{"id":"https://openalex.org/W4410294919","doi":"https://doi.org/10.26599/bdma.2025.9020005","title":"Hierarchical Semi-Supervised Representation Learning for Cyber Physical Social Intelligence","display_name":"Hierarchical Semi-Supervised Representation Learning for Cyber Physical Social Intelligence","publication_year":2025,"publication_date":"2025-05-12","ids":{"openalex":"https://openalex.org/W4410294919","doi":"https://doi.org/10.26599/bdma.2025.9020005"},"language":"en","primary_location":{"id":"doi:10.26599/bdma.2025.9020005","is_oa":true,"landing_page_url":"https://doi.org/10.26599/bdma.2025.9020005","pdf_url":null,"source":{"id":"https://openalex.org/S4210209060","display_name":"Big Data Mining and Analytics","issn_l":"2096-0654","issn":["2096-0654"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311901","host_organization_name":"Tsinghua University Press","host_organization_lineage":["https://openalex.org/P4310311901"],"host_organization_lineage_names":["Tsinghua University Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data Mining and Analytics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.26599/bdma.2025.9020005","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5014356473","display_name":"Na Song","orcid":"https://orcid.org/0000-0002-1672-3065"},"institutions":[{"id":"https://openalex.org/I64449678","display_name":"Putian University","ror":"https://ror.org/00jmsxk74","country_code":"CN","type":"education","lineage":["https://openalex.org/I64449678"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Na Song","raw_affiliation_strings":["School of Mechanical, Electrical and Information Engineering, Putian University,Putian,China,351100"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical, Electrical and Information Engineering, Putian University,Putian,China,351100","institution_ids":["https://openalex.org/I64449678"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101912332","display_name":"Jing Yang","orcid":"https://orcid.org/0000-0001-7583-6185"},"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":"Jing Yang","raw_affiliation_strings":["School of Computer and Artificial Intelligence, Zhengzhou University,Zhengzhou,China,450001"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Artificial Intelligence, Zhengzhou University,Zhengzhou,China,450001","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044656190","display_name":"Xuemei Fu","orcid":"https://orcid.org/0000-0002-5681-3401"},"institutions":[{"id":"https://openalex.org/I20942203","display_name":"Hainan University","ror":"https://ror.org/03q648j11","country_code":"CN","type":"education","lineage":["https://openalex.org/I20942203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuemei Fu","raw_affiliation_strings":["School of Information and Communication Engineering, Hainan University,Haikou,China,570228"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Hainan University,Haikou,China,570228","institution_ids":["https://openalex.org/I20942203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060676621","display_name":"Xiangli Yang","orcid":"https://orcid.org/0009-0009-8442-9747"},"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":"Xiangli Yang","raw_affiliation_strings":["School of Computer and Artificial Intelligence, Zhengzhou University,Zhengzhou,China,450001"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Artificial Intelligence, Zhengzhou University,Zhengzhou,China,450001","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101628906","display_name":"Ying Xie","orcid":"https://orcid.org/0000-0002-6419-3986"},"institutions":[{"id":"https://openalex.org/I64449678","display_name":"Putian University","ror":"https://ror.org/00jmsxk74","country_code":"CN","type":"education","lineage":["https://openalex.org/I64449678"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Xie","raw_affiliation_strings":["School of Mechanical, Electrical and Information Engineering, Putian University,Putian,China,350001"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical, Electrical and Information Engineering, Putian University,Putian,China,350001","institution_ids":["https://openalex.org/I64449678"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100604225","display_name":"Shiping Wang","orcid":"https://orcid.org/0000-0001-5195-9682"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiping Wang","raw_affiliation_strings":["College of Computer and Data Science, Fuzhou University,Fuzhou,China,350108"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer and Data Science, Fuzhou University,Fuzhou,China,350108","institution_ids":["https://openalex.org/I80947539"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5014356473"],"corresponding_institution_ids":["https://openalex.org/I64449678"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04339886,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"8","issue":"4","first_page":"837","last_page":"850"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.4180000126361847,"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":0.4180000126361847,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.41179999709129333,"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/representation","display_name":"Representation (politics)","score":0.5767005085945129},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5684852600097656},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5333601832389832},{"id":"https://openalex.org/keywords/cyber-physical-system","display_name":"Cyber-physical system","score":0.46442002058029175},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4292847514152527},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4252273440361023},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.33199435472488403},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.06423631310462952}],"concepts":[{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5767005085945129},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5684852600097656},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5333601832389832},{"id":"https://openalex.org/C179768478","wikidata":"https://www.wikidata.org/wiki/Q1120057","display_name":"Cyber-physical system","level":2,"score":0.46442002058029175},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4292847514152527},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4252273440361023},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.33199435472488403},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.06423631310462952},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.26599/bdma.2025.9020005","is_oa":true,"landing_page_url":"https://doi.org/10.26599/bdma.2025.9020005","pdf_url":null,"source":{"id":"https://openalex.org/S4210209060","display_name":"Big Data Mining and Analytics","issn_l":"2096-0654","issn":["2096-0654"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311901","host_organization_name":"Tsinghua University Press","host_organization_lineage":["https://openalex.org/P4310311901"],"host_organization_lineage_names":["Tsinghua University Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data Mining and Analytics","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:6486be994862433e948dd176017e0a5c","is_oa":true,"landing_page_url":"https://doaj.org/article/6486be994862433e948dd176017e0a5c","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Big Data Mining and Analytics, Vol 8, Iss 4, Pp 837-850 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.26599/bdma.2025.9020005","is_oa":true,"landing_page_url":"https://doi.org/10.26599/bdma.2025.9020005","pdf_url":null,"source":{"id":"https://openalex.org/S4210209060","display_name":"Big Data Mining and Analytics","issn_l":"2096-0654","issn":["2096-0654"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311901","host_organization_name":"Tsinghua University Press","host_organization_lineage":["https://openalex.org/P4310311901"],"host_organization_lineage_names":["Tsinghua University Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Big Data Mining and Analytics","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.5099999904632568}],"awards":[{"id":"https://openalex.org/G4089052499","display_name":null,"funder_award_id":"62302131,62302130,62276146","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":40,"referenced_works":["https://openalex.org/W1972344647","https://openalex.org/W2012659293","https://openalex.org/W2487852963","https://openalex.org/W2751820872","https://openalex.org/W2894142921","https://openalex.org/W2900928715","https://openalex.org/W2903936867","https://openalex.org/W2922706279","https://openalex.org/W2962946486","https://openalex.org/W2964051675","https://openalex.org/W2998496395","https://openalex.org/W2998662521","https://openalex.org/W3043016077","https://openalex.org/W3097300053","https://openalex.org/W3137220334","https://openalex.org/W3148388528","https://openalex.org/W3155581945","https://openalex.org/W3160988939","https://openalex.org/W3164046276","https://openalex.org/W3197438902","https://openalex.org/W3197696221","https://openalex.org/W4210911618","https://openalex.org/W4211006900","https://openalex.org/W4220924437","https://openalex.org/W4224926219","https://openalex.org/W4285178986","https://openalex.org/W4285818910","https://openalex.org/W4288771025","https://openalex.org/W4306405949","https://openalex.org/W4312973985","https://openalex.org/W4321113904","https://openalex.org/W4360770799","https://openalex.org/W4380883528","https://openalex.org/W4387778634","https://openalex.org/W4390488744","https://openalex.org/W6639103823","https://openalex.org/W6752110883","https://openalex.org/W6760001035","https://openalex.org/W6790814767","https://openalex.org/W6791458620"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"In":[0],"the":[1,23,48,53,131],"context":[2],"of":[3,28,133],"Cyber":[4],"Physical":[5],"Social":[6],"Intelligence":[7],"(CPSI),":[8],"efficiently":[9],"training":[10],"and":[11,25,128],"inferring":[12],"from":[13],"samples":[14],"with":[15,80],"limited":[16],"labels":[17],"poses":[18],"critical":[19],"challenges":[20,54],"due":[21],"to":[22,37,47,89],"scarcity":[24],"high":[26,39],"cost":[27],"label":[29],"acquisition":[30],"for":[31,64,74],"big":[32],"data.":[33],"The":[34],"aim":[35],"is":[36],"attain":[38],"accuracy":[40],"at":[41],"minimal":[42],"cost,":[43],"thereby":[44],"enhancing":[45],"adaptation":[46],"CPSI":[49],"scenario.":[50],"To":[51],"tackle":[52],"in":[55,140],"CPSI,":[56],"we":[57,69],"present":[58],"a":[59,71,81,91,95,104,110],"multi-level":[60],"feature":[61],"learning":[62],"framework":[63],"semi-supervised":[65,142],"classification":[66,143],"tasks.":[67,144],"Initially,":[68],"employ":[70],"mapping":[72],"operation":[73],"each":[75],"view,":[76],"extracting":[77],"view-specific":[78],"features":[79,86],"feature-level":[82],"reconstruction":[83,107],"loss.":[84,108],"These":[85],"are":[87],"fused":[88],"obtain":[90],"shared":[92],"feature.":[93],"Simultaneously,":[94],"learnable":[96],"graph":[97,105,112],"neural":[98],"network":[99],"captures":[100],"global":[101],"topology":[102],"using":[103],"structure-level":[106],"Subsequently,":[109],"scalable":[111],"convolution":[113],"fusion":[114],"module":[115],"combines":[116],"these":[117],"features.":[118],"Our":[119],"evaluations":[120],"on":[121],"eight":[122,137],"benchmark":[123],"datasets":[124],"show":[125],"promising":[126],"results":[127],"empirically":[129],"prove":[130],"effectiveness":[132],"our":[134],"approach,":[135],"surpassing":[136],"state-of-the-art":[138],"methods":[139],"multi-view":[141]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}