{"id":"https://openalex.org/W4388977727","doi":"https://doi.org/10.1145/3634686","title":"A Privacy Preserving System for Movie Recommendations Using Federated Learning","display_name":"A Privacy Preserving System for Movie Recommendations Using Federated Learning","publication_year":2023,"publication_date":"2023-11-24","ids":{"openalex":"https://openalex.org/W4388977727","doi":"https://doi.org/10.1145/3634686"},"language":"en","primary_location":{"id":"doi:10.1145/3634686","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3634686","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3634686","source":{"id":"https://openalex.org/S4387284325","display_name":"ACM Transactions on Recommender Systems","issn_l":"2770-6699","issn":["2770-6699"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Recommender Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3634686","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102743673","display_name":"David Neumann","orcid":"https://orcid.org/0000-0003-1907-8329"},"institutions":[{"id":"https://openalex.org/I2800274787","display_name":"Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute","ror":"https://ror.org/02tbr6331","country_code":"DE","type":"facility","lineage":["https://openalex.org/I2800274787","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"David Neumann","raw_affiliation_strings":["Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute, HHI, Berlin, Germany","Scientific Researcher Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute, HHI [0]Department of Artificial Intelligence [1]Efficient Deep Learning Group Einsteinufer 37 10587 Berlin , Germany"],"raw_orcid":"https://orcid.org/0000-0003-1907-8329","affiliations":[{"raw_affiliation_string":"Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute, HHI, Berlin, Germany","institution_ids":["https://openalex.org/I2800274787"]},{"raw_affiliation_string":"Scientific Researcher Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute, HHI [0]Department of Artificial Intelligence [1]Efficient Deep Learning Group Einsteinufer 37 10587 Berlin , Germany","institution_ids":["https://openalex.org/I2800274787"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114044221","display_name":"Andreas Lutz","orcid":"https://orcid.org/0000-0002-2973-0096"},"institutions":[{"id":"https://openalex.org/I2800274787","display_name":"Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute","ror":"https://ror.org/02tbr6331","country_code":"DE","type":"facility","lineage":["https://openalex.org/I2800274787","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Andreas Lutz","raw_affiliation_strings":["Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute, HHI, Berlin, Germany","Student Research Assistant Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute, HHI [0]Department of Artificial Intelligence [1]Efficient Deep Learning Group Einsteinufer 37 10587 Berlin , Germany"],"raw_orcid":"https://orcid.org/0000-0002-2973-0096","affiliations":[{"raw_affiliation_string":"Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute, HHI, Berlin, Germany","institution_ids":["https://openalex.org/I2800274787"]},{"raw_affiliation_string":"Student Research Assistant Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute, HHI [0]Department of Artificial Intelligence [1]Efficient Deep Learning Group Einsteinufer 37 10587 Berlin , Germany","institution_ids":["https://openalex.org/I2800274787"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019469492","display_name":"Karsten M\u00fcller","orcid":null},"institutions":[{"id":"https://openalex.org/I2800274787","display_name":"Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute","ror":"https://ror.org/02tbr6331","country_code":"DE","type":"facility","lineage":["https://openalex.org/I2800274787","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Karsten M\u00fcller","raw_affiliation_strings":["Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute, HHI, Berlin, Germany","Head of Efficient Deep Learning Group Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute, HHI [0]Department of Artificial Intelligence [1]Efficient Deep Learning Group Einsteinufer 37 10587 Berlin , Germany"],"raw_orcid":"https://orcid.org/0000-0001-8611-7864","affiliations":[{"raw_affiliation_string":"Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute, HHI, Berlin, Germany","institution_ids":["https://openalex.org/I2800274787"]},{"raw_affiliation_string":"Head of Efficient Deep Learning Group Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute, HHI [0]Department of Artificial Intelligence [1]Efficient Deep Learning Group Einsteinufer 37 10587 Berlin , Germany","institution_ids":["https://openalex.org/I2800274787"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026451495","display_name":"Wojciech Samek","orcid":"https://orcid.org/0000-0002-6283-3265"},"institutions":[{"id":"https://openalex.org/I2800274787","display_name":"Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute","ror":"https://ror.org/02tbr6331","country_code":"DE","type":"facility","lineage":["https://openalex.org/I2800274787","https://openalex.org/I4923324"]},{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Wojciech Samek","raw_affiliation_strings":["Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute, HHI, Berlin, Germany and Technical University of Berlin, Berlin, Germany","Artificial Intelligence, Fraunhofer-Institut f\u00fcr Nachrichtentechnik, Heinrich-Hertz-Institut, HHI, Berlin, Germany","Department of Electrical Engineering and Computer Science, Technical University of Berlin, Berlin, Germany"],"raw_orcid":"https://orcid.org/0000-0002-6283-3265","affiliations":[{"raw_affiliation_string":"Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute, HHI, Berlin, Germany and Technical University of Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I2800274787"]},{"raw_affiliation_string":"Artificial Intelligence, Fraunhofer-Institut f\u00fcr Nachrichtentechnik, Heinrich-Hertz-Institut, HHI, Berlin, Germany","institution_ids":["https://openalex.org/I2800274787"]},{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Technical University of Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.8727,"has_fulltext":true,"cited_by_count":22,"citation_normalized_percentile":{"value":0.92550667,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"3","issue":"2","first_page":"1","last_page":"51"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9998999834060669,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9998999834060669,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9976999759674072,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.986299991607666,"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":0.8395888805389404},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.6724777221679688},{"id":"https://openalex.org/keywords/lossy-compression","display_name":"Lossy compression","score":0.5734462738037109},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5529626607894897},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.5170201063156128},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.45073994994163513},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4328123927116394},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.38701727986335754},{"id":"https://openalex.org/keywords/internet-privacy","display_name":"Internet privacy","score":0.36800748109817505},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2992531657218933}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8395888805389404},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.6724777221679688},{"id":"https://openalex.org/C165021410","wikidata":"https://www.wikidata.org/wiki/Q55564","display_name":"Lossy compression","level":2,"score":0.5734462738037109},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5529626607894897},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.5170201063156128},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.45073994994163513},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4328123927116394},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.38701727986335754},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.36800748109817505},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2992531657218933},{"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/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3634686","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3634686","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3634686","source":{"id":"https://openalex.org/S4387284325","display_name":"ACM Transactions on Recommender Systems","issn_l":"2770-6699","issn":["2770-6699"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Recommender Systems","raw_type":"journal-article"},{"id":"pmh:oai:publica.fraunhofer.de:publica/464095","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/464095","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"journal article"}],"best_oa_location":{"id":"doi:10.1145/3634686","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3634686","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3634686","source":{"id":"https://openalex.org/S4387284325","display_name":"ACM Transactions on Recommender Systems","issn_l":"2770-6699","issn":["2770-6699"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Recommender Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6700000166893005,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G434337789","display_name":null,"funder_award_id":"HORIZON2020","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G5087770886","display_name":"COllaborative Platform for trAnsmedia storytelling and cross channel distribution of EUROPEan sport events","funder_award_id":"957059","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4388977727.pdf","grobid_xml":"https://content.openalex.org/works/W4388977727.grobid-xml"},"referenced_works_count":100,"referenced_works":["https://openalex.org/W18112494","https://openalex.org/W1720514416","https://openalex.org/W1834627138","https://openalex.org/W1994389483","https://openalex.org/W1994616650","https://openalex.org/W2002169919","https://openalex.org/W2009797711","https://openalex.org/W2053637704","https://openalex.org/W2054141820","https://openalex.org/W2064675550","https://openalex.org/W2108862644","https://openalex.org/W2112796928","https://openalex.org/W2141420453","https://openalex.org/W2149427297","https://openalex.org/W2150593711","https://openalex.org/W2167879950","https://openalex.org/W2210543184","https://openalex.org/W2219888463","https://openalex.org/W2253995343","https://openalex.org/W2397857137","https://openalex.org/W2469508028","https://openalex.org/W2512971201","https://openalex.org/W2535708379","https://openalex.org/W2605350416","https://openalex.org/W2734358244","https://openalex.org/W2781091734","https://openalex.org/W2783272285","https://openalex.org/W2807021761","https://openalex.org/W2808787330","https://openalex.org/W2811423811","https://openalex.org/W2885195348","https://openalex.org/W2896422817","https://openalex.org/W2903890850","https://openalex.org/W2913668833","https://openalex.org/W2953902152","https://openalex.org/W2955213239","https://openalex.org/W2963935227","https://openalex.org/W2964199361","https://openalex.org/W2970567869","https://openalex.org/W2975043678","https://openalex.org/W2978015420","https://openalex.org/W2989289980","https://openalex.org/W2994684563","https://openalex.org/W3000479830","https://openalex.org/W3004198379","https://openalex.org/W3008665070","https://openalex.org/W3015807225","https://openalex.org/W3016632787","https://openalex.org/W3034503922","https://openalex.org/W3038022836","https://openalex.org/W3047789363","https://openalex.org/W3064112253","https://openalex.org/W3080293527","https://openalex.org/W3081273427","https://openalex.org/W3085804918","https://openalex.org/W3090814594","https://openalex.org/W3100035104","https://openalex.org/W3100848837","https://openalex.org/W3134746691","https://openalex.org/W3137510859","https://openalex.org/W3140753276","https://openalex.org/W3160164683","https://openalex.org/W3161487422","https://openalex.org/W3174074918","https://openalex.org/W3174208514","https://openalex.org/W3181576318","https://openalex.org/W3190695173","https://openalex.org/W3194693407","https://openalex.org/W3196371845","https://openalex.org/W3199975223","https://openalex.org/W3201463768","https://openalex.org/W3202088367","https://openalex.org/W3214161899","https://openalex.org/W4205228770","https://openalex.org/W4206688953","https://openalex.org/W4210871688","https://openalex.org/W4213390626","https://openalex.org/W4224227775","https://openalex.org/W4238100585","https://openalex.org/W4281609047","https://openalex.org/W4282813193","https://openalex.org/W4282937261","https://openalex.org/W4283523864","https://openalex.org/W4283711440","https://openalex.org/W4289147229","https://openalex.org/W4289655313","https://openalex.org/W4294963575","https://openalex.org/W4302024112","https://openalex.org/W4307413946","https://openalex.org/W4310633849","https://openalex.org/W4312191182","https://openalex.org/W4313484570","https://openalex.org/W4313611128","https://openalex.org/W4317434693","https://openalex.org/W4375869356","https://openalex.org/W4377097576","https://openalex.org/W4385805175","https://openalex.org/W6824583106","https://openalex.org/W6830701505","https://openalex.org/W6944211801"],"related_works":["https://openalex.org/W2772628444","https://openalex.org/W2735929803","https://openalex.org/W4220714703","https://openalex.org/W1484355083","https://openalex.org/W3008845055","https://openalex.org/W2098758514","https://openalex.org/W4376854386","https://openalex.org/W2202724490","https://openalex.org/W2508671622","https://openalex.org/W2556532874"],"abstract_inverted_index":{"Recommender":[0],"systems":[1,43],"have":[2],"become":[3],"ubiquitous":[4],"in":[5],"the":[6,11,142,165,174],"past":[7],"years.":[8],"They":[9],"solve":[10],"tyranny":[12],"of":[13,51,144,182],"choice":[14],"problem":[15,143],"faced":[16],"by":[17,23,114,157],"many":[18,24],"users,":[19],"and":[20,30,97,104,112,146],"are":[21,44],"utilized":[22],"online":[25],"businesses":[26],"to":[27,55,75,123,163,179],"drive":[28],"engagement":[29],"sales.":[31],"Besides":[32],"other":[33],"criticisms,":[34],"like":[35],"creating":[36],"filter":[37],"bubbles":[38],"within":[39],"social":[40],"networks,":[41],"recommender":[42,89],"often":[45],"reproved":[46],"for":[47,91],"collecting":[48],"considerable":[49],"amounts":[50],"personal":[52,58,78],"data.":[53],"However,":[54],"personalize":[56],"recommendations,":[57,93],"information":[59],"is":[60,107,136,169],"fundamentally":[61],"required.":[62],"A":[63],"recent":[64],"distributed":[65],"learning":[66,70,111,132],"scheme":[67],"called":[68,134],"federated":[69,110,131],"has":[71],"made":[72],"it":[73,106],"possible":[74],"learn":[76],"from":[77,125],"user":[79],"data":[80,154,193],"without":[81],"its":[82,115,196],"central":[83],"collection.":[84],"Consequently,":[85],"we":[86],"present":[87],"a":[88,129,180],"system":[90],"movie":[92],"which":[94,138,171],"provides":[95],"privacy":[96,194],"thus":[98],"trustworthiness":[99],"on":[100],"multiple":[101],"levels:":[102],"First":[103],"foremost,":[105],"trained":[108],"using":[109],"thus,":[113],"very":[116],"nature,":[117],"privacy-preserving,":[118],"while":[119],"still":[120],"enabling":[121],"users":[122],"benefit":[124],"global":[126],"insights.":[127],"Furthermore,":[128],"novel":[130],"scheme,":[133],"FedQ,":[135],"employed,":[137],"not":[139],"only":[140],"addresses":[141],"non-i.i.d.-ness":[145],"small":[147],"local":[148],"datasets,":[149],"but":[150],"also":[151,191],"prevents":[152],"input":[153],"reconstruction":[155],"attacks":[156],"aggregating":[158],"client":[159],"updates":[160],"early.":[161],"Finally,":[162],"reduce":[164],"communication":[166],"overhead,":[167],"compression":[168],"applied,":[170],"significantly":[172],"compresses":[173],"exchanged":[175],"neural":[176],"network":[177],"parametrizations":[178],"fraction":[181],"their":[183],"original":[184],"size.":[185],"We":[186],"conjecture":[187],"that":[188],"this":[189],"may":[190],"improve":[192],"through":[195],"lossy":[197],"quantization":[198],"stage.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1}],"updated_date":"2026-08-04T08:18:43.703281","created_date":"2023-11-25T00:00:00"}