{"id":"https://openalex.org/W1606520508","doi":"https://doi.org/10.1109/icde.2015.7113354","title":"Differentially private frequent sequence mining via sampling-based candidate pruning","display_name":"Differentially private frequent sequence mining via sampling-based candidate pruning","publication_year":2015,"publication_date":"2015-04-01","ids":{"openalex":"https://openalex.org/W1606520508","doi":"https://doi.org/10.1109/icde.2015.7113354","mag":"1606520508","pmid":"https://pubmed.ncbi.nlm.nih.gov/26973430"},"language":"en","primary_location":{"id":"doi:10.1109/icde.2015.7113354","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde.2015.7113354","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 31st International Conference on Data Engineering","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4788512","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068927077","display_name":"Shengzhi Xu","orcid":"https://orcid.org/0000-0001-6984-1471"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shengzhi Xu","raw_affiliation_strings":["State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications, Beijing, China","[State Key Laboratory of Networking & Switching Technology, Beijing University of Posts and Telecommunications, China]"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"[State Key Laboratory of Networking & Switching Technology, Beijing University of Posts and Telecommunications, China]","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036865453","display_name":"Sen Su","orcid":"https://orcid.org/0000-0003-4266-7527"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sen Su","raw_affiliation_strings":["State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications, Beijing, China","[State Key Laboratory of Networking & Switching Technology, Beijing University of Posts and Telecommunications, China]"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"[State Key Laboratory of Networking & Switching Technology, Beijing University of Posts and Telecommunications, China]","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062327704","display_name":"Xiang Cheng","orcid":"https://orcid.org/0000-0001-6556-2264"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang Cheng","raw_affiliation_strings":["State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications, Beijing, China","[State Key Laboratory of Networking & Switching Technology, Beijing University of Posts and Telecommunications, China]"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"[State Key Laboratory of Networking & Switching Technology, Beijing University of Posts and Telecommunications, China]","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100606800","display_name":"Zhengyi Li","orcid":"https://orcid.org/0000-0003-3899-0057"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengyi Li","raw_affiliation_strings":["State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications, Beijing, China","[State Key Laboratory of Networking & Switching Technology, Beijing University of Posts and Telecommunications, China]"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"[State Key Laboratory of Networking & Switching Technology, Beijing University of Posts and Telecommunications, China]","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078394535","display_name":"Li Xiong","orcid":"https://orcid.org/0000-0001-7354-0428"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Li Xiong","raw_affiliation_strings":["Math and Computer Science Department, Emory University, Atlanta, GA","Math and Computer Science Department, Emory University, Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"Math and Computer Science Department, Emory University, Atlanta, GA","institution_ids":["https://openalex.org/I150468666"]},{"raw_affiliation_string":"Math and Computer Science Department, Emory University, Atlanta, GA, USA","institution_ids":["https://openalex.org/I150468666"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5068927077"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":6.6764,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.96635944,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"2015","issue":null,"first_page":"1035","last_page":"1046"},"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9908999800682068,"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":0.9860000014305115,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.7627205848693848},{"id":"https://openalex.org/keywords/differential-privacy","display_name":"Differential privacy","score":0.6320295929908752},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.619464099407196},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6019825339317322},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5803278684616089},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.56980961561203},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5343697667121887},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.5126380324363708},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4946896731853485},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.43032315373420715},{"id":"https://openalex.org/keywords/reachability","display_name":"Reachability","score":0.41130322217941284},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34546059370040894},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24467411637306213},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.08255866169929504}],"concepts":[{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.7627205848693848},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.6320295929908752},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.619464099407196},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6019825339317322},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5803278684616089},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.56980961561203},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5343697667121887},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5126380324363708},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4946896731853485},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.43032315373420715},{"id":"https://openalex.org/C136643341","wikidata":"https://www.wikidata.org/wiki/Q1361526","display_name":"Reachability","level":2,"score":0.41130322217941284},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34546059370040894},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24467411637306213},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.08255866169929504},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/icde.2015.7113354","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde.2015.7113354","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 31st International Conference on Data Engineering","raw_type":"proceedings-article"},{"id":"pmid:26973430","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/26973430","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. International Conference on Data Engineering","raw_type":null},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.704.5720","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.704.5720","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.mathcs.emory.edu/aims/pub/xu15icde.pdf","raw_type":"text"},{"id":"pmh:oai:pubmedcentral.nih.gov:4788512","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4788512","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc Int Conf Data Eng","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:4788512","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4788512","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc Int Conf Data Eng","raw_type":"Text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W889496518","https://openalex.org/W1484413656","https://openalex.org/W1597561788","https://openalex.org/W1641039719","https://openalex.org/W1873763122","https://openalex.org/W1966862198","https://openalex.org/W1973056687","https://openalex.org/W1993116423","https://openalex.org/W1999119356","https://openalex.org/W2002842265","https://openalex.org/W2015569667","https://openalex.org/W2019384076","https://openalex.org/W2068695222","https://openalex.org/W2090593019","https://openalex.org/W2091644709","https://openalex.org/W2100761657","https://openalex.org/W2104731482","https://openalex.org/W2108215372","https://openalex.org/W2123820077","https://openalex.org/W2134479759","https://openalex.org/W2159024459","https://openalex.org/W2162379889","https://openalex.org/W2164778205","https://openalex.org/W2165157425","https://openalex.org/W2256774029","https://openalex.org/W2293703278","https://openalex.org/W2911978475","https://openalex.org/W6628750762","https://openalex.org/W6635637936","https://openalex.org/W6636681434","https://openalex.org/W6639246211","https://openalex.org/W6667713450","https://openalex.org/W6697062959","https://openalex.org/W6758947373"],"related_works":["https://openalex.org/W2136512912","https://openalex.org/W2127267268","https://openalex.org/W2156446763","https://openalex.org/W2067910792","https://openalex.org/W2150194458","https://openalex.org/W2143461633","https://openalex.org/W2889071233","https://openalex.org/W4321471459","https://openalex.org/W4221156924","https://openalex.org/W2380814829"],"abstract_inverted_index":{"In":[0,130],"this":[1,84],"paper,":[2],"we":[3,64,93,132,205],"study":[4],"the":[5,12,19,50,58,68,74,120,126,134,142,154,168,172,178,194,198],"problem":[6],"of":[7,21,42,52,60,70,109,138,156,180],"mining":[8,28],"frequent":[9,26,182,227],"sequences":[10,122,140,148,183,228],"under":[11],"rigorous":[13],"differential":[14],"privacy":[15,77,203],"model.":[16],"We":[17,44],"explore":[18],"possibility":[20],"designing":[22],"a":[23,39,88,95,160,186],"differentially":[24,47,97],"private":[25,48,98,158],"sequence":[27,161],"(FSM)":[29],"algorithm":[30,111,210,223],"which":[31,101,147],"can":[32,79,224],"achieve":[33],"both":[34],"high":[35,40,230],"data":[36],"utility":[37,75],"and":[38,76],"degree":[41],"privacy.":[43],"found,":[45],"in":[46,141],"FSM,":[49],"amount":[51],"required":[53],"noise":[54],"is":[55,102,112,164,190,211],"proportionate":[56],"to":[57,104,113,117,145,166,176,192],"number":[59,69],"candidate":[61,72,90,121,139],"sequences.":[62],"If":[63],"could":[65],"effectively":[66],"reduce":[67],"unpromising":[71],"sequences,":[73],"tradeoff":[78],"be":[80],"significantly":[81],"improved.":[82],"To":[83,152],"end,":[85],"by":[86],"leveraging":[87],"sampling-based":[89],"pruning":[91],"technique,":[92],"propose":[94],"novel":[96],"FSM":[99],"algorithm,":[100],"referred":[103],"as":[105,184],"<i>PFS</i><sup>2</sup>.":[106],"The":[107],"core":[108],"our":[110,208,221],"utilize":[114],"sample":[115,143,173,199],"databases":[116,144],"further":[118],"prune":[119],"generated":[123],"based":[124],"on":[125,171,216],"downward":[127],"closure":[128],"property.":[129],"particular,":[131],"use":[133],"noisy":[135],"local":[136],"support":[137],"estimate":[146],"are":[149],"potentially":[150],"frequent.":[151],"improve":[153],"accuracy":[155],"such":[157],"estimations,":[159],"shrinking":[162],"method":[163,189],"proposed":[165,191],"enforce":[167],"length":[169],"constraint":[170],"databases.":[174,200],"Moreover,":[175],"decrease":[177],"probability":[179],"misestimating":[181],"infrequent,":[185],"threshold":[187,196],"relaxation":[188],"relax":[193],"user-specified":[195],"for":[197],"Through":[201],"formal":[202],"analysis,":[204],"show":[206],"that":[207,220],"<i>PFS</i><sup>2</sup>":[209,222],"<i>\u03b5</i>-differentially":[212],"private.":[213],"Extensive":[214],"experiments":[215],"real":[217],"datasets":[218],"illustrate":[219],"privately":[225],"find":[226],"with":[229],"accuracy.":[231]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}