{"id":"https://openalex.org/W4415368909","doi":"https://doi.org/10.1109/isit63088.2025.11195287","title":"Improved Community Recovery via Exact Matching in Correlated Contextual Stochastic Block Models","display_name":"Improved Community Recovery via Exact Matching in Correlated Contextual Stochastic Block Models","publication_year":2025,"publication_date":"2025-06-22","ids":{"openalex":"https://openalex.org/W4415368909","doi":"https://doi.org/10.1109/isit63088.2025.11195287"},"language":null,"primary_location":{"id":"doi:10.1109/isit63088.2025.11195287","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit63088.2025.11195287","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Symposium on Information Theory (ISIT)","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/A5111074275","display_name":"Joonhyuk Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Joonhyuk Yang","raw_affiliation_strings":["School of Electrical Engineering, KAIST"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, KAIST","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101685956","display_name":"Hye Won Chung","orcid":"https://orcid.org/0000-0002-6162-9158"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hye Won Chung","raw_affiliation_strings":["School of Electrical Engineering, KAIST"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, KAIST","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5111074275"],"corresponding_institution_ids":["https://openalex.org/I157485424"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.29967264,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9775000214576721,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9775000214576721,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.9717000126838684,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9513000249862671,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/stochastic-block-model","display_name":"Stochastic block model","score":0.766700029373169},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6218000054359436},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5917999744415283},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5169000029563904},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5108000040054321},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5054000020027161},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5001000165939331},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.3953000009059906},{"id":"https://openalex.org/keywords/community-structure","display_name":"Community structure","score":0.3441999852657318}],"concepts":[{"id":"https://openalex.org/C2779982251","wikidata":"https://www.wikidata.org/wiki/Q25053762","display_name":"Stochastic block model","level":3,"score":0.766700029373169},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6218000054359436},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5963000059127808},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5917999744415283},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5169000029563904},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5108000040054321},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5054000020027161},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5001000165939331},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.48899999260902405},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42250001430511475},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.3953000009059906},{"id":"https://openalex.org/C133079900","wikidata":"https://www.wikidata.org/wiki/Q5155065","display_name":"Community structure","level":2,"score":0.3441999852657318},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3402999937534332},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.3239000141620636},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.3190999925136566},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.31779998540878296},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31049999594688416},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.30390000343322754},{"id":"https://openalex.org/C159246509","wikidata":"https://www.wikidata.org/wiki/Q5428725","display_name":"Factor graph","level":3,"score":0.29989999532699585},{"id":"https://openalex.org/C47458327","wikidata":"https://www.wikidata.org/wiki/Q910404","display_name":"Random graph","level":3,"score":0.2930000126361847},{"id":"https://openalex.org/C61455927","wikidata":"https://www.wikidata.org/wiki/Q1030529","display_name":"Blossom algorithm","level":3,"score":0.2847000062465668},{"id":"https://openalex.org/C159254197","wikidata":"https://www.wikidata.org/wiki/Q1144915","display_name":"Lexicographical order","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.28060001134872437},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C114713312","wikidata":"https://www.wikidata.org/wiki/Q7551269","display_name":"Social network analysis","level":3,"score":0.273499995470047},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.27309998869895935},{"id":"https://openalex.org/C2993597952","wikidata":"https://www.wikidata.org/wiki/Q108123644","display_name":"Block model","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26269999146461487}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit63088.2025.11195287","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit63088.2025.11195287","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1439843266","display_name":null,"funder_award_id":"RS-2024-00408003 and RS-2025-00516153","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2102907934","https://openalex.org/W2219655028","https://openalex.org/W2559839022","https://openalex.org/W2942673878","https://openalex.org/W2963264680","https://openalex.org/W3127515714","https://openalex.org/W4206709057","https://openalex.org/W4230781844","https://openalex.org/W4293483898","https://openalex.org/W4386075190","https://openalex.org/W4388666957","https://openalex.org/W4401692931"],"related_works":[],"abstract_inverted_index":{"We":[0],"study":[1],"community":[2,69,121,147],"detection":[3,122],"in":[4,19,125],"multiple":[5],"networks":[6],"whose":[7],"nodes":[8,62,85,101],"and":[9,29,43,114,146],"edges":[10],"are":[11,71],"jointly":[12],"correlated,":[13],"a":[14,57,79,126],"scenario":[15],"that":[16,82],"arises":[17],"naturally":[18],"social":[20],"platforms.":[21],"Extending":[22],"the":[23,36,97,150],"classical":[24],"Stochastic":[25],"Block":[26],"Model":[27],"(SBM)":[28],"its":[30],"contextual":[31],"counterpart":[32],"(CSBM),":[33],"we":[34,49,77,117],"introduce":[35],"correlated":[37,52,75,136],"CSBMs,":[38,76],"which":[39],"incorporates":[40],"both":[41],"structural":[42],"attribute":[44],"correlations.":[45],"To":[46],"build":[47],"intuition,":[48],"first":[50],"analyze":[51],"Gaussian":[53],"Mixture":[54],"Models,":[55],"where":[56,120],"distance-based":[58],"estimator":[59],"can":[60],"align":[61],"across":[63],"graphs":[64,137],"(without":[65],"edges)":[66],"even":[67],"when":[68,132],"labels":[70],"initially":[72],"unknown.":[73],"For":[74],"develop":[78],"two-step":[80],"procedure":[81],"matches":[83],"most":[84],"via":[86],"<tex":[87],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[88],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$k$</tex>-core":[89],"matching":[90,98,145],"based":[91],"on":[92,152],"edge":[93],"information,":[94],"then":[95],"refines":[96],"for":[99],"remaining":[100],"by":[102],"leveraging":[103],"their":[104],"attributes,":[105],"enabling":[106],"perfect":[107],"alignment":[108],"under":[109],"suitable":[110],"conditions.":[111],"By":[112],"aligning":[113],"combining":[115],"graphs,":[116],"identify":[118],"regimes":[119],"is":[123,138],"infeasible":[124],"single":[127],"graph":[128,144],"but":[129],"becomes":[130],"possible":[131],"side":[133],"information":[134],"from":[135],"incorporated,":[139],"illustrating":[140],"how":[141],"interplay":[142],"between":[143],"recovery":[148],"enhances":[149],"inference":[151],"graphs.":[153]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-21T00:00:00"}