{"id":"https://openalex.org/W2417727035","doi":"https://doi.org/10.1109/tkde.2016.2578315","title":"A Partial Correlation Statistic Structure Learning Algorithm Under Linear Structural Equation Models","display_name":"A Partial Correlation Statistic Structure Learning Algorithm Under Linear Structural Equation Models","publication_year":2016,"publication_date":"2016-06-08","ids":{"openalex":"https://openalex.org/W2417727035","doi":"https://doi.org/10.1109/tkde.2016.2578315","mag":"2417727035"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2016.2578315","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2016.2578315","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-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/A5075949909","display_name":"Jing Yang","orcid":"https://orcid.org/0000-0003-3922-299X"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jing Yang","raw_affiliation_strings":["School of Computer and Information, Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Information, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100651298","display_name":"Ning An","orcid":"https://orcid.org/0000-0003-3317-5299"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning An","raw_affiliation_strings":["School of Computer and Information, Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Information, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076921758","display_name":"Gil Alterovitz","orcid":"https://orcid.org/0000-0002-0495-7059"},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gil Alterovitz","raw_affiliation_strings":["Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA"],"affiliations":[{"raw_affiliation_string":"Center for Biomedical Informatics, Harvard Medical School, 10 Shattuck Street, Boston, MA","institution_ids":["https://openalex.org/I136199984"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5075949909"],"corresponding_institution_ids":["https://openalex.org/I16365422"],"apc_list":null,"apc_paid":null,"fwci":1.7775,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.89164338,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"28","issue":"10","first_page":"2552","last_page":"2565"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9965000152587891,"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":0.9965000152587891,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9789000153541565,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9593999981880188,"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/partial-correlation","display_name":"Partial correlation","score":0.6531009674072266},{"id":"https://openalex.org/keywords/statistic","display_name":"Statistic","score":0.6388585567474365},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6191317439079285},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5159262418746948},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.45769932866096497},{"id":"https://openalex.org/keywords/structural-equation-modeling","display_name":"Structural equation modeling","score":0.41419708728790283},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.3501965403556824},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2389380931854248}],"concepts":[{"id":"https://openalex.org/C64708745","wikidata":"https://www.wikidata.org/wiki/Q2998010","display_name":"Partial correlation","level":3,"score":0.6531009674072266},{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.6388585567474365},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6191317439079285},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5159262418746948},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45769932866096497},{"id":"https://openalex.org/C71104824","wikidata":"https://www.wikidata.org/wiki/Q1476639","display_name":"Structural equation modeling","level":2,"score":0.41419708728790283},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.3501965403556824},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2389380931854248},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2016.2578315","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2016.2578315","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7700343171","display_name":null,"funder_award_id":"61305064","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8890861304","display_name":null,"funder_award_id":"51274078","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W113002869","https://openalex.org/W284239745","https://openalex.org/W1526097585","https://openalex.org/W1550193283","https://openalex.org/W1556652771","https://openalex.org/W1769824028","https://openalex.org/W1840218356","https://openalex.org/W2043505250","https://openalex.org/W2043765379","https://openalex.org/W2052609634","https://openalex.org/W2072917100","https://openalex.org/W2087422107","https://openalex.org/W2092168940","https://openalex.org/W2132507555","https://openalex.org/W2154195147","https://openalex.org/W2320090061","https://openalex.org/W2359002627","https://openalex.org/W2611591252","https://openalex.org/W2797028157","https://openalex.org/W2797618158","https://openalex.org/W2943899430","https://openalex.org/W2946046356","https://openalex.org/W2949597390","https://openalex.org/W3133236490","https://openalex.org/W4302423442","https://openalex.org/W6604573595","https://openalex.org/W6631330034","https://openalex.org/W6632936499","https://openalex.org/W6638112547","https://openalex.org/W6679853467","https://openalex.org/W6700160510"],"related_works":["https://openalex.org/W2562018983","https://openalex.org/W1892569393","https://openalex.org/W2095386159","https://openalex.org/W2358202830","https://openalex.org/W1973051804","https://openalex.org/W2378832745","https://openalex.org/W3111706109","https://openalex.org/W2063178317","https://openalex.org/W2038897217","https://openalex.org/W2165707856"],"abstract_inverted_index":{"A":[0,166],"new":[1],"algorithm,":[2,8],"the":[3,53,59,77,95,101,128,132,139,142,152,160,170],"Partial":[4],"Correlation":[5],"Statistic":[6],"(PCS)":[7],"is":[9,62,69,154],"presented":[10],"for":[11,44],"structure":[12],"learning":[13,89],"under":[14],"linear":[15,28,45,54],"Structural":[16],"Equation":[17],"Models.":[18],"The":[19,109,149],"PCS":[20,78,110,129,171],"algorithm":[21,79,111,130,153,172],"can":[22],"deal":[23],"with":[24,156],"continuous":[25],"data":[26],"following":[27],"arbitrary":[29],"distribution":[30],"rather":[31],"than":[32],"only":[33],"a":[34,73],"Gaussian":[35],"distribution.":[36],"This":[37,98],"paper":[38],"makes":[39],"two":[40],"specific":[41],"contributions.":[42],"First,":[43],"arbitrarily":[46],"distributed":[47],"datasets,":[48],"which":[49],"are":[50],"generated":[51],"by":[52,122],"structural":[55],"equation":[56],"models,":[57],"if":[58],"sample":[60],"size":[61],"sufficiently":[63],"large,":[64],"partial":[65,84,120],"correlation":[66,85,121],"coefficient":[67],"statistic":[68,86,135],"proved":[70],"to":[71,90,115],"follow":[72],"Student's":[74],"t-distribution.":[75],"Second,":[76],"combines":[80],"hypothesis":[81],"testing":[82],"of":[83,94,119,125,141,151,159,178],"and":[87,104,137,181],"local":[88],"select":[91],"potential":[92],"neighbors":[93],"target":[96],"node.":[97],"significantly":[99],"reduces":[100],"search":[102],"space":[103],"achieves":[105],"good":[106],"time":[107,182],"performance.":[108],"does":[112],"not":[113],"need":[114],"choose":[116],"optimal":[117],"threshold":[118],"large":[123],"amount":[124],"experiments.":[126],"Especially,":[127],"redefines":[131],"relevance":[133,140],"from":[134],"theory":[136],"measure":[138],"variables":[143],"based":[144],"on":[145,163,184],"<inline-formula><tex-math":[146],"notation=\"LaTeX\">$p$</tex-math></inline-formula>":[147],"-value.":[148],"effectiveness":[150],"compared":[155],"current":[157],"state":[158],"art":[161],"methods":[162],"seven":[164],"networks.":[165],"simulation":[167],"shows":[168],"that":[169],"outperforms":[173],"existing":[174],"algorithms":[175],"in":[176],"terms":[177],"both":[179],"accuracy":[180],"performance":[183],"average.":[185]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
