{"id":"https://openalex.org/W3088364587","doi":"https://doi.org/10.1145/3383313.3412268","title":"TAFA: Two-headed Attention Fused Autoencoder for Context-Aware Recommendations","display_name":"TAFA: Two-headed Attention Fused Autoencoder for Context-Aware Recommendations","publication_year":2020,"publication_date":"2020-09-19","ids":{"openalex":"https://openalex.org/W3088364587","doi":"https://doi.org/10.1145/3383313.3412268","mag":"3088364587"},"language":"en","primary_location":{"id":"doi:10.1145/3383313.3412268","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3383313.3412268","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3383313.3412268","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fourteenth ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3383313.3412268","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070503869","display_name":"Jin Peng Zhou","orcid":"https://orcid.org/0000-0001-8407-1110"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jin Peng Zhou","raw_affiliation_strings":["Layer 6 AI, Canada"],"affiliations":[{"raw_affiliation_string":"Layer 6 AI, Canada","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062856371","display_name":"Zhaoyue Cheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhaoyue Cheng","raw_affiliation_strings":["Layer 6 AI, Canada"],"affiliations":[{"raw_affiliation_string":"Layer 6 AI, Canada","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108282056","display_name":"Felipe P\u00e9rez","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Felipe Perez","raw_affiliation_strings":["Layer 6 AI, Canada"],"affiliations":[{"raw_affiliation_string":"Layer 6 AI, Canada","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027341076","display_name":"Maksims Volkovs","orcid":"https://orcid.org/0009-0007-0561-2187"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Maksims Volkovs","raw_affiliation_strings":["Layer 6 AI, Canada"],"affiliations":[{"raw_affiliation_string":"Layer 6 AI, Canada","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5070503869"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.8719,"has_fulltext":true,"cited_by_count":37,"citation_normalized_percentile":{"value":0.96462586,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"338","last_page":"347"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9858999848365784,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9837999939918518,"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/computer-science","display_name":"Computer science","score":0.833753228187561},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.7365936040878296},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.721366286277771},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.703071653842926},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5232676267623901},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5091604590415955},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4834943115711212},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4599247872829437},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.4547325074672699},{"id":"https://openalex.org/keywords/salience","display_name":"Salience (neuroscience)","score":0.4420262575149536},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.42294052243232727},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3171314597129822}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.833753228187561},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7365936040878296},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.721366286277771},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.703071653842926},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5232676267623901},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5091604590415955},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4834943115711212},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4599247872829437},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4547325074672699},{"id":"https://openalex.org/C108154423","wikidata":"https://www.wikidata.org/wiki/Q1469792","display_name":"Salience (neuroscience)","level":2,"score":0.4420262575149536},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.42294052243232727},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3171314597129822},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3383313.3412268","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3383313.3412268","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3383313.3412268","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fourteenth ACM Conference on Recommender Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3383313.3412268","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3383313.3412268","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3383313.3412268","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fourteenth ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3088364587.pdf","grobid_xml":"https://content.openalex.org/works/W3088364587.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W1720514416","https://openalex.org/W2025768430","https://openalex.org/W2054141820","https://openalex.org/W2078488685","https://openalex.org/W2124187902","https://openalex.org/W2152790380","https://openalex.org/W2157881433","https://openalex.org/W2250539671","https://openalex.org/W2253995343","https://openalex.org/W2463645429","https://openalex.org/W2515144511","https://openalex.org/W2531563875","https://openalex.org/W2573167395","https://openalex.org/W2575006718","https://openalex.org/W2604433096","https://openalex.org/W2604738573","https://openalex.org/W2606749808","https://openalex.org/W2615395371","https://openalex.org/W2740253077","https://openalex.org/W2788376297","https://openalex.org/W2788953034","https://openalex.org/W2799048248","https://openalex.org/W2905305843","https://openalex.org/W2921980263","https://openalex.org/W2951707557","https://openalex.org/W2954808392","https://openalex.org/W2957191877","https://openalex.org/W2963085847","https://openalex.org/W2963519394","https://openalex.org/W3017158675","https://openalex.org/W3047171579","https://openalex.org/W3105114834","https://openalex.org/W3122507327"],"related_works":["https://openalex.org/W2368605798","https://openalex.org/W2518037665","https://openalex.org/W2348524959","https://openalex.org/W2159052453","https://openalex.org/W3013693939","https://openalex.org/W2368049389","https://openalex.org/W2384861574","https://openalex.org/W2952704802","https://openalex.org/W2566616303","https://openalex.org/W2970845521"],"abstract_inverted_index":{"Collaborative":[0],"filtering":[1],"with":[2,58],"implicit":[3,32,102,155],"feedback":[4,33,103,156],"is":[5,246],"a":[6,51,139,202],"ubiquitous":[7],"class":[8],"of":[9,54,88,97],"recommendation":[10,24],"problems":[11],"where":[12],"only":[13],"positive":[14],"interactions":[15],"such":[16],"as":[17],"purchases":[18],"or":[19],"clicks":[20],"are":[21,62,78,107],"observed.":[22],"Autoencoder-based":[23],"models":[25,37],"have":[26],"shown":[27],"strong":[28],"performance":[29],"on":[30,214],"many":[31],"benchmarks.":[34,217],"However,":[35],"these":[36,135],"tend":[38],"to":[39,64,90,113,157,171,195,224],"suffer":[40],"from":[41,101,121,151,178],"popularity":[42,72,185],"bias":[43],"making":[44],"recommendations":[45,233],"less":[46],"personalized.":[47],"User-generated":[48],"reviews":[49,77,153,225],"contain":[50],"rich":[52],"source":[53],"preference":[55],"information,":[56],"often":[57],"specific":[59],"details":[60],"that":[61,147,209],"important":[63],"each":[65],"user,":[66],"and":[67,104,129,154,163,174,234],"can":[68,117,227],"help":[69],"mitigate":[70],"the":[71,95,111,119,126,169,189,197,231],"bias.":[73],"Since":[74],"not":[75],"all":[76],"equally":[79],"useful,":[80],"existing":[81],"work":[82,245],"has":[83],"been":[84],"exploring":[85],"various":[86],"forms":[87],"attention":[89,221],"distill":[91],"relevant":[92,176],"information.":[93],"In":[94],"majority":[96],"proposed":[98],"approaches,":[99],"representations":[100,150],"review":[105],"branches":[106],"simply":[108],"concatenated":[109],"at":[110],"end":[112],"generate":[114],"predictions.":[115],"This":[116],"prevent":[118],"model":[120,146,170],"learning":[122],"deeper":[123],"correlations":[124],"between":[125],"two":[127],"modalities":[128],"affect":[130],"prediction":[131],"accuracy.":[132],"To":[133,182],"address":[134],"problems,":[136],"we":[137,187,207,226],"propose":[138],"novel":[140],"Two-headed":[141],"Attention":[142],"Fused":[143],"Autoencoder":[144],"(TAFA)":[145],"jointly":[148],"learns":[149],"user":[152,199,239],"make":[158],"recommendations.":[159],"We":[160],"apply":[161],"early":[162],"late":[164],"modality":[165],"fusion":[166],"which":[167],"allows":[168],"fully":[172],"correlate":[173],"extract":[175],"information":[177],"both":[179],"input":[180],"sources.":[181],"further":[183,236],"combat":[184],"bias,":[186],"leverage":[188],"Noise":[190],"Contrastive":[191],"Estimation":[192],"(NCE)":[193],"objective":[194],"\u201cde-popularize\u201d":[196],"fused":[198],"representation":[200],"via":[201],"two-headed":[203],"decoder":[204],"architecture.":[205],"Empirically,":[206],"show":[208],"TAFA":[210],"outperforms":[211],"leading":[212],"baselines":[213],"multiple":[215],"real-world":[216],"Moreover,":[218],"by":[219],"tracing":[220],"weights":[222],"back":[223],"provide":[228],"explanations":[229],"for":[230,243],"generated":[232],"gain":[235],"insights":[237],"into":[238],"preferences.":[240],"Full":[241],"code":[242],"this":[244],"available":[247],"here:":[248],"https://github.com/layer6ai-labs/TAFA.":[249]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
