{"id":"https://openalex.org/W4386125404","doi":"https://doi.org/10.14778/3611479.3611508","title":"Saibot: A Differentially Private Data Search Platform","display_name":"Saibot: A Differentially Private Data Search Platform","publication_year":2023,"publication_date":"2023-07-01","ids":{"openalex":"https://openalex.org/W4386125404","doi":"https://doi.org/10.14778/3611479.3611508"},"language":"en","primary_location":{"id":"doi:10.14778/3611479.3611508","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3611479.3611508","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"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":"Proceedings of the VLDB Endowment","raw_type":"journal-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/A5002877429","display_name":"Zezhou Huang","orcid":"https://orcid.org/0009-0002-6613-0337"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zezhou Huang","raw_affiliation_strings":["Columbia University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100721394","display_name":"Jiaxiang Liu","orcid":"https://orcid.org/0009-0000-6498-1678"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiaxiang Liu","raw_affiliation_strings":["Columbia University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043962944","display_name":"Daniel Alabi","orcid":"https://orcid.org/0000-0002-1613-6565"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Gbenga Alabi","raw_affiliation_strings":["Columbia University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003690515","display_name":"Raul Castro Fernandez","orcid":"https://orcid.org/0000-0001-7675-6080"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Raul Castro Fernandez","raw_affiliation_strings":["University of Chicago"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chicago","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049016095","display_name":"Eugene Wu","orcid":"https://orcid.org/0000-0003-4254-6688"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eugene Wu","raw_affiliation_strings":["DSI, Columbia University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DSI, Columbia University","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4759,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.68874882,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"16","issue":"11","first_page":"3057","last_page":"3070"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.989799976348877,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T10237","display_name":"Cryptography and Data Security","score":0.9846000075340271,"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":0.7957097291946411},{"id":"https://openalex.org/keywords/joins","display_name":"Joins","score":0.7086721062660217},{"id":"https://openalex.org/keywords/differential-privacy","display_name":"Differential privacy","score":0.6311923265457153},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.5901161432266235},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5319880247116089},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5279378294944763},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5059630274772644},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4956458806991577},{"id":"https://openalex.org/keywords/movielens","display_name":"MovieLens","score":0.4203999936580658},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3898300528526306},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23402878642082214},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.1159084141254425},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10251608490943909},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.09460106492042542},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09202876687049866},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.08722522854804993}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7957097291946411},{"id":"https://openalex.org/C2778692605","wikidata":"https://www.wikidata.org/wiki/Q4041866","display_name":"Joins","level":2,"score":0.7086721062660217},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.6311923265457153},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.5901161432266235},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5319880247116089},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5279378294944763},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5059630274772644},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4956458806991577},{"id":"https://openalex.org/C2776156558","wikidata":"https://www.wikidata.org/wiki/Q4353746","display_name":"MovieLens","level":4,"score":0.4203999936580658},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3898300528526306},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23402878642082214},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.1159084141254425},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10251608490943909},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.09460106492042542},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09202876687049866},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.08722522854804993},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.14778/3611479.3611508","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3611479.3611508","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"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":"Proceedings of the VLDB Endowment","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals","score":0.49000000953674316}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W72904796","https://openalex.org/W200517375","https://openalex.org/W1557833142","https://openalex.org/W1873763122","https://openalex.org/W1981029888","https://openalex.org/W1997690112","https://openalex.org/W2022542865","https://openalex.org/W2027461913","https://openalex.org/W2042469398","https://openalex.org/W2050100848","https://openalex.org/W2096803423","https://openalex.org/W2167372639","https://openalex.org/W2284514301","https://openalex.org/W2293299776","https://openalex.org/W2520881573","https://openalex.org/W2739902099","https://openalex.org/W2795089200","https://openalex.org/W2948085204","https://openalex.org/W2950321888","https://openalex.org/W2962991166","https://openalex.org/W2963560792","https://openalex.org/W2970408474","https://openalex.org/W3016632787","https://openalex.org/W3027749727","https://openalex.org/W3106378891","https://openalex.org/W3111578933","https://openalex.org/W3113714175","https://openalex.org/W3118813946","https://openalex.org/W3168854329","https://openalex.org/W3175808861","https://openalex.org/W3196904276","https://openalex.org/W4232172926","https://openalex.org/W4248861293","https://openalex.org/W4281811562","https://openalex.org/W4285522518","https://openalex.org/W4289533971","https://openalex.org/W4320167562"],"related_works":["https://openalex.org/W2398491113","https://openalex.org/W2794657157","https://openalex.org/W2219888463","https://openalex.org/W3045147512","https://openalex.org/W2088925915","https://openalex.org/W2022984797","https://openalex.org/W2382891957","https://openalex.org/W2075329139","https://openalex.org/W4384919653","https://openalex.org/W2032764764"],"abstract_inverted_index":{"Recent":[0],"data":[1,54,64,68,100],"search":[2,14,26,69,77,101,158],"platforms":[3,25,63],"use":[4],"ML":[5,119],"task-based":[6],"utility":[7],"measures":[8],"rather":[9],"than":[10],"metadata-based":[11],"keywords,":[12],"to":[13,35,113,141,143,176,195,199],"large":[15],"dataset":[16,211],"corpora.":[17],"Requesters":[18],"submit":[19],"a":[20,75,97,109,209],"training":[21,80],"dataset,":[22,39],"and":[23,81,130,148,170,191],"these":[24,62],"for":[27,118,135,166,185],"augmentations":[28,221],"---join":[29],"or":[30,85],"union-compatible":[31],"datasets---that,":[32],"when":[33],"used":[34],"augment":[36],"the":[37,136,152,162,201,204,232],"requester's":[38],"most":[40],"improve":[41],"model":[42,224],"(e.g.,":[43],"linear":[44,177],"regression)":[45],"performance.":[46],"Although":[47],"effective,":[48],"providers":[49],"that":[50,103,154,217,222],"manage":[51],"personally":[52],"identifiable":[53],"demand":[55],"differential":[56],"privacy":[57,91],"(DP)":[58],"guarantees":[59],"before":[60],"granting":[61],"access.":[65],"Unfortunately,":[66],"making":[67],"differentially":[70,98],"private":[71,99],"is":[72],"nontrivial,":[73],"as":[74],"single":[76],"can":[78,131,219],"involve":[79],"evaluating":[82],"datasets":[83,147,215],"hundreds":[84],"thousands":[86],"of":[87,123,146,164,213,228,243],"times,":[88],"quickly":[89],"depleting":[90],"budgets.":[92],"We":[93,160],"present":[94],"Saibot":[95,140,218],",":[96],"platform":[102],"employs":[104],"Factorized":[105],"Privacy":[106],"Mechanism":[107],"(FPM),":[108],"novel":[110],"DP":[111,155,197,235],"mechanism,":[112],"calculate":[114],"sufficient":[115],"semi-ring":[116],"statistics":[117,126],"over":[120],"different":[121],"combinations":[122],"datasets.":[124],"These":[125],"are":[127,240],"privatized":[128],"once,":[129],"be":[132],"freely":[133],"reused":[134],"search.":[137],"This":[138],"allows":[139],"scale":[142],"arbitrary":[144],"numbers":[145],"requests,":[149],"while":[150,231],"minimizing":[151],"amount":[153],"noise":[156,198],"affects":[157],"results.":[159],"optimize":[161],"sensitivity":[163],"FPM":[165],"common":[167],"augmentation":[168],"operations,":[169],"analyze":[171],"its":[172,189],"properties":[173],"with":[174],"respect":[175],"regression.":[178],"Specifically,":[179],"we":[180],"develop":[181,192],"an":[182,193],"unbiased":[183],"estimator":[184],"many-to-many":[186],"joins,":[187],"prove":[188],"bounds,":[190],"optimization":[194],"redistribute":[196],"minimize":[200],"impact":[202],"on":[203,208],"model.":[205],"Our":[206],"evaluation":[207],"real-world":[210],"corpus":[212],"329":[214],"demonstrates":[216],"return":[220],"achieve":[223],"accuracy":[225],"within":[226],"50--90%":[227],"non-private":[229],"search,":[230],"leading":[233],"alternative":[234],"mechanisms":[236],"(TPM,":[237],"APM,":[238],"shuffling)":[239],"several":[241],"orders":[242],"magnitude":[244],"worse.":[245]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}