{"id":"https://openalex.org/W3209495512","doi":"https://doi.org/10.1145/3459637.3482390","title":"Semi-deterministic and Contrastive Variational Graph Autoencoder for Recommendation","display_name":"Semi-deterministic and Contrastive Variational Graph Autoencoder for Recommendation","publication_year":2021,"publication_date":"2021-10-26","ids":{"openalex":"https://openalex.org/W3209495512","doi":"https://doi.org/10.1145/3459637.3482390","mag":"3209495512"},"language":"en","primary_location":{"id":"doi:10.1145/3459637.3482390","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482390","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information & Knowledge Management","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/A5100688231","display_name":"Yue Ding","orcid":"https://orcid.org/0000-0002-2911-1244"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yue Ding","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110800866","display_name":"Yuxiang Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxiang Shi","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100427434","display_name":"Bo Chen","orcid":"https://orcid.org/0000-0003-3750-2533"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Chen","raw_affiliation_strings":["Noah's Ark Lab, Huawei, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Noah's Ark Lab, Huawei, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024599321","display_name":"Chenghua Lin","orcid":"https://orcid.org/0000-0003-3454-2468"},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Chenghua Lin","raw_affiliation_strings":["The University of Sheffield, Sheffield, United Kingdom"],"affiliations":[{"raw_affiliation_string":"The University of Sheffield, Sheffield, United Kingdom","institution_ids":["https://openalex.org/I91136226"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102899381","display_name":"Hongtao Lu","orcid":"https://orcid.org/0000-0003-2300-3039"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongtao Lu","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100679241","display_name":"Jie Li","orcid":"https://orcid.org/0000-0002-4974-6116"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Li","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054330014","display_name":"Ruiming Tang","orcid":"https://orcid.org/0000-0002-9224-2431"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruiming Tang","raw_affiliation_strings":["Noah's Ark Lab, Huawei, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Noah's Ark Lab, Huawei, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100391562","display_name":"Dong Wang","orcid":"https://orcid.org/0000-0003-4872-4860"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Wang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5100688231"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":1.6525,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.87460793,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"382","last_page":"391"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9994000196456909,"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":0.9994000196456909,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9961000084877014,"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/T10028","display_name":"Topic Modeling","score":0.9925000071525574,"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/autoencoder","display_name":"Autoencoder","score":0.7565383315086365},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6500469446182251},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.553779125213623},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4970143139362335},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.47282278537750244},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4520067572593689},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.42169392108917236},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.38481712341308594},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.35049760341644287},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.34681516885757446},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34268152713775635},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.27561765909194946},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2698909044265747},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.2369854748249054}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7565383315086365},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6500469446182251},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.553779125213623},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4970143139362335},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47282278537750244},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4520067572593689},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.42169392108917236},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.38481712341308594},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.35049760341644287},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34681516885757446},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34268152713775635},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.27561765909194946},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2698909044265747},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.2369854748249054},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3459637.3482390","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482390","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1533861849","https://openalex.org/W1959608418","https://openalex.org/W2054141820","https://openalex.org/W2225156818","https://openalex.org/W2557579533","https://openalex.org/W2605350416","https://openalex.org/W2725606191","https://openalex.org/W2747329762","https://openalex.org/W2753738274","https://openalex.org/W2767948492","https://openalex.org/W2784067649","https://openalex.org/W2803244426","https://openalex.org/W2883308936","https://openalex.org/W2893944917","https://openalex.org/W2901227482","https://openalex.org/W2912298496","https://openalex.org/W2916106175","https://openalex.org/W2945827670","https://openalex.org/W2949871834","https://openalex.org/W2951873722","https://openalex.org/W2956136341","https://openalex.org/W2962711740","https://openalex.org/W2963085847","https://openalex.org/W2963376432","https://openalex.org/W2963522047","https://openalex.org/W2963622136","https://openalex.org/W2963799213","https://openalex.org/W2964121744","https://openalex.org/W2964184826","https://openalex.org/W2970574558","https://openalex.org/W2971187489","https://openalex.org/W2982602185","https://openalex.org/W2990155616","https://openalex.org/W2994610548","https://openalex.org/W2997223565","https://openalex.org/W2997617192","https://openalex.org/W3003952093","https://openalex.org/W3041956526","https://openalex.org/W3045200674","https://openalex.org/W3098638686","https://openalex.org/W3100278010","https://openalex.org/W3101380508","https://openalex.org/W3102467995","https://openalex.org/W3135995094","https://openalex.org/W3154345605","https://openalex.org/W3159654895","https://openalex.org/W4289436753"],"related_works":["https://openalex.org/W2159052453","https://openalex.org/W2470043383","https://openalex.org/W2953501176","https://openalex.org/W2965095304","https://openalex.org/W3034474024","https://openalex.org/W2770818364","https://openalex.org/W4317242571","https://openalex.org/W2944085132","https://openalex.org/W2169866437","https://openalex.org/W1964286703"],"abstract_inverted_index":{"Variational":[0,152],"AutoEncoder":[1,31],"(VAE)":[2],"is":[3,164],"a":[4,10,26,34,52,66,128,147,176],"popular":[5],"deep":[6],"generative":[7,38,135],"framework":[8],"with":[9],"solid":[11],"theoretical":[12],"basis.":[13],"There":[14],"are":[15,274],"many":[16],"research":[17,109],"efforts":[18],"on":[19,138,254],"improving":[20],"VAE.":[21],"Among":[22],"the":[23,42,45,56,63,70,81,114,124,139,167,170,194,200,208,212,233,247,260,269],"existing":[24],"works,":[25],"recently":[27],"proposed":[28],"deterministic":[29,67,71],"Regularized":[30],"(RAE)":[32],"provides":[33],"new":[35],"scheme":[36],"for":[37,156,199,268],"modeling.":[39],"RAE":[40,72,77,84,94],"fixes":[41],"variance":[43,168],"of":[44,65,116,162,169,197,211,216,226,262],"inferred":[46,181],"Gaussian":[47,172],"approximate":[48,171],"posterior":[49,173],"distribution":[50,174],"as":[51],"hyperparameter,":[53],"and":[54,122,150,205,243],"substitutes":[55],"stochastic":[57],"encoder":[58],"by":[59,179],"injecting":[60],"noise":[61],"into":[62],"input":[64],"decoder.":[68],"However,":[69],"has":[73],"three":[74,255],"limitations:":[75],"1)":[76],"needs":[78],"to":[79,89,100,132,165,245,258],"fit":[80],"variance;":[82],"2)":[83],"requires":[85],"ex-post":[86],"density":[87],"estimation":[88],"ensure":[90,101],"sample":[91],"quality;":[92],"3)":[93],"employs":[95],"an":[96,107,221],"additional":[97],"gradient":[98,227],"regularization":[99,224,235],"training":[102,130,248],"smoothness.":[103],"Thus,":[104],"it":[105],"raises":[106],"interesting":[108],"question:":[110],"Can":[111],"we":[112,145,206,219],"maintain":[113],"flexibility":[115],"variational":[117],"inference":[118],"while":[119],"simplifying":[120],"VAE,":[121],"at":[123,276],"same":[125],"time":[126],"ensuring":[127],"smooth":[129,246],"process":[131],"obtain":[133],"good":[134],"performance?":[136],"Based":[137],"above":[140],"motivation,":[141],"in":[142,175],"this":[143],"paper,":[144],"propose":[146],"novel":[148],"Semi-deterministic":[149],"Contrastive":[151],"Graph":[153],"autoencoder":[154],"(SCVG)":[155],"item":[157,270],"recommendation.":[158],"The":[159],"core":[160],"design":[161],"SCVG":[163,198],"learn":[166],"semi-deterministic":[177],"manner":[178],"aggregating":[180],"mean":[182],"vectors":[183],"from":[184],"other":[185],"connected":[186],"nodes":[187],"via":[188],"graph":[189,202],"convolution":[190],"operation.":[191],"We":[192,229,250],"analyze":[193],"expressive":[195],"power":[196],"Weisfeiler-Lehman":[201],"isomorphism":[203],"test,":[204],"deduce":[207],"simplified":[209],"form":[210],"evidence":[213],"lower":[214],"bound":[215],"SCVG.":[217],"Besides,":[218],"introduce":[220],"efficient":[222],"contrastive":[223,234],"instead":[225],"regularization.":[228],"empirically":[230],"show":[231,259],"that":[232],"makes":[236],"learned":[237],"user/item":[238],"latent":[239],"representation":[240],"more":[241],"personalized":[242],"helps":[244],"process.":[249],"conduct":[251],"extensive":[252],"experiments":[253],"real-world":[256],"datasets":[257],"superiority":[261],"our":[263],"model":[264],"over":[265],"state-of-the-art":[266],"methods":[267],"recommendation":[271],"task.":[272],"Codes":[273],"available":[275],"https://github.com/syxkason/SCVG.":[277]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}