{"id":"https://openalex.org/W3200924549","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533585","title":"VDGAN: A Collaborative Filtering Framework Based on Variational Denoising with GANs","display_name":"VDGAN: A Collaborative Filtering Framework Based on Variational Denoising with GANs","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3200924549","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533585","mag":"3200924549"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9533585","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533585","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-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/A5101650869","display_name":"Weifeng Sun","orcid":"https://orcid.org/0000-0001-6013-1369"},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weifeng Sun","raw_affiliation_strings":["School of Software, Dalian University of Technology,Dalian,China","School of Software, Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software, Dalian University of Technology,Dalian,China","institution_ids":["https://openalex.org/I27357992"]},{"raw_affiliation_string":"School of Software, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029768054","display_name":"Shumiao Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I27357992","display_name":"Dalian University of Technology","ror":"https://ror.org/023hj5876","country_code":"CN","type":"education","lineage":["https://openalex.org/I27357992"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shumiao Yu","raw_affiliation_strings":["School of Software, Dalian University of Technology,Dalian,China","School of Software, Dalian University of Technology, Dalian, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software, Dalian University of Technology,Dalian,China","institution_ids":["https://openalex.org/I27357992"]},{"raw_affiliation_string":"School of Software, Dalian University of Technology, Dalian, China","institution_ids":["https://openalex.org/I27357992"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089251186","display_name":"Boxiang Dong","orcid":"https://orcid.org/0000-0001-9520-1494"},"institutions":[{"id":"https://openalex.org/I166088655","display_name":"Montclair State University","ror":"https://ror.org/01nxc2t48","country_code":"US","type":"education","lineage":["https://openalex.org/I166088655"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Boxiang Dong","raw_affiliation_strings":["Montclair State University,Montclair,NJ,USA","Montclair State University, Montclair, NJ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Montclair State University,Montclair,NJ,USA","institution_ids":["https://openalex.org/I166088655"]},{"raw_affiliation_string":"Montclair State University, Montclair, NJ, USA","institution_ids":["https://openalex.org/I166088655"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.097,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.40328382,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11309","display_name":"Music and Audio Processing","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/discriminator","display_name":"Discriminator","score":0.8111158609390259},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8034379482269287},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.7283208966255188},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6164773106575012},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.5956684947013855},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5695110559463501},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5032193064689636},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4991476535797119},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47555869817733765},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.46300461888313293},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3945161998271942},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3910420536994934},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3671038746833801},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.3456566333770752},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.29226595163345337},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.11094284057617188}],"concepts":[{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.8111158609390259},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8034379482269287},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.7283208966255188},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6164773106575012},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.5956684947013855},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5695110559463501},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5032193064689636},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4991476535797119},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47555869817733765},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.46300461888313293},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3945161998271942},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3910420536994934},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3671038746833801},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.3456566333770752},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.29226595163345337},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.11094284057617188},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9533585","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533585","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7300000190734863}],"awards":[{"id":"https://openalex.org/G7391918885","display_name":null,"funder_award_id":"DUT18JC28,DUT19ZD103,DUT21LAB115","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1959608418","https://openalex.org/W2025768430","https://openalex.org/W2095705004","https://openalex.org/W2099471712","https://openalex.org/W2124187902","https://openalex.org/W2253995343","https://openalex.org/W2560512785","https://openalex.org/W2619206542","https://openalex.org/W2886661492","https://openalex.org/W2897167574","https://openalex.org/W2924526555","https://openalex.org/W2927931735","https://openalex.org/W2953046278","https://openalex.org/W2963085847","https://openalex.org/W2963403868","https://openalex.org/W2964121744","https://openalex.org/W2964268978","https://openalex.org/W2964926209","https://openalex.org/W2966145721","https://openalex.org/W2966483207","https://openalex.org/W3014926316","https://openalex.org/W3101023724","https://openalex.org/W3122507327","https://openalex.org/W3123463284","https://openalex.org/W4288083766","https://openalex.org/W4289676341","https://openalex.org/W4320013936","https://openalex.org/W4385245566","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6640963894","https://openalex.org/W6657028776","https://openalex.org/W6674330103","https://openalex.org/W6727862155","https://openalex.org/W6730998768","https://openalex.org/W6739901393","https://openalex.org/W6747855564","https://openalex.org/W6753544890","https://openalex.org/W6789414772"],"related_works":["https://openalex.org/W2772628444","https://openalex.org/W1484355083","https://openalex.org/W2735929803","https://openalex.org/W4220714703","https://openalex.org/W3008845055","https://openalex.org/W2098758514","https://openalex.org/W2170391450","https://openalex.org/W4376854386","https://openalex.org/W2202724490","https://openalex.org/W2508671622"],"abstract_inverted_index":{"Generative":[0],"Adversarial":[1],"Networks":[2],"(GANs)":[3],"effectively":[4],"capture":[5],"the":[6,26,29,39,67,71,75,79,88,91,101,107,111,115,120,124,129,134,142,145,151,160,165,169,182,188],"true":[7],"posterior":[8],"distribution.":[9],"When":[10],"applied":[11],"to":[12,83,87,132],"Collaborative":[13],"Filtering":[14],"(CF),":[15],"GANs":[16,62,193],"can":[17],"generate":[18],"a":[19,95],"recommendation":[20,166],"list":[21],"through":[22,119],"implicit":[23],"feedback.":[24],"However,":[25],"discriminators":[27],"in":[28],"existing":[30],"GANs-based":[31],"CF":[32],"methods":[33,190],"are":[34],"not":[35],"utilized":[36],"fully,":[37],"and":[38,70,99,162,194],"generators":[40],"perform":[41],"poorly":[42],"on":[43,58,175,192],"sparse":[44,102],"data":[45,103],"mining.":[46],"In":[47,109],"this":[48],"paper,":[49],"we":[50,179],"propose":[51],"an":[52],"improved":[53],"collaborative":[54],"filtering":[55],"framework":[56],"based":[57,191],"variational":[59,68,92],"denoising":[60,112],"for":[61],"(VDGAN).":[63],"Specifically,":[64],"VDGAN":[65,185],"integrates":[66],"encoder":[69,93],"self-attention":[72,130],"mechanism":[73,82,131],"into":[74],"GANs.":[76],"By":[77],"using":[78],"positive-negative":[80],"sampling":[81],"add":[84],"specific":[85],"noise":[86],"input":[89],"data,":[90],"obtains":[94],"robust":[96],"feature":[97,121],"matrix":[98,118],"improves":[100,164],"processing":[104],"capability":[105],"of":[106,128,137,144,155,168,184],"generator.":[108],"VDGAN,":[110],"generator":[113,161],"reconstructs":[114],"user-items":[116],"interaction":[117],"matrix.":[122],"And":[123],"discriminator":[125],"is":[126],"composed":[127],"obtain":[133],"explicit":[135],"features":[136],"user":[138],"preferences,":[139],"which":[140,157],"extends":[141],"ability":[143],"discriminator.":[146],"Furthermore,":[147],"reinforcement":[148],"learning":[149],"replaces":[150],"traditional":[152],"objective":[153],"function":[154],"GANs,":[156],"better":[158],"optimizes":[159],"further":[163],"accuracy":[167],"model.":[170],"From":[171],"our":[172],"comprehensive":[173],"experiments":[174],"three":[176],"real-world":[177],"datasets,":[178],"demonstrate":[180],"that":[181],"performance":[183],"significantly":[186],"outperforms":[187],"state-of-the-art":[189],"Auto-Encoders.":[195]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
