{"id":"https://openalex.org/W2018364180","doi":"https://doi.org/10.1109/ciss.2014.6814173","title":"Subjective confidence and source reliability in soft data fusion","display_name":"Subjective confidence and source reliability in soft data fusion","publication_year":2014,"publication_date":"2014-03-01","ids":{"openalex":"https://openalex.org/W2018364180","doi":"https://doi.org/10.1109/ciss.2014.6814173","mag":"2018364180"},"language":"en","primary_location":{"id":"doi:10.1109/ciss.2014.6814173","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ciss.2014.6814173","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 48th Annual Conference on Information Sciences and Systems (CISS)","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/A5091062384","display_name":"Donald J. Bucci","orcid":"https://orcid.org/0000-0002-7500-5768"},"institutions":[{"id":"https://openalex.org/I72816309","display_name":"Drexel University","ror":"https://ror.org/04bdffz58","country_code":"US","type":"education","lineage":["https://openalex.org/I72816309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Donald J. Bucci","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Drexel University, Philadelphia, Pennsylvania","Department of Electrical and Computer Engineering, Drexel University, Philadelphia, Pennsylvania, 19104-2816, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Drexel University, Philadelphia, Pennsylvania","institution_ids":["https://openalex.org/I72816309"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Drexel University, Philadelphia, Pennsylvania, 19104-2816, USA","institution_ids":["https://openalex.org/I72816309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070824862","display_name":"Sayandeep Acharya","orcid":"https://orcid.org/0000-0002-9745-5276"},"institutions":[{"id":"https://openalex.org/I72816309","display_name":"Drexel University","ror":"https://ror.org/04bdffz58","country_code":"US","type":"education","lineage":["https://openalex.org/I72816309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sayandeep Acharya","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Drexel University, Philadelphia, Pennsylvania","Department of Electrical and Computer Engineering, Drexel University, Philadelphia, Pennsylvania, 19104-2816, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Drexel University, Philadelphia, Pennsylvania","institution_ids":["https://openalex.org/I72816309"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Drexel University, Philadelphia, Pennsylvania, 19104-2816, USA","institution_ids":["https://openalex.org/I72816309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041381906","display_name":"Timothy J. Pleskac","orcid":"https://orcid.org/0000-0001-5761-1900"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Timothy J. Pleskac","raw_affiliation_strings":["Psychology Department, Michigan State University, East Lansing, Michigan","Psychology Department, Michigan State University, East Lansing, 48824-3407, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Psychology Department, Michigan State University, East Lansing, Michigan","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Psychology Department, Michigan State University, East Lansing, 48824-3407, USA","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047426159","display_name":"Moshe Kam","orcid":"https://orcid.org/0000-0001-7117-1593"},"institutions":[{"id":"https://openalex.org/I72816309","display_name":"Drexel University","ror":"https://ror.org/04bdffz58","country_code":"US","type":"education","lineage":["https://openalex.org/I72816309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Moshe Kam","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Drexel University, Philadelphia, Pennsylvania","Department of Electrical and Computer Engineering, Drexel University, Philadelphia, Pennsylvania, 19104-2816, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Drexel University, Philadelphia, Pennsylvania","institution_ids":["https://openalex.org/I72816309"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Drexel University, Philadelphia, Pennsylvania, 19104-2816, USA","institution_ids":["https://openalex.org/I72816309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7995,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.86626364,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"3","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9901999831199646,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9872999787330627,"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/confidence-interval","display_name":"Confidence interval","score":0.5849487781524658},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5706101059913635},{"id":"https://openalex.org/keywords/replicate","display_name":"Replicate","score":0.4905204176902771},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.490242063999176},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4791485667228699},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.46385642886161804},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.4562858045101166},{"id":"https://openalex.org/keywords/subject","display_name":"Subject (documents)","score":0.4501096308231354},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40735435485839844},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3928760588169098},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30424976348876953},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.23243412375450134}],"concepts":[{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.5849487781524658},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5706101059913635},{"id":"https://openalex.org/C2781162219","wikidata":"https://www.wikidata.org/wiki/Q26250693","display_name":"Replicate","level":2,"score":0.4905204176902771},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.490242063999176},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4791485667228699},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.46385642886161804},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.4562858045101166},{"id":"https://openalex.org/C2777855551","wikidata":"https://www.wikidata.org/wiki/Q12310021","display_name":"Subject (documents)","level":2,"score":0.4501096308231354},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40735435485839844},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3928760588169098},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30424976348876953},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.23243412375450134},{"id":"https://openalex.org/C161191863","wikidata":"https://www.wikidata.org/wiki/Q199655","display_name":"Library science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ciss.2014.6814173","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ciss.2014.6814173","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 48th Annual Conference on Information Sciences and Systems (CISS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.5799999833106995,"id":"https://metadata.un.org/sdg/16"},{"display_name":"Reduced inequalities","score":0.41999998688697815,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1490145800","https://openalex.org/W1500551892","https://openalex.org/W1512780188","https://openalex.org/W1524122080","https://openalex.org/W1565231976","https://openalex.org/W1764120778","https://openalex.org/W1981031086","https://openalex.org/W2002397801","https://openalex.org/W2004215803","https://openalex.org/W2004265177","https://openalex.org/W2017541195","https://openalex.org/W2021078113","https://openalex.org/W2038420319","https://openalex.org/W2048196003","https://openalex.org/W2073241381","https://openalex.org/W2096088275","https://openalex.org/W2106106899","https://openalex.org/W2112262428","https://openalex.org/W2139580021","https://openalex.org/W2142879169","https://openalex.org/W2146443948","https://openalex.org/W2158389550","https://openalex.org/W2162289206","https://openalex.org/W2165075905","https://openalex.org/W2292561230","https://openalex.org/W2311097431","https://openalex.org/W2335368887","https://openalex.org/W2797148637","https://openalex.org/W4301347335","https://openalex.org/W6631630011","https://openalex.org/W6637732757","https://openalex.org/W6674447700"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W4254851101","https://openalex.org/W3171007296","https://openalex.org/W22115721","https://openalex.org/W2321234655","https://openalex.org/W2065444835","https://openalex.org/W4394550905","https://openalex.org/W2952773340","https://openalex.org/W2470062578","https://openalex.org/W2981861370"],"abstract_inverted_index":{"There":[0],"is":[1,31],"ongoing":[2],"interest":[3],"in":[4,66,231],"constructing":[5],"data":[6],"fusion":[7,73,100,157,185,189,238],"systems":[8],"which":[9,30,191,212],"are":[10],"capable":[11],"of":[12,49,53,72,133,145,150,155,180,194,215,237,266,271],"using":[13],"human":[14,54,57],"(i.e.,":[15,200,218,245],"soft)":[16],"decisions":[17,80,92,107,195,243],"and":[18,39,43,56,63,93,98,108,113,120,129,147,196,221,257],"confidence":[19,58,109,127,136,197],"assessments":[20,110,198],"as":[21,82,263],"inputs.":[22],"Most":[23],"relevant":[24],"studies":[25],"involved":[26],"experimentation":[27],"with":[28],"humans":[29],"often":[32],"expensive,":[33],"subject":[34,91,106,125,216],"to":[35,41,68,159,235],"strict":[36],"institutional":[37],"regulations,":[38],"hard":[40],"validate":[42],"replicate.":[44],"Here":[45],"we":[46],"make":[47],"use":[48,78,90,105,124,193,214],"a":[50],"mathematical":[51],"model":[52],"decision-making":[55],"assessment":[59],"developed":[60],"by":[61,165,183,255],"Pleskac":[62,256],"Busemeyer":[64],"(2010)":[65],"order":[67],"compare":[69],"four":[70],"types":[71,219],"operators:":[74],"(1)":[75],"operators":[76,88,103,122,190],"that":[77,89,104,123,240,262],"human-subject":[79],"(such":[81],"the":[83,114,130,139,167,171,178,184,204,249,264,269],"k-out-of-N":[84],"majority":[85],"rule);":[86,101],"(2)":[87,220],"error":[94],"rates":[95],"(the":[96],"Chair":[97],"Varshney":[99],"(3)":[102],"(Yager's":[111],"rule":[112,118,144,149],"Proportional":[115],"Conflict":[116],"Redistribution":[117],"#5);":[119],"(4)":[121],"decisions,":[126],"assessments,":[128],"average":[131,140],"strength":[132],"each":[134,156],"subject's":[135],"assessment,":[137],"namely":[138],"Brier":[141],"scores":[142],"(Dempster's":[143],"combination":[146],"Bayes'":[148],"probability":[151],"combination).":[152],"The":[153],"ability":[154],"system":[158],"discriminate":[160],"between":[161],"alternatives":[162],"was":[163],"determined":[164],"computing":[166],"normalized":[168,208,227],"area":[169],"under":[170],"receiver":[172],"operating":[173],"characteristic":[174],"curves":[175],"(AUC).":[176],"When":[177],"number":[179,265],"sources":[181,267],"used":[182],"algorithm":[186],"exceeded":[187],"five,":[188],"made":[192,213],"alone":[199,244],"type":[201,246],"(3))":[202],"produced":[203,223],"lowest":[205],"(namely,":[206,225],"worst)":[207],"AUC":[209,228],"values.":[210],"Operators":[211],"reliabilities":[217],"(4))":[222],"larger":[224],"better)":[226],"values":[229],"which,":[230],"addition,":[232],"were":[233],"similar":[234],"those":[236],"algorithms":[239],"relied":[241],"on":[242],"(1)).":[247],"For":[248],"city":[250],"size":[251],"discrimination":[252],"task":[253],"studied":[254],"Busmeyer,":[258],"these":[259],"results":[260],"suggest":[261],"increases,":[268],"importance":[270],"decision":[272],"self-assessment":[273],"diminishes.":[274]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
