{"id":"https://openalex.org/W2980848703","doi":"https://doi.org/10.1145/3336191.3371856","title":"Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations","display_name":"Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations","publication_year":2020,"publication_date":"2020-01-20","ids":{"openalex":"https://openalex.org/W2980848703","doi":"https://doi.org/10.1145/3336191.3371856","mag":"2980848703"},"language":"en","primary_location":{"id":"doi:10.1145/3336191.3371856","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3336191.3371856","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1910.08902","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021612761","display_name":"Oluwaseyi Feyisetan","orcid":"https://orcid.org/0000-0002-0786-9505"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]},{"id":"https://openalex.org/I4210089985","display_name":"Amazon (Germany)","ror":"https://ror.org/00b9ktm87","country_code":"DE","type":"company","lineage":["https://openalex.org/I1311688040","https://openalex.org/I4210089985"]}],"countries":["DE","US"],"is_corresponding":true,"raw_author_name":"Oluwaseyi Feyisetan","raw_affiliation_strings":["Amazon, Seattle, WA, USA","Amazon"],"affiliations":[{"raw_affiliation_string":"Amazon, Seattle, WA, USA","institution_ids":["https://openalex.org/I1311688040"]},{"raw_affiliation_string":"Amazon","institution_ids":["https://openalex.org/I4210089985"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085679401","display_name":"Borja Balle","orcid":"https://orcid.org/0009-0003-8726-2803"},"institutions":[{"id":"https://openalex.org/I4210123934","display_name":"Amazon (United Kingdom)","ror":"https://ror.org/02xey9634","country_code":"GB","type":"company","lineage":["https://openalex.org/I1311688040","https://openalex.org/I4210123934"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Borja Balle","raw_affiliation_strings":["Amazon, Cambridge, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Amazon, Cambridge, United Kingdom","institution_ids":["https://openalex.org/I4210123934"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056927941","display_name":"Thomas M Drake","orcid":"https://orcid.org/0000-0002-9334-6494"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]},{"id":"https://openalex.org/I4210089985","display_name":"Amazon (Germany)","ror":"https://ror.org/00b9ktm87","country_code":"DE","type":"company","lineage":["https://openalex.org/I1311688040","https://openalex.org/I4210089985"]}],"countries":["DE","US"],"is_corresponding":false,"raw_author_name":"Thomas Drake","raw_affiliation_strings":["Amazon, Seattle, WA, USA","Amazon"],"affiliations":[{"raw_affiliation_string":"Amazon, Seattle, WA, USA","institution_ids":["https://openalex.org/I1311688040"]},{"raw_affiliation_string":"Amazon","institution_ids":["https://openalex.org/I4210089985"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058474860","display_name":"Tom Diethe","orcid":"https://orcid.org/0000-0002-0776-5407"},"institutions":[{"id":"https://openalex.org/I4210123934","display_name":"Amazon (United Kingdom)","ror":"https://ror.org/02xey9634","country_code":"GB","type":"company","lineage":["https://openalex.org/I1311688040","https://openalex.org/I4210123934"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Tom Diethe","raw_affiliation_strings":["Amazon, Cambridge, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Amazon, Cambridge, United Kingdom","institution_ids":["https://openalex.org/I4210123934"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5021612761"],"corresponding_institution_ids":["https://openalex.org/I1311688040","https://openalex.org/I4210089985"],"apc_list":null,"apc_paid":null,"fwci":0.5485,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.7218802,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"178","last_page":"186"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":1.0,"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":1.0,"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/T11045","display_name":"Privacy, Security, and Data Protection","score":0.983299970626831,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9764999747276306,"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":0.7746412754058838},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6219780445098877},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5074180960655212},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.48526236414909363},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.48037606477737427},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4595029056072235},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.44450992345809937},{"id":"https://openalex.org/keywords/anonymity","display_name":"Anonymity","score":0.4441249370574951},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4198983609676361},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41493451595306396},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.38648414611816406},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.259294331073761},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.21470865607261658},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16142475605010986}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7746412754058838},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6219780445098877},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5074180960655212},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.48526236414909363},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.48037606477737427},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4595029056072235},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.44450992345809937},{"id":"https://openalex.org/C178005623","wikidata":"https://www.wikidata.org/wiki/Q308859","display_name":"Anonymity","level":2,"score":0.4441249370574951},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4198983609676361},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41493451595306396},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.38648414611816406},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.259294331073761},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.21470865607261658},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16142475605010986},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1145/3336191.3371856","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3336191.3371856","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1910.08902","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1910.08902","pdf_url":"https://arxiv.org/pdf/1910.08902","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},{"id":"doi:10.48550/arxiv.1910.08902","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1910.08902","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"},{"id":"mag:2980848703","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1910.08902","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1910.08902","pdf_url":"https://arxiv.org/pdf/1910.08902","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.6399999856948853,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2980848703.pdf","grobid_xml":"https://content.openalex.org/works/W2980848703.grobid-xml"},"referenced_works_count":52,"referenced_works":["https://openalex.org/W145956381","https://openalex.org/W1566256432","https://openalex.org/W1603920809","https://openalex.org/W1658920975","https://openalex.org/W1690606251","https://openalex.org/W1800745661","https://openalex.org/W1873763122","https://openalex.org/W1981029888","https://openalex.org/W1992263322","https://openalex.org/W2002494050","https://openalex.org/W2026002400","https://openalex.org/W2030559796","https://openalex.org/W2053637704","https://openalex.org/W2056700697","https://openalex.org/W2077217970","https://openalex.org/W2082894754","https://openalex.org/W2091815328","https://openalex.org/W2110868467","https://openalex.org/W2113459411","https://openalex.org/W2116950384","https://openalex.org/W2131571251","https://openalex.org/W2135930857","https://openalex.org/W2153579005","https://openalex.org/W2157006255","https://openalex.org/W2159171098","https://openalex.org/W2159675343","https://openalex.org/W2170540710","https://openalex.org/W2173361515","https://openalex.org/W2245160765","https://openalex.org/W2250539671","https://openalex.org/W2252211741","https://openalex.org/W2473418344","https://openalex.org/W2476457629","https://openalex.org/W2493916176","https://openalex.org/W2535690855","https://openalex.org/W2584956383","https://openalex.org/W2623059953","https://openalex.org/W2742225091","https://openalex.org/W2794651469","https://openalex.org/W2887818006","https://openalex.org/W2898996243","https://openalex.org/W2952604841","https://openalex.org/W2963515066","https://openalex.org/W2963541051","https://openalex.org/W2963999993","https://openalex.org/W2964154091","https://openalex.org/W3102407811","https://openalex.org/W3102994281","https://openalex.org/W3122641901","https://openalex.org/W3123972088","https://openalex.org/W4288345394","https://openalex.org/W6646066113"],"related_works":["https://openalex.org/W2998378988","https://openalex.org/W3003815046","https://openalex.org/W2974116050","https://openalex.org/W2953314980","https://openalex.org/W2994849590","https://openalex.org/W1665258286","https://openalex.org/W2967916697","https://openalex.org/W2917666053","https://openalex.org/W2951051665","https://openalex.org/W3089242161","https://openalex.org/W3080836987","https://openalex.org/W2990553645","https://openalex.org/W2611718442","https://openalex.org/W2975302291","https://openalex.org/W3099351401","https://openalex.org/W2088517895","https://openalex.org/W3107761660","https://openalex.org/W2000263922","https://openalex.org/W2763957864","https://openalex.org/W2998245534"],"abstract_inverted_index":{"Accurately":[0],"learning":[1],"from":[2],"user":[3,20],"data":[4],"while":[5,18,164],"providing":[6,165],"quantifiable":[7],"privacy":[8,31,72,79,121,139,167],"guarantees":[9,83,168],"provides":[10,82],"an":[11],"opportunity":[12],"to":[13,28,41,53,86,134],"build":[14],"better":[15,166],"ML":[16],"models":[17,127],"maintaining":[19],"trust.":[21],"This":[22],"paper":[23],"presents":[24],"a":[25,59,71,87],"formal":[26],"approach":[27,48],"carrying":[29],"out":[30],"preserving":[32],"text":[33],"perturbation":[34],"using":[35],"the":[36,78,92,136],"notion":[37],"of":[38,56,145],"d_\u03c7-privacy":[39,76],"designed":[40],"achieve":[42],"geo-indistinguishability":[43],"in":[44,58],"location":[45],"data.":[46],"Our":[47,151],"applies":[49],"carefully":[50],"calibrated":[51],"noise":[52],"vector":[54],"representation":[55],"words":[57],"high":[60],"dimension":[61],"space":[62],"as":[63],"defined":[64,90],"by":[65,91,103,110],"word":[66,93],"embedding":[67,94],"models.":[68,171],"We":[69,96,119],"present":[70],"proof":[73],"that":[74],"satisfies":[75],"where":[77],"parameter":[80],"$\\varepsilon$":[81,99],"with":[84],"respect":[85],"distance":[88],"metric":[89],"space.":[95],"demonstrate":[97,135,153],"how":[98],"can":[100],"be":[101],"selected":[102],"analyzing":[104],"plausible":[105],"deniability":[106],"statistics":[107],"backed":[108],"up":[109],"large":[111],"scale":[112],"analysis":[113],"on":[114,131,147],"GloVe":[115],"and":[116,128,140],"fastText":[117],"embeddings.":[118],"conduct":[120],"audit":[122],"experiments":[123,130],"against":[124],"$2$":[125],"baseline":[126,170],"utility":[129,141,155,158],"3":[132],"datasets":[133],"tradeoff":[137],"between":[138],"for":[142,160],"varying":[143],"values":[144],"varepsilon":[146],"different":[148],"task":[149],"types.":[150],"results":[152],"practical":[154],"(<":[156],"2%":[157],"loss":[159],"training":[161],"binary":[162],"classifiers)":[163],"than":[169]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
