{"id":"https://openalex.org/W7124258656","doi":"https://doi.org/10.1080/00031305.2026.2730356","title":"Graph Canonical Coherence Analysis","display_name":"Graph Canonical Coherence Analysis","publication_year":2026,"publication_date":"2026-09-08","ids":{"openalex":"https://openalex.org/W7124258656","doi":"https://doi.org/10.1080/00031305.2026.2730356"},"language":"en","primary_location":{"id":"doi:10.1080/00031305.2026.2730356","doi":"https://doi.org/10.1080/00031305.2026.2730356","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00031305.2026.2730356","pdf_url":null,"source":{"id":"https://openalex.org/S4179095","display_name":"The American Statistician","issn_l":"0003-1305","issn":["0003-1305","1537-2731"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-b","anvur-scientific","cwts-core","dongbi-b","doyens","jufo-1","ki-jl-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The American Statistician","raw_type":"journal-article"},"parent_works":[],"lineage":["https://openalex.org/W7124258656"],"child_works_count":0,"type":"article","is_traditional":true,"indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2601.09038","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002536452","display_name":"Kyusoon Kim","orcid":"https://orcid.org/0000-0002-9035-1474","observed_orcids":["https://orcid.org/0000-0002-9035-1474"]},"institutions":[{"id":"https://openalex.org/I141371507","display_name":"Soongsil University","ror":"https://ror.org/017xnm587","country_code":"KR","type":"education","lineage":["https://openalex.org/I141371507"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kyusoon Kim","raw_affiliation_strings":["Department of Statistics and Actuarial Science, Soongsil University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics and Actuarial Science, Soongsil University","institution_ids":["https://openalex.org/I141371507"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032931435","display_name":"Hee\u2010Seok Oh","orcid":"https://orcid.org/0000-0002-1501-0530","observed_orcids":["https://orcid.org/0000-0002-1501-0530"]},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hee-Seok Oh","raw_affiliation_strings":["Department of Statistics, Seoul National University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, Seoul National University","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5032931435"],"corresponding_institution_ids":["https://openalex.org/I139264467"],"apc_list":null,"apc_paid":null,"fwci":1.3951,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.80881696,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.8999000191688538,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.8999000191688538,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.019700000062584877,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T12536","display_name":"Topological and Geometric Data Analysis","score":0.014600000344216824,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/graph-signal-processing","display_name":"graph signal processing","score":0.6119999885559082},{"id":"https://openalex.org/keywords/g20","display_name":"G20","score":0.9950000047683716}],"concepts":[{"id":"https://openalex.org/C153874254","wikidata":"https://www.wikidata.org/wiki/Q115542","display_name":"Canonical correlation","level":2,"score":0.7246999740600586},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6553999781608582},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.5692999958992004},{"id":"https://openalex.org/C106937863","wikidata":"https://www.wikidata.org/wiki/Q7236518","display_name":"Power graph analysis","level":3,"score":0.4620000123977661},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4521999955177307},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.43939998745918274},{"id":"https://openalex.org/C75806538","wikidata":"https://www.wikidata.org/wiki/Q5033360","display_name":"Canonical analysis","level":2,"score":0.4359000027179718},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.41589999198913574},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.4009000062942505},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4002000093460083},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39320001006126404},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37310001254081726},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.32409998774528503},{"id":"https://openalex.org/C74003402","wikidata":"https://www.wikidata.org/wiki/Q3180727","display_name":"Spectral graph theory","level":5,"score":0.3215000033378601},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31299999356269836},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.3070000112056732},{"id":"https://openalex.org/C64339825","wikidata":"https://www.wikidata.org/wiki/Q722659","display_name":"Graph property","level":5,"score":0.29490000009536743},{"id":"https://openalex.org/C19332903","wikidata":"https://www.wikidata.org/wiki/Q7623247","display_name":"Strength of a graph","level":5,"score":0.28540000319480896},{"id":"https://openalex.org/C2985906921","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Spectral properties","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C2983668108","wikidata":"https://www.wikidata.org/wiki/Q280453","display_name":"Spectral analysis","level":3,"score":0.2718999981880188},{"id":"https://openalex.org/C204707403","wikidata":"https://www.wikidata.org/wiki/Q1152398","display_name":"Canonical form","level":2,"score":0.27059999108314514},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2676999866962433},{"id":"https://openalex.org/C38180746","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate analysis","level":2,"score":0.25529998540878296},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.2522999942302704}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1080/00031305.2026.2730356","doi":"https://doi.org/10.1080/00031305.2026.2730356","is_oa":false,"landing_page_url":"https://doi.org/10.1080/00031305.2026.2730356","pdf_url":null,"source":{"id":"https://openalex.org/S4179095","display_name":"The American Statistician","issn_l":"0003-1305","issn":["0003-1305","1537-2731"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-b","anvur-scientific","cwts-core","dongbi-b","doyens","jufo-1","ki-jl-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The American Statistician","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2601.09038","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2601.09038","pdf_url":"https://arxiv.org/pdf/2601.09038","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2601.09038","doi":"https://doi.org/10.48550/arxiv.2601.09038","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.09038","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},{"id":"doi:10.6084/m9.figshare.33465529","doi":"https://doi.org/10.6084/m9.figshare.33465529","is_oa":true,"landing_page_url":"https://doi.org/10.6084/m9.figshare.33465529","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"JournalArticle"},{"id":"doi:10.6084/m9.figshare.33465529.v1","doi":"https://doi.org/10.6084/m9.figshare.33465529.v1","is_oa":true,"landing_page_url":"https://doi.org/10.6084/m9.figshare.33465529.v1","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"JournalArticle"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2601.09038","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2601.09038","pdf_url":"https://arxiv.org/pdf/2601.09038","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G3285623891","display_name":null,"funder_award_id":"2021R1A2C1091357","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G960853366","display_name":null,"funder_award_id":"RS-2021-NR060140","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7124258656.pdf","grobid_xml":"https://content.openalex.org/works/W7124258656.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W1698699930","https://openalex.org/W1991252559","https://openalex.org/W2025341678","https://openalex.org/W2039508219","https://openalex.org/W2045218416","https://openalex.org/W2101491865","https://openalex.org/W2235146554","https://openalex.org/W2274086169","https://openalex.org/W2299462150","https://openalex.org/W2607169934","https://openalex.org/W2763569390","https://openalex.org/W2795051509","https://openalex.org/W2884534819","https://openalex.org/W2902091715","https://openalex.org/W2963482031","https://openalex.org/W2964693622","https://openalex.org/W3007598526","https://openalex.org/W4256217162","https://openalex.org/W4379795960","https://openalex.org/W4396242587","https://openalex.org/W4403444170","https://openalex.org/W4407184865","https://openalex.org/W4413051433","https://openalex.org/W4416366418"],"related_works":["https://openalex.org/W4407184865","https://openalex.org/W4391409051","https://openalex.org/W4403444170","https://openalex.org/W2939120987","https://openalex.org/W1971368490","https://openalex.org/W2292747169","https://openalex.org/W4416366418","https://openalex.org/W3013322408","https://openalex.org/W2952798993","https://openalex.org/W3108029334"],"abstract_inverted_index":{"We":[0,80],"propose":[1],"graph":[2,17,21,45,60],"canonical":[3,12,44],"coherence":[4],"analysis":[5,14],"(gCChA),":[6],"a":[7,63,88],"novel":[8],"framework":[9,67],"that":[10,47],"extends":[11],"correlation":[13],"to":[15,94],"multivariate":[16],"signals":[18,46,61],"in":[19],"the":[20,31,52,78,82],"frequency":[22],"domain.":[23],"The":[24],"proposed":[25],"method":[26,86],"addresses":[27],"challenges":[28],"posed":[29],"by":[30],"inherent":[32],"features":[33],"of":[34,43,54,59,77,84,99],"graphs:":[35],"discreteness,":[36],"finiteness,":[37],"and":[38,91,96],"irregularity.":[39],"It":[40],"identifies":[41],"pairs":[42],"maximize":[48],"their":[49],"coherence,":[50],"enabling":[51],"exploration":[53],"relationships":[55,71],"between":[56],"two":[57],"sets":[58],"from":[62],"spectral":[64],"perspective.":[65],"This":[66],"shows":[68],"how":[69],"these":[70],"change":[72],"across":[73],"different":[74],"structural":[75],"scales":[76],"graph.":[79],"demonstrate":[81],"usefulness":[83],"this":[85],"through":[87],"simulation":[89],"study":[90],"an":[92],"application":[93],"economic":[95],"energy":[97],"datasets":[98],"G20":[100],"countries.":[101]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-11-12T12:28:57.059296","created_date":"2026-01-16T00:00:00"}