{"id":"https://openalex.org/W4385568007","doi":"https://doi.org/10.1145/3580305.3599230","title":"2nd Workshop on Uncertainty Reasoning and Quantification in Decision Making","display_name":"2nd Workshop on Uncertainty Reasoning and Quantification in Decision Making","publication_year":2023,"publication_date":"2023-08-04","ids":{"openalex":"https://openalex.org/W4385568007","doi":"https://doi.org/10.1145/3580305.3599230"},"language":"en","primary_location":{"id":"doi:10.1145/3580305.3599230","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599230","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://vtechworks.lib.vt.edu/bitstreams/beda41a3-2cef-4b37-8c0e-98f478795b49/download","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036221931","display_name":"Xujiang Zhao","orcid":"https://orcid.org/0000-0003-4950-4018"},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xujiang Zhao","raw_affiliation_strings":["NEC Laboratories America, Princeton, NJ, USA"],"affiliations":[{"raw_affiliation_string":"NEC Laboratories America, Princeton, NJ, USA","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100767050","display_name":"Chen Zhao","orcid":"https://orcid.org/0000-0002-6400-0048"},"institutions":[{"id":"https://openalex.org/I157394403","display_name":"Baylor University","ror":"https://ror.org/005781934","country_code":"US","type":"education","lineage":["https://openalex.org/I157394403"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chen Zhao","raw_affiliation_strings":["Baylor University, Waco, TX, USA"],"affiliations":[{"raw_affiliation_string":"Baylor University, Waco, TX, USA","institution_ids":["https://openalex.org/I157394403"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100352703","display_name":"Feng Chen","orcid":"https://orcid.org/0000-0002-4508-5963"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Feng Chen","raw_affiliation_strings":["University of Texas at Dallas, Richardson, TX, USA"],"affiliations":[{"raw_affiliation_string":"University of Texas at Dallas, Richardson, TX, USA","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011649304","display_name":"Jin-Hee Cho","orcid":"https://orcid.org/0000-0002-5908-4662"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jin-Hee Cho","raw_affiliation_strings":["Virginia Tech, Blacksburg, VA, USA"],"affiliations":[{"raw_affiliation_string":"Virginia Tech, Blacksburg, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004514673","display_name":"Haifeng Chen","orcid":"https://orcid.org/0000-0003-3934-7311"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haifeng Chen","raw_affiliation_strings":["NEC Laboratories America, Princetioin, NJ, USA"],"affiliations":[{"raw_affiliation_string":"NEC Laboratories America, Princetioin, NJ, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5036221931"],"corresponding_institution_ids":["https://openalex.org/I20089843"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08906109,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5907","last_page":"5908"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9850000143051147,"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":0.9850000143051147,"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":0.9830999970436096,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9711999893188477,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5775456428527832},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5471162796020508},{"id":"https://openalex.org/keywords/management-science","display_name":"Management science","score":0.5290771126747131},{"id":"https://openalex.org/keywords/uncertainty-quantification","display_name":"Uncertainty quantification","score":0.46239814162254333},{"id":"https://openalex.org/keywords/evidential-reasoning-approach","display_name":"Evidential reasoning approach","score":0.46213382482528687},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4489167332649231},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44463470578193665},{"id":"https://openalex.org/keywords/business-decision-mapping","display_name":"Business decision mapping","score":0.39575499296188354},{"id":"https://openalex.org/keywords/decision-support-system","display_name":"Decision support system","score":0.32449352741241455},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.26390886306762695},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13755062222480774},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08554965257644653}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5775456428527832},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5471162796020508},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.5290771126747131},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.46239814162254333},{"id":"https://openalex.org/C156201811","wikidata":"https://www.wikidata.org/wiki/Q5418360","display_name":"Evidential reasoning approach","level":4,"score":0.46213382482528687},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4489167332649231},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44463470578193665},{"id":"https://openalex.org/C97944126","wikidata":"https://www.wikidata.org/wiki/Q5001864","display_name":"Business decision mapping","level":3,"score":0.39575499296188354},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.32449352741241455},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26390886306762695},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13755062222480774},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08554965257644653},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3580305.3599230","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599230","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:vtechworks.lib.vt.edu:10919/116202","is_oa":true,"landing_page_url":"http://hdl.handle.net/10919/116202","pdf_url":"https://vtechworks.lib.vt.edu/bitstreams/beda41a3-2cef-4b37-8c0e-98f478795b49/download","source":{"id":"https://openalex.org/S4306400248","display_name":"VTechWorks (Virginia Tech)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I859038795","host_organization_name":"Virginia Tech","host_organization_lineage":["https://openalex.org/I859038795"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:vtechworks.lib.vt.edu:10919/116202","is_oa":true,"landing_page_url":"http://hdl.handle.net/10919/116202","pdf_url":"https://vtechworks.lib.vt.edu/bitstreams/beda41a3-2cef-4b37-8c0e-98f478795b49/download","source":{"id":"https://openalex.org/S4306400248","display_name":"VTechWorks (Virginia Tech)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I859038795","host_organization_name":"Virginia Tech","host_organization_lineage":["https://openalex.org/I859038795"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5921281487","display_name":null,"funder_award_id":"number","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8329380728","display_name":null,"funder_award_id":"2107449","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4385568007.pdf"},"referenced_works_count":5,"referenced_works":["https://openalex.org/W2914648904","https://openalex.org/W3011901034","https://openalex.org/W3094397005","https://openalex.org/W4221161646","https://openalex.org/W6602610147"],"related_works":["https://openalex.org/W646492873","https://openalex.org/W787402332","https://openalex.org/W2899325887","https://openalex.org/W4242788481","https://openalex.org/W1485742592","https://openalex.org/W1581101130","https://openalex.org/W261301474","https://openalex.org/W2150145149","https://openalex.org/W2600221717","https://openalex.org/W2355049521"],"abstract_inverted_index":{"Uncertainty":[0],"reasoning":[1,50,83,118],"and":[2,20,28,37,51,62,73,84,94,109,114,132,137],"quantification":[3,52],"play":[4],"a":[5,58],"critical":[6,46],"role":[7],"in":[8,53,75,120],"decision":[9,39,54,95],"making":[10],"across":[11],"various":[12,121],"domains,":[13],"prompting":[14],"increased":[15],"attention":[16],"from":[17,64],"both":[18],"academia":[19],"industry.":[21],"As":[22],"real-world":[23],"applications":[24],"become":[25],"more":[26],"complex":[27],"data-driven,":[29],"effectively":[30],"handling":[31],"uncertainty":[32,49,82],"becomes":[33],"paramount":[34],"for":[35,60,107,112],"accurate":[36],"reliable":[38],"making.":[40,55],"This":[41],"workshop":[42,101],"focuses":[43],"on":[44,70],"the":[45,105,126],"topics":[47],"of":[48,81],"It":[56],"provides":[57],"platform":[59],"experts":[61],"researchers":[63],"diverse":[65],"backgrounds":[66],"to":[67,103,128],"exchange":[68],"ideas":[69],"cutting-edge":[71],"techniques":[72],"challenges":[74],"this":[76],"field.":[77],"The":[78,100],"interdisciplinary":[79],"nature":[80],"quantification,":[85],"spanning":[86],"artificial":[87],"intelligence,":[88],"machine":[89],"learning,":[90],"statistics,":[91],"risk":[92],"analysis,":[93],"science,":[96],"will":[97,124],"be":[98],"explored.":[99],"aims":[102],"address":[104],"need":[106],"robust":[108],"interpretable":[110],"methods":[111],"modeling":[113],"quantifying":[115],"uncertainty,":[116],"fostering":[117],"decision-making":[119,139],"domains.":[122],"Participants":[123],"have":[125],"opportunity":[127],"share":[129],"research":[130],"findings":[131],"practical":[133],"experiences,":[134],"promoting":[135],"collaboration":[136],"advancing":[138],"practices":[140],"under":[141],"uncertainty.":[142]},"counts_by_year":[],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}