{"id":"https://openalex.org/W3123463284","doi":"https://doi.org/10.1109/globecom42002.2020.9322300","title":"A Novel Collaborative Filtering Framework Based on Variational Self-Attention GAN","display_name":"A Novel Collaborative Filtering Framework Based on Variational Self-Attention GAN","publication_year":2020,"publication_date":"2020-12-01","ids":{"openalex":"https://openalex.org/W3123463284","doi":"https://doi.org/10.1109/globecom42002.2020.9322300","mag":"3123463284"},"language":"en","primary_location":{"id":"doi:10.1109/globecom42002.2020.9322300","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom42002.2020.9322300","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2020 - 2020 IEEE Global Communications Conference","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"],"raw_orcid":null,"affiliations":[{"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"],"raw_orcid":null,"affiliations":[{"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/A5072670647","display_name":"Jin Min Yang","orcid":"https://orcid.org/0000-0002-4291-2724"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin Yang","raw_affiliation_strings":["JD.com America Technologies Corporation, Mountain View, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"JD.com America Technologies Corporation, Mountain View, CA, USA","institution_ids":[]}]},{"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"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Montclair State University, Montclair, NJ, USA","institution_ids":["https://openalex.org/I166088655"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2785,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.70109786,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9958999752998352,"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"}},"topics":[{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9958999752998352,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9950000047683716,"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/T11309","display_name":"Music and Audio Processing","score":0.9778000116348267,"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/computer-science","display_name":"Computer science","score":0.723021924495697},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.673841118812561},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6136691570281982},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.6106328368186951},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5938248038291931},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4830239713191986},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4543560743331909},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.4410891532897949},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.4175852835178375},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3654713034629822},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33601564168930054}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.723021924495697},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.673841118812561},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6136691570281982},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.6106328368186951},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5938248038291931},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4830239713191986},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4543560743331909},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.4410891532897949},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4175852835178375},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3654713034629822},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33601564168930054},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom42002.2020.9322300","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom42002.2020.9322300","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2020 - 2020 IEEE Global Communications Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7599999904632568}],"awards":[{"id":"https://openalex.org/G2779465245","display_name":null,"funder_award_id":"2018YFB1700100","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G7702814283","display_name":null,"funder_award_id":"DUT18JC28,DUT19ZD103","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"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":19,"referenced_works":["https://openalex.org/W1959608418","https://openalex.org/W2253995343","https://openalex.org/W2619206542","https://openalex.org/W2886661492","https://openalex.org/W2897167574","https://openalex.org/W2912122876","https://openalex.org/W2924526555","https://openalex.org/W2962745591","https://openalex.org/W2963085847","https://openalex.org/W2984100107","https://openalex.org/W2989519942","https://openalex.org/W2998431760","https://openalex.org/W3101023724","https://openalex.org/W4289676341","https://openalex.org/W4320013936","https://openalex.org/W4385245566","https://openalex.org/W6640963894","https://openalex.org/W6739901393","https://openalex.org/W6753544890"],"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":{"It":[0],"is":[1,18,45,142],"difficult":[2],"for":[3,89,117],"users":[4,24],"to":[5,22,56,103,129],"find":[6],"the":[7,12,26,63,76,80,91,95,105,118,125,130,138,146],"required":[8],"information":[9],"promptly":[10],"in":[11],"massive":[13],"data.":[14],"The":[15,110],"collaborative":[16],"filtering":[17],"an":[19,33],"effective":[20],"way":[21],"help":[23],"get":[25],"proper":[27],"information.":[28],"To":[29],"achieve":[30],"better":[31,115,144],"performance,":[32],"improved":[34],"framework":[35],"based":[36],"on":[37,150],"variational":[38,59,101],"Generative":[39,86],"Adversarial":[40,87],"Networks":[41,88],"with":[42],"self-attention":[43,49,58,100],"(VGCF)":[44],"proposed.":[46],"In":[47],"VGCF,":[48],"mechanism":[50],"and":[51,68,74,79,120],"Variational":[52],"Autoencoders":[53],"are":[54],"combined":[55],"form":[57],"encoder,":[60],"which":[61,123],"improves":[62],"ability":[64],"of":[65,71,140],"acquiring":[66],"explicit":[67],"implicit":[69],"features":[70],"sparse":[72],"data":[73,132],"obtains":[75],"personal":[77],"preference":[78],"correlation":[81],"between":[82],"users.":[83],"By":[84],"utilizing":[85],"prediction,":[90],"generative":[92],"model":[93,112],"uses":[94],"compression":[96],"matrix":[97],"obtained":[98],"by":[99],"encoder":[102],"generate":[104],"predicted":[106],"user-items":[107],"interaction":[108],"matrix.":[109],"discriminative":[111],"provides":[113],"a":[114],"approximation":[116],"posterior":[119],"maximum-likelihood":[121],"assignment,":[122],"makes":[124],"generated":[126],"result":[127],"closer":[128],"real":[131],"distribution.":[133],"Finally,":[134],"we":[135],"show":[136],"that":[137],"performance":[139],"VGCF":[141],"significantly":[143],"than":[145],"state-of-the-art":[147],"recommendation":[148],"methods":[149],"several":[151],"real-world":[152],"datasets.":[153]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}