{"id":"https://openalex.org/W2740374084","doi":"https://doi.org/10.24963/ijcai.2017/375","title":"Locally Consistent Bayesian Network Scores for Multi-Relational Data","display_name":"Locally Consistent Bayesian Network Scores for Multi-Relational Data","publication_year":2017,"publication_date":"2017-07-28","ids":{"openalex":"https://openalex.org/W2740374084","doi":"https://doi.org/10.24963/ijcai.2017/375","mag":"2740374084"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2017/375","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/375","pdf_url":"https://www.ijcai.org/proceedings/2017/0375.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2017/0375.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026297632","display_name":"Oliver Schulte","orcid":"https://orcid.org/0000-0002-2805-4313"},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"education","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Oliver Schulte","raw_affiliation_strings":["Simon Fraser University, Burnaby, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Simon Fraser University, Burnaby, Canada","institution_ids":["https://openalex.org/I18014758"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053336896","display_name":"Sajjad Gholami","orcid":null},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"education","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Sajjad Gholami","raw_affiliation_strings":["Simon Fraser University, Burnaby, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Simon Fraser University, Burnaby, Canada","institution_ids":["https://openalex.org/I18014758"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I18014758"],"apc_list":null,"apc_paid":null,"fwci":0.6195,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.77074364,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2693","last_page":"2700"},"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/T11719","display_name":"Data Quality and Management","score":0.9868999719619751,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9635000228881836,"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":0.593586266040802},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.557045578956604},{"id":"https://openalex.org/keywords/relational-database","display_name":"Relational database","score":0.5529157519340515},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5001604557037354},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.48199978470802307},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.474173903465271},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4662341773509979},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.46597573161125183},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44980326294898987},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.43805426359176636},{"id":"https://openalex.org/keywords/score","display_name":"Score","score":0.4281979203224182},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.422829270362854},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.41889283061027527},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.413901150226593},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.10203754901885986}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.593586266040802},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.557045578956604},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.5529157519340515},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5001604557037354},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.48199978470802307},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.474173903465271},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4662341773509979},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.46597573161125183},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44980326294898987},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.43805426359176636},{"id":"https://openalex.org/C65660741","wikidata":"https://www.wikidata.org/wiki/Q3952743","display_name":"Score","level":2,"score":0.4281979203224182},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.422829270362854},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.41889283061027527},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.413901150226593},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.10203754901885986},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2017/375","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/375","pdf_url":"https://www.ijcai.org/proceedings/2017/0375.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2017/375","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2017/375","pdf_url":"https://www.ijcai.org/proceedings/2017/0375.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2740374084.pdf","grobid_xml":"https://content.openalex.org/works/W2740374084.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W18223240","https://openalex.org/W73939759","https://openalex.org/W1487588218","https://openalex.org/W1529533208","https://openalex.org/W1535439311","https://openalex.org/W1585529040","https://openalex.org/W1814427248","https://openalex.org/W1959840315","https://openalex.org/W1965552673","https://openalex.org/W1976743651","https://openalex.org/W2002826893","https://openalex.org/W2021754764","https://openalex.org/W2069150044","https://openalex.org/W2073171642","https://openalex.org/W2114157818","https://openalex.org/W2126185296","https://openalex.org/W2135209143","https://openalex.org/W2138949658","https://openalex.org/W2144907232","https://openalex.org/W2168865746","https://openalex.org/W2221230328","https://openalex.org/W2243132409","https://openalex.org/W2270062199","https://openalex.org/W2401098482","https://openalex.org/W2401131346","https://openalex.org/W2540540486","https://openalex.org/W2587177616","https://openalex.org/W2623293810","https://openalex.org/W2952047749","https://openalex.org/W3103377809","https://openalex.org/W3112180085","https://openalex.org/W4250143236","https://openalex.org/W4250685163"],"related_works":["https://openalex.org/W2069592018","https://openalex.org/W2075740387","https://openalex.org/W2358990940","https://openalex.org/W2093931120","https://openalex.org/W2329812990","https://openalex.org/W2349116365","https://openalex.org/W3021708704","https://openalex.org/W2004231473","https://openalex.org/W2527777278","https://openalex.org/W3095784589"],"abstract_inverted_index":{"An":[0],"important":[1],"task":[2],"for":[3,39,47,56,99,110,124],"relational":[4,111,125,172],"learning":[5,17],"is":[6,18,96,107,119,134,159,179],"Bayesian":[7],"network":[8],"(BN)":[9],"structure":[10,16,126],"learning.":[11,127],"A":[12,128],"fundamental":[13],"component":[14],"of":[15,131,162],"a":[19,27,30,34,42,92,136,144,156,160,163,194],"model":[20,28,93,165],"selection":[21,94],"score":[22,45,95,157],"that":[23,37,55,66,74,90,140,158,175],"measures":[24],"how":[25],"well":[26],"fits":[29],"dataset.":[31],"We":[32],"describe":[33],"new":[35],"method":[36],"upgrades":[38],"multi-relational":[40],"databases,":[41],"log-linear":[43],"BN":[44,60,149,191],"designed":[46],"single-table":[48],"i.i.d.":[49,57,100],"data.":[50],"Chickering":[51],"and":[52],"Meek":[53],"showed":[54],"data,":[58,101],"standard":[59],"scores":[61],"are":[62],"locally":[63,97,108],"consistent,":[64],"meaning":[65],"their":[67],"maxima":[68],"converge":[69],"to":[70],"an":[71,147],"optimal":[72],"model,":[73],"represents":[75],"the":[76,120],"data":[77,112,186,196],"generating":[78],"distribution":[79],"{\\em":[80,137],"and}":[81],"contains":[82],"no":[83],"redundant":[84],"edges.":[85],"Our":[86],"main":[87],"theorem":[88],"establishes":[89],"if":[91],"consistent":[98,109],"then":[102],"our":[103,116,132,176],"upgraded":[104],"gain":[105,138,177],"function":[106,161,178],"as":[113],"well.":[114],"To":[115],"knowledge":[117],"this":[118],"first":[121],"consistency":[122],"result":[123],"novel":[129],"aspect":[130],"approach":[133],"employing":[135],"function}":[139],"compares":[141],"two":[142],"models:":[143],"current":[145],"vs.":[146],"alternative":[148],"structure.":[150],"In":[151],"contrast,":[152],"previous":[153],"approaches":[154],"employed":[155],"single":[164],"only.":[166],"Empirical":[167],"evaluation":[168],"on":[169],"six":[170],"benchmark":[171],"databases":[173],"shows":[174],"also":[180],"practically":[181],"useful:":[182],"On":[183],"realistic":[184],"size":[185],"sets,":[187],"it":[188],"selects":[189],"informative":[190],"structures":[192],"with":[193],"better":[195],"fit":[197],"than":[198],"those":[199],"selected":[200],"by":[201],"baseline":[202],"single-model":[203],"scores.":[204]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}