425758362},{"id":"https://openalex.org/C83725634","wikidata":"https://www.wikidata.org/wiki/Q7268699","display_name":"Qualitative reasoning","level":2,"score":0.4393021762371063},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2007.4371362","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2007.4371362","pdf_url":null,"source":{"id":"https://openalex.org/S4210195743","display_name":"IEEE International Conference on Neural Networks/IEEE ... International Conference on Neural Networks","issn_l":"1098-7576","issn":["1098-7576","1558-3902"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 International Joint Conference on Neural Networks","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W101442828","https://openalex.org/W1593793857","https://openalex.org/W1615454278","https://openalex.org/W1719177231","https://openalex.org/W1881025941","https://openalex.org/W1893233497","https://openalex.org/W1973155827","https://openalex.org/W1983780377","https://openalex.org/W1989486129","https://openalex.org/W1996933820","https://openalex.org/W2023829601","https://openalex.org/W2048642086","https://openalex.org/W2139507823","https://openalex.org/W2309752383","https://openalex.org/W2397866408","https://openalex.org/W2993001347","https://openalex.org/W4285719527","https://openalex.org/W6604191338","https://openalex.org/W6635452821","https://openalex.org/W6636455871","https://openalex.org/W6637704336","https://openalex.org/W6639267706","https://openalex.org/W6639290150","https://openalex.org/W6680763546","https://openalex.org/W6771782512"],"related_works":["https://openalex.org/W299368792","https://openalex.org/W2372988341","https://openalex.org/W2025423151","https://openalex.org/W4214872087","https://openalex.org/W2068793003","https://openalex.org/W2161970884","https://openalex.org/W2081579622","https://openalex.org/W3049691116","https://openalex.org/W2407375987","https://openalex.org/W3081214562"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"present":[4],"a":[5,27,38,58,101],"novel":[6],"framework":[7],"for":[8],"modeling":[9],"Bayesian":[10,15,52,61],"networks":[11,62],"and":[12,31,55],"performing":[13],"quantitative":[14,98],"inference":[16,72,99],"based":[17],"on":[18,87],"qualitative":[19,24,40,44,68,105],"knowledge.":[20,69],"Our":[21],"method":[22,84,94],"transforms":[23],"statements":[25],"into":[26],"set":[28,102],"of":[29,37,60,103],"structure":[30],"parameter":[32],"constraints":[33,45],"by":[34,75],"making":[35],"use":[36],"proposed":[39],"knowledge":[41],"model.":[42],"These":[43],"are":[46,64],"utilized":[47],"to":[48,56],"restrain":[49],"uncertainties":[50],"in":[51],"model":[53,76],"space":[54],"generate":[57],"class":[59],"which":[63],"consistent":[65],"with":[66,78],"the":[67],"Quantitative":[70],"probabilistic":[71],"is":[73,85],"calculated":[74],"averaging":[77],"Monte":[79],"Carlo":[80],"integration":[81],"method.":[82],"The":[83],"benchmarked":[86],"ASIA":[88],"network.":[89],"Results":[90],"suggest":[91],"that":[92],"our":[93],"can":[95],"reasonably":[96],"predict":[97],"from":[100],"realistic":[104],"statements.":[106]},"counts_by_year":[{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
