{"id":"https://openalex.org/W4412972614","doi":"https://doi.org/10.1109/tsmc.2025.3583919","title":"Neural Networks-Incorporated Latent Factor Analysis for High-Dimensional and Incomplete Data","display_name":"Neural Networks-Incorporated Latent Factor Analysis for High-Dimensional and Incomplete Data","publication_year":2025,"publication_date":"2025-07-16","ids":{"openalex":"https://openalex.org/W4412972614","doi":"https://doi.org/10.1109/tsmc.2025.3583919"},"language":"en","primary_location":{"id":"doi:10.1109/tsmc.2025.3583919","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmc.2025.3583919","pdf_url":null,"source":{"id":"https://openalex.org/S4210209078","display_name":"IEEE Transactions on Systems Man and Cybernetics Systems","issn_l":"2168-2216","issn":["2168-2216","2168-2232"],"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 Systems, Man, and Cybernetics: 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/A5101851003","display_name":"Ming\u2010Wei Lin","orcid":"https://orcid.org/0000-0003-2026-7178"},"institutions":[{"id":"https://openalex.org/I111753288","display_name":"Fujian Normal University","ror":"https://ror.org/020azk594","country_code":"CN","type":"education","lineage":["https://openalex.org/I111753288"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingwei Lin","raw_affiliation_strings":["College of Computer and Cyber Security, Fujian Normal University, Fuzhou, Fujian, China"],"raw_orcid":"https://orcid.org/0000-0003-2026-7178","affiliations":[{"raw_affiliation_string":"College of Computer and Cyber Security, Fujian Normal University, Fuzhou, Fujian, China","institution_ids":["https://openalex.org/I111753288"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xingyu Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I111753288","display_name":"Fujian Normal University","ror":"https://ror.org/020azk594","country_code":"CN","type":"education","lineage":["https://openalex.org/I111753288"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingyu Lin","raw_affiliation_strings":["College of Computer and Cyber Security, Fujian Normal University, Fuzhou, Fujian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer and Cyber Security, Fujian Normal University, Fuzhou, Fujian, China","institution_ids":["https://openalex.org/I111753288"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065313978","display_name":"Xiuqin Xu","orcid":"https://orcid.org/0000-0001-6639-5269"},"institutions":[{"id":"https://openalex.org/I111753288","display_name":"Fujian Normal University","ror":"https://ror.org/020azk594","country_code":"CN","type":"education","lineage":["https://openalex.org/I111753288"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuqin Xu","raw_affiliation_strings":["College of Computer and Cyber Security, Fujian Normal University, Fuzhou, Fujian, China"],"raw_orcid":"https://orcid.org/0000-0001-6639-5269","affiliations":[{"raw_affiliation_string":"College of Computer and Cyber Security, Fujian Normal University, Fuzhou, Fujian, China","institution_ids":["https://openalex.org/I111753288"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100437308","display_name":"Zeshui Xu","orcid":"https://orcid.org/0000-0003-3547-2908"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zeshui Xu","raw_affiliation_strings":["Business School, Sichuan University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-3547-2908","affiliations":[{"raw_affiliation_string":"Business School, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I24185976"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088955392","display_name":"Xin Luo","orcid":"https://orcid.org/0000-0002-1348-5305"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Luo","raw_affiliation_strings":["College of Computer and Information Science, Southwest University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-1348-5305","affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.217,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.95240592,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"55","issue":"10","first_page":"7302","last_page":"7314"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.6312999725341797,"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/T10320","display_name":"Neural Networks and Applications","score":0.6312999725341797,"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/artificial-neural-network","display_name":"Artificial neural network","score":0.5134544968605042},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5012636184692383},{"id":"https://openalex.org/keywords/factor","display_name":"Factor (programming language)","score":0.48526903986930847},{"id":"https://openalex.org/keywords/latent-class-model","display_name":"Latent class model","score":0.46654224395751953},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4307505786418915},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.23450079560279846}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5134544968605042},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5012636184692383},{"id":"https://openalex.org/C2781039887","wikidata":"https://www.wikidata.org/wiki/Q1391724","display_name":"Factor (programming language)","level":2,"score":0.48526903986930847},{"id":"https://openalex.org/C70727504","wikidata":"https://www.wikidata.org/wiki/Q1806878","display_name":"Latent class model","level":2,"score":0.46654224395751953},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4307505786418915},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.23450079560279846},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsmc.2025.3583919","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsmc.2025.3583919","pdf_url":null,"source":{"id":"https://openalex.org/S4210209078","display_name":"IEEE Transactions on Systems Man and Cybernetics Systems","issn_l":"2168-2216","issn":["2168-2216","2168-2232"],"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 Systems, Man, and Cybernetics: Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6279274168","display_name":null,"funder_award_id":"F21E0011202B01","funder_id":"https://openalex.org/F4320321878","funder_display_name":"Natural Science Foundation of Fujian Province"},{"id":"https://openalex.org/G8515641209","display_name":null,"funder_award_id":"62272078","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"},{"id":"https://openalex.org/F4320321878","display_name":"Natural Science Foundation of Fujian Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1720514416","https://openalex.org/W2008886893","https://openalex.org/W2054141820","https://openalex.org/W2085179787","https://openalex.org/W2117354486","https://openalex.org/W2119523409","https://openalex.org/W2315490857","https://openalex.org/W2605350416","https://openalex.org/W2608069546","https://openalex.org/W2761091319","https://openalex.org/W2765820394","https://openalex.org/W2782259251","https://openalex.org/W2829536470","https://openalex.org/W2892240940","https://openalex.org/W2899338891","https://openalex.org/W2900229157","https://openalex.org/W2944420298","https://openalex.org/W3015387428","https://openalex.org/W3036408105","https://openalex.org/W3119262449","https://openalex.org/W3121678941","https://openalex.org/W3153539640","https://openalex.org/W3212684647","https://openalex.org/W3213920736","https://openalex.org/W4200484978","https://openalex.org/W4214580404","https://openalex.org/W4232714830","https://openalex.org/W4283311205","https://openalex.org/W4285135356","https://openalex.org/W4285238799","https://openalex.org/W4289654500","https://openalex.org/W4293107381","https://openalex.org/W4379033926","https://openalex.org/W4380874559","https://openalex.org/W4381894803","https://openalex.org/W4390534276","https://openalex.org/W4393391530","https://openalex.org/W4398157455","https://openalex.org/W4399426376","https://openalex.org/W4402215873"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"high-dimensional":[0],"and":[1,104,139,157,208],"incomplete":[2],"(HDI)":[3],"matrices":[4],"are":[5,173],"commonly":[6],"encountered":[7],"in":[8,26,41,49,64,79,90,203],"a":[9,115],"variety":[10],"of":[11,132,164,205],"big":[12],"data-related":[13],"industrial":[14,42,178],"applications,":[15],"which":[16],"describe":[17],"complex":[18],"interactions":[19],"between":[20],"entities.":[21],"The":[22,181],"complete":[23],"interaction":[24],"relationship":[25],"the":[27,46,50,69,75,80,88,91,109,121,129,133,143,146,162,165,186],"HDI":[28,51,81,92,134],"matrix":[29,52,135],"is":[30,53],"essential":[31],"to":[32,149,194,213],"deal":[33],"with":[34,169],"various":[35],"problems":[36],"such":[37,66],"as":[38],"pattern":[39],"recognition":[40],"applications.":[43],"Therefore,":[44],"estimating":[45],"missing":[47],"data":[48],"crucial.":[54],"latent":[55],"factor":[56],"analysis":[57],"(LFA)":[58],"models":[59,72,172],"have":[60],"achieved":[61],"advanced":[62],"results":[63,183],"solving":[65],"problems.":[67],"However,":[68],"existing":[70],"LFA":[71,147],"cannot":[73],"model":[74,128,148,188,199],"nonlinear":[76,130],"structure":[77,131],"hidden":[78],"matrix.":[82],"neural":[83],"networks":[84],"(NNs)":[85],"can":[86,127],"handle":[87],"nonlinearity":[89],"data,":[93],"but":[94],"their":[95],"high":[96,101,155],"estimation":[97,151,190],"accuracy":[98,152,191],"relies":[99],"on":[100,175],"computation":[102],"cost":[103],"storage":[105,158,209],"burden.":[106],"To":[107,160],"address":[108],"aforementioned":[110],"problems,":[111],"this":[112],"article":[113],"proposes":[114],"novel":[116],"NNLFA":[117,166,187,198],"model.":[118],"It":[119],"contains":[120],"following":[122],"primary":[123],"ideas:":[124],"1)":[125],"it":[126,141],"efficiently":[136],"through":[137],"NNs":[138,144],"2)":[140],"incorporates":[142],"into":[145],"improve":[150],"while":[153],"maintaining":[154],"computational":[156],"efficiency.":[159],"validate":[161],"superiority":[163],"model,":[167],"experiments":[168],"six":[170,176],"state-of-the-art":[171],"conducted":[174],"practical":[177],"application":[179],"datasets.":[180],"experimental":[182],"indicate":[184],"that":[185],"enhances":[189],"by":[192],"up":[193],"33.3%.":[195],"In":[196],"addition,":[197],"shows":[200],"strong":[201],"competitiveness":[202],"terms":[204],"both":[206],"time":[207],"efficiency":[210],"when":[211],"compared":[212],"baseline":[214],"models.":[215]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}