{"id":"https://openalex.org/W4399601257","doi":"https://doi.org/10.1109/tfuzz.2024.3413826","title":"Graph Classification Method Based on Fuzzy Entropy Causality in a Network Formal Context","display_name":"Graph Classification Method Based on Fuzzy Entropy Causality in a Network Formal Context","publication_year":2024,"publication_date":"2024-06-13","ids":{"openalex":"https://openalex.org/W4399601257","doi":"https://doi.org/10.1109/tfuzz.2024.3413826"},"language":"en","primary_location":{"id":"doi:10.1109/tfuzz.2024.3413826","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2024.3413826","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Fuzzy Systems","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/A5103101717","display_name":"Min Fan","orcid":null},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Fan","raw_affiliation_strings":["Data Science Research Center, Kunming University of Science and Technology, Kunming, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science Research Center, Kunming University of Science and Technology, Kunming, China","institution_ids":["https://openalex.org/I10660446"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109000074","display_name":"Huan Li","orcid":"https://orcid.org/0009-0007-3407-279X"},"institutions":[{"id":"https://openalex.org/I10660446","display_name":"Kunming University of Science and Technology","ror":"https://ror.org/00xyeez13","country_code":"CN","type":"education","lineage":["https://openalex.org/I10660446"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huan Li","raw_affiliation_strings":["Data Science Research Center, Kunming University of Science and Technology, Kunming, China"],"raw_orcid":"https://orcid.org/0009-0007-3407-279X","affiliations":[{"raw_affiliation_string":"Data Science Research Center, Kunming University of Science and Technology, Kunming, China","institution_ids":["https://openalex.org/I10660446"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I10660446"],"apc_list":null,"apc_paid":null,"fwci":0.8647,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.75049122,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"32","issue":"9","first_page":"5018","last_page":"5032"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9998999834060669,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9902999997138977,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.978600025177002,"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":0.6015251874923706},{"id":"https://openalex.org/keywords/causality","display_name":"Causality (physics)","score":0.5878903865814209},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5257167220115662},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5250931978225708},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.49434709548950195},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.48656120896339417},{"id":"https://openalex.org/keywords/fuzzy-set","display_name":"Fuzzy set","score":0.43198198080062866},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38695889711380005},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38422802090644836},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.35095518827438354},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34333401918411255}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6015251874923706},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.5878903865814209},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5257167220115662},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5250931978225708},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.49434709548950195},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.48656120896339417},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.43198198080062866},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38695889711380005},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38422802090644836},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.35095518827438354},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34333401918411255},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tfuzz.2024.3413826","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2024.3413826","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.44999998807907104,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G1837892858","display_name":null,"funder_award_id":"12371460","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":55,"referenced_works":["https://openalex.org/W2033973415","https://openalex.org/W2070813883","https://openalex.org/W2074310030","https://openalex.org/W2096060214","https://openalex.org/W2121044470","https://openalex.org/W2160448328","https://openalex.org/W2729480800","https://openalex.org/W2788919350","https://openalex.org/W2794180119","https://openalex.org/W2797554548","https://openalex.org/W2907101105","https://openalex.org/W2946693349","https://openalex.org/W2947954362","https://openalex.org/W2997546679","https://openalex.org/W2997997679","https://openalex.org/W2998423439","https://openalex.org/W3010882303","https://openalex.org/W3012521642","https://openalex.org/W3015751214","https://openalex.org/W3034090344","https://openalex.org/W3041899150","https://openalex.org/W3139120698","https://openalex.org/W3157658347","https://openalex.org/W3173856251","https://openalex.org/W3176140580","https://openalex.org/W3188927595","https://openalex.org/W3214872094","https://openalex.org/W4224119973","https://openalex.org/W4224284427","https://openalex.org/W4234423219","https://openalex.org/W4252684946","https://openalex.org/W4283070111","https://openalex.org/W4290948450","https://openalex.org/W4308459300","https://openalex.org/W4315650716","https://openalex.org/W4319068825","https://openalex.org/W4319302558","https://openalex.org/W4321607999","https://openalex.org/W4322727980","https://openalex.org/W4381198929","https://openalex.org/W6685265622","https://openalex.org/W6690815549","https://openalex.org/W6726873649","https://openalex.org/W6736685754","https://openalex.org/W6738964360","https://openalex.org/W6745537798","https://openalex.org/W6753331806","https://openalex.org/W6754929296","https://openalex.org/W6761665040","https://openalex.org/W6762735450","https://openalex.org/W6770102389","https://openalex.org/W6771510844","https://openalex.org/W6790558058","https://openalex.org/W6839404074","https://openalex.org/W6921978402"],"related_works":["https://openalex.org/W2081494945","https://openalex.org/W2389053294","https://openalex.org/W1970893504","https://openalex.org/W4312071518","https://openalex.org/W2901208600","https://openalex.org/W1677090476","https://openalex.org/W830525666","https://openalex.org/W2330229995","https://openalex.org/W3014724311","https://openalex.org/W2106711308"],"abstract_inverted_index":{"Graph":[0],"classification":[1,43,137,149,168],"has":[2],"always":[3],"been":[4],"a":[5,27,36,41,80,93,133],"research":[6],"hotspot":[7],"in":[8,123],"the":[9,21,62,84,101,143,146,171,175],"field":[10],"of":[11,23,86,103,145,162,174],"graph":[12,24,42,59,69,113,157],"neural":[13,71],"networks":[14,72],"and":[15,33,58,109,159],"related":[16],"areas.":[17],"However,":[18],"due":[19],"to":[20,100,141],"complexity":[22],"data,":[25],"finding":[26],"feasible":[28],"algorithm":[29,108,115],"that":[30],"balance":[31],"efficiency":[32],"accuracy":[34],"remains":[35],"challenge.":[37],"In":[38,91],"this":[39],"article,":[40],"method":[44,138],"based":[45],"on":[46],"fuzzy":[47,127,134],"entropy":[48,128,135],"causality":[49,136],"is":[50,66,96],"introduced":[51],"by":[52],"combining":[53,126],"formal":[54,64,77],"concept":[55],"analysis,":[56],"causality,":[57,131],"convolution.":[60],"First,":[61],"network":[63,76],"context":[65],"combined":[67],"with":[68,129],"convolutional":[70],"(GCNs),":[73],"forming":[74],"\u201cgraph":[75],"context,\u201d":[78],"providing":[79],"solid":[81],"foundation":[82],"for":[83],"convergence":[85],"these":[87],"two":[88],"theoretical":[89],"domains.":[90],"addition,":[92],"high-order":[94,104,110],"GCN":[95],"thoroughly":[97],"studied,":[98],"leading":[99],"design":[102],"cluster":[105],"information":[106,122],"aggregation":[107,111],"hierarchical":[112],"pooling":[114],"(HAGP).":[116],"These":[117],"innovations":[118],"comprehensively":[119],"capture":[120],"fundamental":[121],"graphs.":[124],"Simultaneously,":[125],"Pearl's":[130],"creating":[132],"(FECCM).":[139],"Finally,":[140],"validate":[142],"effectiveness":[144],"proposed":[147],"model,":[148],"performance":[150],"comparison":[151],"experiments":[152],"are":[153],"conducted":[154],"using":[155],"12":[156],"datasets":[158],"nine":[160],"University":[161],"CaliforniaIrvine":[163],"Machine":[164],"Learning":[165],"Repository":[166],"(UCI)":[167],"datasets,":[169],"demonstrating":[170],"advanced":[172],"nature":[173],"HAGP-FECCM.":[176]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}