{"id":"https://openalex.org/W2792749098","doi":"https://doi.org/10.1145/3161885","title":"Tied Kronecker Product Graph Models to Capture Variance in Network Populations","display_name":"Tied Kronecker Product Graph Models to Capture Variance in Network Populations","publication_year":2018,"publication_date":"2018-03-23","ids":{"openalex":"https://openalex.org/W2792749098","doi":"https://doi.org/10.1145/3161885","mag":"2792749098"},"language":"en","primary_location":{"id":"doi:10.1145/3161885","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3161885","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","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/A5060132668","display_name":"Sebasti\u00e1n Moreno","orcid":"https://orcid.org/0000-0001-5422-0656"},"institutions":[{"id":"https://openalex.org/I21067949","display_name":"Adolfo Ib\u00e1\u00f1ez University","ror":"https://ror.org/0326knt82","country_code":"CL","type":"education","lineage":["https://openalex.org/I21067949"]}],"countries":["CL"],"is_corresponding":false,"raw_author_name":"Sebastian Moreno","raw_affiliation_strings":["Universidad Adolfo Iba\u00f1ez"],"raw_orcid":"https://orcid.org/0000-0001-5422-0656","affiliations":[{"raw_affiliation_string":"Universidad Adolfo Iba\u00f1ez","institution_ids":["https://openalex.org/I21067949"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064439579","display_name":"Jennifer Neville","orcid":"https://orcid.org/0000-0001-8108-4899"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jennifer Neville","raw_affiliation_strings":["Purdue University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079050185","display_name":"Sergey Kirshner","orcid":null},"institutions":[{"id":"https://openalex.org/I2252078561","display_name":"Meta (Israel)","ror":"https://ror.org/02388em19","country_code":"IL","type":"company","lineage":["https://openalex.org/I2252078561","https://openalex.org/I4210114444"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Sergey Kirshner","raw_affiliation_strings":["Facebook, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Facebook, Inc","institution_ids":["https://openalex.org/I2252078561"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0366,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.75556259,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"12","issue":"3","first_page":"1","last_page":"40"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9998999834060669,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9878000020980835,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9732999801635742,"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/kronecker-product","display_name":"Kronecker product","score":0.7086927890777588},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6208290457725525},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5449466109275818},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.47741711139678955},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4727017879486084},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4662766754627228},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.4334830343723297},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4275825023651123},{"id":"https://openalex.org/keywords/network-analysis","display_name":"Network analysis","score":0.4125930368900299},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39132827520370483},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.3564341962337494},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3054354786872864},{"id":"https://openalex.org/keywords/kronecker-delta","display_name":"Kronecker delta","score":0.2802474796772003},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23803886771202087}],"concepts":[{"id":"https://openalex.org/C46030957","wikidata":"https://www.wikidata.org/wiki/Q1238125","display_name":"Kronecker product","level":3,"score":0.7086927890777588},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6208290457725525},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5449466109275818},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.47741711139678955},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4727017879486084},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4662766754627228},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.4334830343723297},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4275825023651123},{"id":"https://openalex.org/C32946077","wikidata":"https://www.wikidata.org/wiki/Q618079","display_name":"Network analysis","level":2,"score":0.4125930368900299},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39132827520370483},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.3564341962337494},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3054354786872864},{"id":"https://openalex.org/C39482219","wikidata":"https://www.wikidata.org/wiki/Q192826","display_name":"Kronecker delta","level":2,"score":0.2802474796772003},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23803886771202087},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3161885","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3161885","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.46000000834465027,"id":"https://metadata.un.org/sdg/12","display_name":"Responsible consumption and production"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W618612974","https://openalex.org/W753235638","https://openalex.org/W1482192857","https://openalex.org/W1588530906","https://openalex.org/W1985093013","https://openalex.org/W1985339741","https://openalex.org/W1986261925","https://openalex.org/W1989747348","https://openalex.org/W2004009890","https://openalex.org/W2005747881","https://openalex.org/W2008620264","https://openalex.org/W2020385058","https://openalex.org/W2027377866","https://openalex.org/W2028314260","https://openalex.org/W2057010485","https://openalex.org/W2057444638","https://openalex.org/W2069639863","https://openalex.org/W2076844992","https://openalex.org/W2098290609","https://openalex.org/W2102907934","https://openalex.org/W2112090702","https://openalex.org/W2112681514","https://openalex.org/W2115579680","https://openalex.org/W2128252562","https://openalex.org/W2135838082","https://openalex.org/W2136676173","https://openalex.org/W2148606196","https://openalex.org/W2153204928","https://openalex.org/W2165132717","https://openalex.org/W2172067437","https://openalex.org/W3004555699","https://openalex.org/W3102855359","https://openalex.org/W3103560620","https://openalex.org/W3142570770","https://openalex.org/W3143219376","https://openalex.org/W4234057457","https://openalex.org/W4312512934","https://openalex.org/W6677111876"],"related_works":["https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W2280377497","https://openalex.org/W4387506531","https://openalex.org/W3174044702","https://openalex.org/W4238433571","https://openalex.org/W2967848559","https://openalex.org/W4283803360"],"abstract_inverted_index":{"Much":[0],"of":[1,17,33,35,45,67,110,120,149],"the":[2,14,31,42,60,78,100,118,121,126,147,156],"past":[3],"work":[4],"on":[5,12],"mining":[6],"and":[7,63],"modeling":[8],"networks":[9,87],"has":[10],"focused":[11],"understanding":[13],"observed":[15,84],"properties":[16,44,83],"single":[18],"example":[19],"graphs.":[20,36],"However,":[21],"in":[22,81,129,159],"many":[23],"real-life":[24],"applications":[25],"it":[26],"is":[27],"important":[28],"to":[29,116,134],"characterize":[30],"structure":[32],"populations":[34],"In":[37],"this":[38],"work,":[39],"we":[40,71,98],"analyze":[41],"distributional":[43],"probabilistic":[46],"generative":[47],"graph":[48,82,137],"models":[49],"(PGGMs)":[50],"for":[51],"network":[52,61,160],"populations.":[53],"PGGMs":[54,75],"are":[55],"statistical":[56],"methods":[57],"that":[58,73,112,142],"model":[59],"distribution":[62],"match":[64],"common":[65],"characteristics":[66,148],"real-world":[68,150],"networks.":[69],"Specifically,":[70],"show":[72,141],"most":[74],"cannot":[76],"reflect":[77],"natural":[79,157],"variability":[80,119,158],"across":[85],"multiple":[86],"because":[88],"their":[89],"edge":[90,127],"generation":[91],"process":[92],"assumes":[93],"independence":[94],"among":[95],"edges.":[96],"Then,":[97],"propose":[99],"mixed":[101],"Kronecker":[102],"Product":[103],"Graph":[104],"Model":[105],"(mKPGM),":[106],"a":[107],"scalable":[108],"generalization":[109],"KPGMs":[111],"uses":[113],"tied":[114],"parameters":[115],"increase":[117],"sampled":[122],"networks,":[123,151],"while":[124,152],"preserving":[125],"probabilities":[128],"expectation.":[130],"We":[131],"compare":[132],"mKPGM":[133],"several":[135],"other":[136],"models.":[138],"The":[139],"results":[140],"learned":[143],"mKPGMs":[144],"accurately":[145],"represent":[146],"also":[153],"effectively":[154],"capturing":[155],"structure.":[161]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}