{"id":"https://openalex.org/W1990396763","doi":"https://doi.org/10.4236/jilsa.2010.23019","title":"Knowledge Discovery for Query Formulation for Validation of a Bayesian Belief Network","display_name":"Knowledge Discovery for Query Formulation for Validation of a Bayesian Belief Network","publication_year":2010,"publication_date":"2010-01-01","ids":{"openalex":"https://openalex.org/W1990396763","doi":"https://doi.org/10.4236/jilsa.2010.23019","mag":"1990396763"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.4236/jilsa.2010.23019","pdf_url":"http://www.scirp.org/journal/PaperDownload.aspx?paperID=2548","source":{"id":"https://openalex.org/S4210234112","display_name":"Journal of Intelligent Learning Systems and Applications","issn_l":"2150-8402","issn":["2150-8402","2150-8410"],"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":true,"host_organization":"https://openalex.org/P4310320480","host_organization_name":"Scientific Research Publishing","host_organization_lineage":["https://openalex.org/P4310320480"],"host_organization_lineage_names":["Scientific Research Publishing"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"journal-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"http://www.scirp.org/journal/PaperDownload.aspx?paperID=2548","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018680547","display_name":"G\u00fcrsel Serpen","orcid":"https://orcid.org/0000-0001-9005-5483"},"institutions":[{"id":"https://openalex.org/I90871651","display_name":"University of Toledo","ror":"https://ror.org/01pbdzh19","country_code":"US","type":"funder","lineage":["https://openalex.org/I90871651"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gursel Serpen","raw_affiliation_strings":["University of Toledo"],"affiliations":[{"raw_affiliation_string":"University of Toledo","institution_ids":["https://openalex.org/I90871651"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023382357","display_name":"Michael Riesen","orcid":null},"institutions":[{"id":"https://openalex.org/I90871651","display_name":"University of Toledo","ror":"https://ror.org/01pbdzh19","country_code":"US","type":"funder","lineage":["https://openalex.org/I90871651"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Riesen","raw_affiliation_strings":["Electrical Engineering and Computer Science, College of Engineering, University of Toledo; School of Law, University of Toledo, Toledo, USA."],"affiliations":[{"raw_affiliation_string":"Electrical Engineering and Computer Science, College of Engineering, University of Toledo; School of Law, University of Toledo, Toledo, USA.","institution_ids":["https://openalex.org/I90871651"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.395,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":1,"citation_normalized_percentile":{"value":0.569751,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":64,"max":71},"biblio":{"volume":"02","issue":"03","first_page":"156","last_page":"166"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9997,"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":0.9997,"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":0.9936,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9929,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8631289},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.6830973},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5559916},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5522961},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.54686314},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.50857484},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.50576687},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.49891162},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47626325},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47369456},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4514139},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.43763292},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2694037},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":true,"landing_page_url":"https://doi.org/10.4236/jilsa.2010.23019","pdf_url":"http://www.scirp.org/journal/PaperDownload.aspx?paperID=2548","source":{"id":"https://openalex.org/S4210234112","display_name":"Journal of Intelligent Learning Systems and Applications","issn_l":"2150-8402","issn":["2150-8402","2150-8410"],"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":true,"host_organization":"https://openalex.org/P4310320480","host_organization_name":"Scientific Research Publishing","host_organization_lineage":["https://openalex.org/P4310320480"],"host_organization_lineage_names":["Scientific Research Publishing"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.4236/jilsa.2010.23019","pdf_url":"http://www.scirp.org/journal/PaperDownload.aspx?paperID=2548","source":{"id":"https://openalex.org/S4210234112","display_name":"Journal of Intelligent Learning Systems and Applications","issn_l":"2150-8402","issn":["2150-8402","2150-8410"],"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":false,"is_core":true,"host_organization":"https://openalex.org/P4310320480","host_organization_name":"Scientific Research Publishing","host_organization_lineage":["https://openalex.org/P4310320480"],"host_organization_lineage_names":["Scientific Research Publishing"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[{"display_name":"Peace, justice, and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.73}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":23,"referenced_works":["https://openalex.org/W1484413656","https://openalex.org/W1492149280","https://openalex.org/W1503703685","https://openalex.org/W1514470448","https://openalex.org/W1528113134","https://openalex.org/W1570448133","https://openalex.org/W1573686114","https://openalex.org/W1573742539","https://openalex.org/W1576271900","https://openalex.org/W1577577882","https://openalex.org/W1670263352","https://openalex.org/W1983690667","https://openalex.org/W2019262216","https://openalex.org/W2045487373","https://openalex.org/W2066796977","https://openalex.org/W2096242147","https://openalex.org/W2107110014","https://openalex.org/W2125055259","https://openalex.org/W2142245294","https://openalex.org/W2164551395","https://openalex.org/W2166103330","https://openalex.org/W2170112109","https://openalex.org/W2966207845"],"related_works":["https://openalex.org/W3213252596","https://openalex.org/W2560191017","https://openalex.org/W2368237856","https://openalex.org/W2348892528","https://openalex.org/W2158321484","https://openalex.org/W2149300931","https://openalex.org/W1734881440","https://openalex.org/W1649619740","https://openalex.org/W1583422155","https://openalex.org/W1534006406"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"machine":[3,68],"learning":[4,69],"techniques":[5],"to":[6,61,73,109,132,138],"discover":[7,74],"knowledge":[8,75],"in":[9,12,76,82,193,209],"a":[10,27,67,111,162,203],"dataset":[11],"the":[13,19,33,42,63,77,83,87,139,145,151,165,185,196,213],"form":[14,78],"of":[15,21,26,32,53,79,99,115,122,150,195,202],"if-then":[16,80,100],"rules":[17,81,101,126],"for":[18,24,135,200,212,215],"purpose":[20],"formulating":[22],"queries":[23,131],"validation":[25,93,136,201],"Bayesian":[28,88,140],"belief":[29,89,141],"network":[30,90,142],"model":[31,91],"same":[34,146],"data.":[35],"Although":[36],"do-main":[37],"expertise":[38,108],"is":[39,46,56,71,127,188],"often":[40],"available,":[41],"query":[43,54,64,197],"formulation":[44,55,65,198],"task":[45],"tedious":[47],"and":[48,50,104,117,124,175,190,219],"laborious,":[49],"hence":[51],"automation":[52],"desirable.":[57],"In":[58],"an":[59,157],"effort":[60],"automate":[62],"process,":[66],"algorithm":[70],"lev-eraged":[72],"data":[84,179],"from":[85,144],"which":[86,170,207],"under":[92],"was":[94,154],"also":[95],"induced.":[96],"The":[97,120,148,181],"set":[98],"are":[102],"processed":[103],"filtered":[105],"through":[106,156],"domain":[107],"identify":[110],"subset":[112,121],"that":[113,184],"consists":[114],"\u201cinteresting\u201d":[116],"\u201csignificant\u201d":[118],"rules.":[119],"interesting":[123],"significant":[125],"formulated":[128],"into":[129],"corresponding":[130],"be":[133],"posed,":[134],"purposes,":[137],"induced":[143],"dataset.":[147],"promise":[149],"proposed":[152,186],"methodology":[153],"assessed":[155],"empirical":[158],"study":[159,182],"performed":[160],"on":[161],"real-life":[163],"dataset,":[164],"National":[166],"Crime":[167],"Victimization":[168],"Survey,":[169],"has":[171],"over":[172,177],"250":[173],"attributes":[174],"well":[176],"200,000":[178],"points.":[180],"demonstrated":[183],"approach":[187],"feasible":[189],"provides":[191],"automation,":[192],"part,":[194],"process":[199],"complex":[204],"probabilistic":[205],"model,":[206],"culminates":[208],"substantial":[210],"savings":[211],"need":[214],"human":[216],"expert":[217],"involvement":[218],"investment.":[220]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W1990396763","counts_by_year":[{"year":2012,"cited_by_count":1}],"updated_date":"2025-03-21T22:27:41.433084","created_date":"2016-06-24"}