{"id":"https://openalex.org/W3007399118","doi":"https://doi.org/10.1109/bigdata47090.2019.9006313","title":"Deep Neural Networks as Similitude Models for Sharing Big Data","display_name":"Deep Neural Networks as Similitude Models for Sharing Big Data","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3007399118","doi":"https://doi.org/10.1109/bigdata47090.2019.9006313","mag":"3007399118"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata47090.2019.9006313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006313","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (Big Data)","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/A5017805559","display_name":"Philip Derbeko","orcid":"https://orcid.org/0000-0002-8904-3108"},"institutions":[{"id":"https://openalex.org/I124227911","display_name":"Ben-Gurion University of the Negev","ror":"https://ror.org/05tkyf982","country_code":"IL","type":"education","lineage":["https://openalex.org/I124227911"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Philip Derbeko","raw_affiliation_strings":["Ben-Gurion University of the Negev, Beer-Sheva, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ben-Gurion University of the Negev, Beer-Sheva, Israel","institution_ids":["https://openalex.org/I124227911"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060182415","display_name":"Shlomi Dolev","orcid":"https://orcid.org/0000-0001-5418-6670"},"institutions":[{"id":"https://openalex.org/I124227911","display_name":"Ben-Gurion University of the Negev","ror":"https://ror.org/05tkyf982","country_code":"IL","type":"education","lineage":["https://openalex.org/I124227911"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Shlomi Dolev","raw_affiliation_strings":["Ben-Gurion University of the Negev, Beer-Sheva, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ben-Gurion University of the Negev, Beer-Sheva, Israel","institution_ids":["https://openalex.org/I124227911"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101602501","display_name":"Ehud Gudes","orcid":"https://orcid.org/0000-0003-0687-086X"},"institutions":[{"id":"https://openalex.org/I124227911","display_name":"Ben-Gurion University of the Negev","ror":"https://ror.org/05tkyf982","country_code":"IL","type":"education","lineage":["https://openalex.org/I124227911"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Ehud Gudes","raw_affiliation_strings":["Ben-Gurion University of the Negev, Beer-Sheva, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ben-Gurion University of the Negev, Beer-Sheva, Israel","institution_ids":["https://openalex.org/I124227911"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1446,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.61640951,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"abs 1312 6114","issue":null,"first_page":"5728","last_page":"5736"},"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.994700014591217,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9861000180244446,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/similitude","display_name":"Similitude","score":0.7588732242584229},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7209469079971313},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6126842498779297},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.5412660837173462},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47088345885276794},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4495962858200073},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.41626426577568054},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38204193115234375},{"id":"https://openalex.org/keywords/software-engineering","display_name":"Software engineering","score":0.10668230056762695}],"concepts":[{"id":"https://openalex.org/C143271835","wikidata":"https://www.wikidata.org/wiki/Q254515","display_name":"Similitude","level":2,"score":0.7588732242584229},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7209469079971313},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6126842498779297},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.5412660837173462},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47088345885276794},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4495962858200073},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.41626426577568054},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38204193115234375},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.10668230056762695}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bigdata47090.2019.9006313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006313","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},{"id":"mag:3043567266","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=202002229338047178","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":71,"referenced_works":["https://openalex.org/W1494985239","https://openalex.org/W1873763122","https://openalex.org/W1909320841","https://openalex.org/W1959608418","https://openalex.org/W1965555277","https://openalex.org/W1971459440","https://openalex.org/W1993116423","https://openalex.org/W1996784330","https://openalex.org/W2011430131","https://openalex.org/W2019363670","https://openalex.org/W2021850646","https://openalex.org/W2064675550","https://openalex.org/W2071511328","https://openalex.org/W2072128103","https://openalex.org/W2080785753","https://openalex.org/W2092422002","https://openalex.org/W2099471712","https://openalex.org/W2101771965","https://openalex.org/W2103012681","https://openalex.org/W2104803737","https://openalex.org/W2110557355","https://openalex.org/W2123820077","https://openalex.org/W2126398289","https://openalex.org/W2127867569","https://openalex.org/W2134569822","https://openalex.org/W2134842679","https://openalex.org/W2145094598","https://openalex.org/W2149545836","https://openalex.org/W2166214172","https://openalex.org/W2473418344","https://openalex.org/W2541884796","https://openalex.org/W2619508703","https://openalex.org/W2808185587","https://openalex.org/W2885673189","https://openalex.org/W2896457183","https://openalex.org/W2910022251","https://openalex.org/W2911978475","https://openalex.org/W2912934387","https://openalex.org/W2953267151","https://openalex.org/W2963341956","https://openalex.org/W2963403868","https://openalex.org/W2963848253","https://openalex.org/W2964049407","https://openalex.org/W2997574889","https://openalex.org/W3099514962","https://openalex.org/W3141585064","https://openalex.org/W4206181323","https://openalex.org/W4212883601","https://openalex.org/W4231109964","https://openalex.org/W4238472918","https://openalex.org/W4254407475","https://openalex.org/W4293568373","https://openalex.org/W4318619660","https://openalex.org/W4320013936","https://openalex.org/W4385245566","https://openalex.org/W6639246211","https://openalex.org/W6639732818","https://openalex.org/W6640963894","https://openalex.org/W6673580112","https://openalex.org/W6679061810","https://openalex.org/W6680067488","https://openalex.org/W6681096077","https://openalex.org/W6728757088","https://openalex.org/W6734208355","https://openalex.org/W6738591009","https://openalex.org/W6739901393","https://openalex.org/W6753384464","https://openalex.org/W6755207826","https://openalex.org/W6758340423","https://openalex.org/W6758947373","https://openalex.org/W6780248173"],"related_works":["https://openalex.org/W2323025356","https://openalex.org/W2342977227","https://openalex.org/W3033216323","https://openalex.org/W4376875328","https://openalex.org/W3107710733","https://openalex.org/W4390608645","https://openalex.org/W2802349803","https://openalex.org/W4247566972","https://openalex.org/W2227662128","https://openalex.org/W4394895745"],"abstract_inverted_index":{"The":[0],"amount":[1],"of":[2,12,29,35,51,61,89,95,99,110,123],"data":[3,24,42,53,64,79,96,101,117],"grows":[4,31],"rapidly":[5],"with":[6],"time":[7,73],"and":[8,19,22,32,74,136,147],"shows":[9],"no":[10],"signs":[11],"stopping.":[13],"Ubiquitous":[14],"computing":[15,68],"continues":[16],"to":[17,119,141],"collect":[18],"generate":[20],"more":[21,23],"as":[25,92,115],"both":[26,144],"the":[27,33,41,52,62,77,82,87,100,108,152],"number":[28],"devices":[30,36,45],"capabilities":[34],"increase.":[37],"We":[38],"suggest":[39,107],"processing":[40,72],"on":[43],"end":[44],"by":[46,130],"building":[47,131],"a":[48,57,116],"representative":[49],"model":[50,59,118],"(\u201csimilitude\u201d":[54],"model).":[55],"Sharing":[56],"smaller":[58],"instead":[60,98],"entire":[63,153],"allows":[65],"for":[66],"saving":[67],"power,":[69],"network":[70,135],"time,":[71],"also,":[75],"keeping":[76],"collected":[78],"private.":[80],"In":[81,103],"past":[83],"research,":[84],"we":[85,106,127],"suggested":[86],"use":[88,109],"similitude":[90],"models,":[91],"compact":[93],"models":[94,133],"representation":[97],"itself.":[102],"this":[104],"paper,":[105],"deep":[111],"neural":[112],"networks":[113],"(DNN)":[114],"answer":[120,142],"different":[121],"types":[122],"queries.":[124],"More":[125],"specifically,":[126],"show":[128],"that":[129],"two":[132],"(generative":[134],"auto-encoder)":[137],"it":[138],"is":[139],"possible":[140],"approximately":[143],"statistical":[145],"queries":[146,149],"membership":[148],"without":[150],"exposing":[151],"dataset.":[154]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}