{"id":"https://openalex.org/W7165545340","doi":"https://doi.org/10.1007/s12083-026-02223-9","title":"A KAN-enhanced graphSAGE model for ethereum account classification on heterophilic graphs","display_name":"A KAN-enhanced graphSAGE model for ethereum account classification on heterophilic graphs","publication_year":2026,"publication_date":"2026-06-22","ids":{"openalex":"https://openalex.org/W7165545340","doi":"https://doi.org/10.1007/s12083-026-02223-9"},"language":"en","primary_location":{"id":"doi:10.1007/s12083-026-02223-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s12083-026-02223-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s12083-026-02223-9.pdf","source":{"id":"https://openalex.org/S177487720","display_name":"Peer-to-Peer Networking and Applications","issn_l":"1936-6442","issn":["1936-6442","1936-6450"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Peer-to-Peer Networking and Applications","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s12083-026-02223-9.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139081244","display_name":"Hengliang Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hengliang Guo","raw_affiliation_strings":["National Supercomputing Center in Zhengzhou, University Zhengzhou, Southeast corner of Changchun Road and Fengyang Street intersection, Zhengzhou, 450001, China","School of Computer and Artificial Intelligence, University Zhengzhou, No.100, Kexue Avenue, Zhengzhou, 450001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Supercomputing Center in Zhengzhou, University Zhengzhou, Southeast corner of Changchun Road and Fengyang Street intersection, Zhengzhou, 450001, China","institution_ids":["https://openalex.org/I38877650"]},{"raw_affiliation_string":"School of Computer and Artificial Intelligence, University Zhengzhou, No.100, Kexue Avenue, Zhengzhou, 450001, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139085588","display_name":"Yizhe Sui","orcid":null},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yizhe Sui","raw_affiliation_strings":["School of Computer and Artificial Intelligence, University Zhengzhou, No.100, Kexue Avenue, Zhengzhou, 450001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Artificial Intelligence, University Zhengzhou, No.100, Kexue Avenue, Zhengzhou, 450001, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101874451","display_name":"Jiaru Li","orcid":"https://orcid.org/0000-0001-5550-7421"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaru Li","raw_affiliation_strings":["School of Computer and Artificial Intelligence, University Zhengzhou, No.100, Kexue Avenue, Zhengzhou, 450001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Artificial Intelligence, University Zhengzhou, No.100, Kexue Avenue, Zhengzhou, 450001, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048701309","display_name":"Fuchang Gao","orcid":"https://orcid.org/0000-0001-7699-4433"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fuchang Gao","raw_affiliation_strings":["School of Computer and Artificial Intelligence, University Zhengzhou, No.100, Kexue Avenue, Zhengzhou, 450001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Artificial Intelligence, University Zhengzhou, No.100, Kexue Avenue, Zhengzhou, 450001, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107742382","display_name":"Yubo Han","orcid":null},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yubo Han","raw_affiliation_strings":["School of Computer and Artificial Intelligence, University Zhengzhou, No.100, Kexue Avenue, Zhengzhou, 450001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Artificial Intelligence, University Zhengzhou, No.100, Kexue Avenue, Zhengzhou, 450001, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101863638","display_name":"Yang Guo","orcid":"https://orcid.org/0000-0002-1453-6645"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Guo","raw_affiliation_strings":["National Supercomputing Center in Zhengzhou, University Zhengzhou, Southeast corner of Changchun Road and Fengyang Street intersection, Zhengzhou, 450001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Supercomputing Center in Zhengzhou, University Zhengzhou, Southeast corner of Changchun Road and Fengyang Street intersection, Zhengzhou, 450001, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5139117083","display_name":"Gang Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Gang Wu","raw_affiliation_strings":["National Supercomputing Center in Zhengzhou, University Zhengzhou, Southeast corner of Changchun Road and Fengyang Street intersection, Zhengzhou, 450001, China","School of Computer and Artificial Intelligence, University Zhengzhou, No.100, Kexue Avenue, Zhengzhou, 450001, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Supercomputing Center in Zhengzhou, University Zhengzhou, Southeast corner of Changchun Road and Fengyang Street intersection, Zhengzhou, 450001, China","institution_ids":["https://openalex.org/I38877650"]},{"raw_affiliation_string":"School of Computer and Artificial Intelligence, University Zhengzhou, No.100, Kexue Avenue, Zhengzhou, 450001, China","institution_ids":["https://openalex.org/I38877650"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5139117083"],"corresponding_institution_ids":["https://openalex.org/I38877650"],"apc_list":{"value":3590,"currency":"USD","value_usd":3590},"apc_paid":{"value":3590,"currency":"USD","value_usd":3590},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.78979161,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"19","issue":"4","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.4221000075340271,"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":0.4221000075340271,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.08640000224113464,"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/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.065700002014637,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.6687999963760376},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5687999725341797},{"id":"https://openalex.org/keywords/database-transaction","display_name":"Database transaction","score":0.5666000247001648},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.39739999175071716},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3596000075340271},{"id":"https://openalex.org/keywords/graph-theory","display_name":"Graph theory","score":0.3172000050544739}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7522000074386597},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.6687999963760376},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5687999725341797},{"id":"https://openalex.org/C75949130","wikidata":"https://www.wikidata.org/wiki/Q848010","display_name":"Database transaction","level":2,"score":0.5666000247001648},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46560001373291016},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46239998936653137},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44350001215934753},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.397599995136261},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.39739999175071716},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3596000075340271},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.3172000050544739},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.313400000333786},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.3046000003814697},{"id":"https://openalex.org/C72108876","wikidata":"https://www.wikidata.org/wiki/Q844565","display_name":"Transaction processing","level":3,"score":0.27250000834465027}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s12083-026-02223-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s12083-026-02223-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s12083-026-02223-9.pdf","source":{"id":"https://openalex.org/S177487720","display_name":"Peer-to-Peer Networking and Applications","issn_l":"1936-6442","issn":["1936-6442","1936-6450"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Peer-to-Peer Networking and Applications","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s12083-026-02223-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s12083-026-02223-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s12083-026-02223-9.pdf","source":{"id":"https://openalex.org/S177487720","display_name":"Peer-to-Peer Networking and Applications","issn_l":"1936-6442","issn":["1936-6442","1936-6450"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Peer-to-Peer Networking and Applications","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7165545340.pdf","grobid_xml":"https://content.openalex.org/works/W7165545340.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W3090999459","https://openalex.org/W3114928288","https://openalex.org/W3128443161","https://openalex.org/W4200632081","https://openalex.org/W4206425576","https://openalex.org/W4221142149","https://openalex.org/W4225328503","https://openalex.org/W4226427994","https://openalex.org/W4312646739","https://openalex.org/W4379160762","https://openalex.org/W4384284001","https://openalex.org/W4388878493","https://openalex.org/W4394717809","https://openalex.org/W4396735669","https://openalex.org/W4396758663","https://openalex.org/W4397009065","https://openalex.org/W4399449905","https://openalex.org/W4401507710","https://openalex.org/W4403917594","https://openalex.org/W4405439414","https://openalex.org/W4407783603","https://openalex.org/W4409149670","https://openalex.org/W7133184696"],"related_works":[],"abstract_inverted_index":{"Ethereum":[0,38,155],"account":[1,18],"classification":[2,129,168],"is":[3,90],"essential":[4],"for":[5,27,76],"identifying":[6],"individuals":[7],"engaged":[8],"in":[9,189],"illicit":[10],"transactions":[11],"and":[12,29,55,111,124,136,145,166,176,195],"analyzing":[13],"behavioral":[14],"patterns":[15],"across":[16],"various":[17],"types.":[19],"This":[20],"process":[21],"serves":[22],"as":[23],"a":[24,44,73,153,167],"critical":[25],"mechanism":[26],"monitoring":[28],"regulating":[30],"unlawful":[31],"activities":[32],"within":[33],"transactional":[34],"markets.":[35],"However,":[36],"the":[37,41,53,67,97,140,146],"network":[39],"exhibits":[40],"characteristics":[42],"of":[43,57,100,164,170],"complex":[45],"heterophilic":[46,77,101,125,177],"graph":[47,59,78,148],"which":[48],"poses":[49],"significant":[50],"challenges":[51],"to":[52,93,96,106,114,132,203],"effectiveness":[54],"performance":[56],"conventional":[58,204],"neural":[60,79],"networks":[61,80],"(GNNs).":[62],"To":[63],"address":[64],"this":[65],"challenge,":[66],"present":[68],"study":[69],"proposes":[70],"FSGCN(Fourier-Sage":[71],"GCN),":[72],"novel":[74],"architecture":[75],"(GNNs)":[81],"that":[82,159],"integrates":[83],"Kolmogorov\u2013Arnold":[84],"Networks":[85],"(KANs)":[86],"with":[87],"GraphSAGE.":[88,205],"FSGCN":[89,119,160,181],"specifically":[91],"designed":[92],"adapt":[94],"efficiently":[95],"structural":[98],"complexity":[99],"graphs.":[102],"By":[103],"leveraging":[104],"KANs":[105],"extract":[107],"high-order":[108],"neighborhood":[109,117],"information":[110],"employing":[112],"GraphSAGE":[113],"capture":[115],"low-order":[116],"patterns,":[118],"effectively":[120],"aggregates":[121],"both":[122],"homophilic":[123,175],"features,":[126],"thereby":[127],"improving":[128,196],"performance.":[130],"Furthermore,":[131],"improve":[133],"training":[134,184,198],"efficiency":[135],"generalization,":[137],"we":[138],"propose":[139],"MLPInit":[141],"weight":[142],"initialization":[143],"scheme":[144],"DropEdge":[147],"augmentation":[149],"technique.":[150],"Experiments":[151],"on":[152],"large-scale":[154],"transaction":[156],"dataset":[157],"show":[158],"achieves":[161],"an":[162],"F1-score":[163],"91.8%":[165],"accuracy":[169],"91.6%,":[171],"significantly":[172],"outperforming":[173],"traditional":[174],"GNN":[178],"baselines.":[179],"Additionally,":[180],"demonstrates":[182],"high":[183],"efficiency,":[185],"completing":[186],"each":[187],"epoch":[188,194],"just":[190],"2.302":[191],"s":[192],"per":[193],"overall":[197],"speed":[199],"by":[200],"130.4%":[201],"compared":[202]},"counts_by_year":[],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2026-06-23T00:00:00"}
