{"id":"https://openalex.org/W2893034441","doi":"https://doi.org/10.1145/3234338","title":"Stream Sampling Framework and Application for Frequency Cap Statistics","display_name":"Stream Sampling Framework and Application for Frequency Cap Statistics","publication_year":2018,"publication_date":"2018-09-24","ids":{"openalex":"https://openalex.org/W2893034441","doi":"https://doi.org/10.1145/3234338","mag":"2893034441"},"language":"en","primary_location":{"id":"doi:10.1145/3234338","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3234338","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3234338?download=true","source":{"id":"https://openalex.org/S137348503","display_name":"ACM Transactions on Algorithms","issn_l":"1549-6325","issn":["1549-6325","1549-6333"],"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 Algorithms","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/10.1145/3234338?download=true","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026385549","display_name":"Edith Cohen","orcid":"https://orcid.org/0000-0002-3926-8237"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]},{"id":"https://openalex.org/I16391192","display_name":"Tel Aviv University","ror":"https://ror.org/04mhzgx49","country_code":"IL","type":"education","lineage":["https://openalex.org/I16391192"]}],"countries":["IL","US"],"is_corresponding":true,"raw_author_name":"Edith Cohen","raw_affiliation_strings":["Google AI, CA, USA and Tel Aviv University, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google AI, CA, USA and Tel Aviv University, Israel","institution_ids":["https://openalex.org/I1291425158","https://openalex.org/I16391192"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5026385549"],"corresponding_institution_ids":["https://openalex.org/I1291425158","https://openalex.org/I16391192"],"apc_list":null,"apc_paid":null,"fwci":0.7582,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.7537898,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"14","issue":"4","first_page":"1","last_page":"40"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9984999895095825,"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/T11106","display_name":"Data Management and Algorithms","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/statistics","display_name":"Statistics","score":0.505031406879425},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.49318140745162964},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.48041534423828125},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.470855176448822},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.46818625926971436},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.42962121963500977},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.42656955122947693},{"id":"https://openalex.org/keywords/sample-size-determination","display_name":"Sample size determination","score":0.4215499758720398},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3784889280796051},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32057762145996094}],"concepts":[{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.505031406879425},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.49318140745162964},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.48041534423828125},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.470855176448822},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.46818625926971436},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.42962121963500977},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.42656955122947693},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.4215499758720398},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3784889280796051},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32057762145996094},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3234338","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3234338","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3234338?download=true","source":{"id":"https://openalex.org/S137348503","display_name":"ACM Transactions on Algorithms","issn_l":"1549-6325","issn":["1549-6325","1549-6333"],"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 Algorithms","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3234338","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3234338","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3234338?download=true","source":{"id":"https://openalex.org/S137348503","display_name":"ACM Transactions on Algorithms","issn_l":"1549-6325","issn":["1549-6325","1549-6333"],"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 Algorithms","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2893034441.pdf","grobid_xml":"https://content.openalex.org/works/W2893034441.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W1965996575","https://openalex.org/W1977141583","https://openalex.org/W1980242380","https://openalex.org/W1981663184","https://openalex.org/W1982092405","https://openalex.org/W1993482412","https://openalex.org/W2006355640","https://openalex.org/W2013809345","https://openalex.org/W2025051251","https://openalex.org/W2031657002","https://openalex.org/W2034417563","https://openalex.org/W2040088116","https://openalex.org/W2045555847","https://openalex.org/W2060385919","https://openalex.org/W2080234606","https://openalex.org/W2080745194","https://openalex.org/W2085845250","https://openalex.org/W2087982439","https://openalex.org/W2090914728","https://openalex.org/W2092236286","https://openalex.org/W2111806841","https://openalex.org/W2119050385","https://openalex.org/W2136987366","https://openalex.org/W2142035328","https://openalex.org/W2144146806","https://openalex.org/W2156760512","https://openalex.org/W2592374036","https://openalex.org/W2751862591","https://openalex.org/W2962904868","https://openalex.org/W2979473749","https://openalex.org/W4206244036","https://openalex.org/W4232440580","https://openalex.org/W4233471163","https://openalex.org/W4300526689"],"related_works":["https://openalex.org/W4388813866","https://openalex.org/W4293088233","https://openalex.org/W2850804095","https://openalex.org/W1481656249","https://openalex.org/W2162280767","https://openalex.org/W2999104021","https://openalex.org/W2774950576","https://openalex.org/W1570799877","https://openalex.org/W2800688113","https://openalex.org/W2057598446"],"abstract_inverted_index":{"Unaggregated":[0],"data,":[1],"in":[2,52,81],"a":[3,48,53,57,105,130,139,200,208,293],"streamed":[4],"or":[5,213],"distributed":[6,217],"form,":[7],"are":[8,93,257],"prevalent":[9],"and":[10,23,33,91,117,219,235,251],"come":[11],"from":[12],"diverse":[13],"sources":[14],"such":[15,41,158],"as":[16,47],"interactions":[17],"of":[18,56,67,69,78,88,96,120,172,182,190,245,287],"users":[19],"with":[20,35,141,144,265],"web":[21],"services":[22],"IP":[24],"traffic.":[25],"Data":[26],"elements":[27,34],"have":[28],"keys":[29,37,51,80],"(cookies,":[30],"users,":[31],"queries),":[32],"different":[36],"interleave.":[38],"Analytics":[39],"on":[40,254,277,296],"data":[42,168,205],"typically":[43],"utilizes":[44],"statistics":[45,121,128,250,264,283],"expressed":[46],"sum":[49,87],"over":[50],"specified":[54],"segment":[55],"function":[58,132],"f":[59,133,149],"applied":[60],"to":[61,126,148,187,223,259],"the":[62,70,76,82,86,102,167,170,188,224],"frequency":[63,97,103,142,249],"(the":[64,284],"total":[65],"number":[66,77,189],"occurrences)":[68],"key.":[71],"In":[72],"particular,":[73],"Distinct":[74,234],"is":[75,85,155,177,185],"active":[79,191],"segment,":[83],"Sum":[84],"their":[89],"frequencies,":[90],"both":[92],"special":[94],"cases":[95],"cap":[98,101,263,288],"statistics,":[99],"which":[100,193],"by":[104],"parameter":[106],"T":[107,266],".":[108],"Random":[109],"samples":[110,160,240,272],"can":[111,161,194],"be":[112,162,195],"very":[113,196],"effective":[114],"for":[115,129,203,233,262,279],"quick":[116],"efficient":[118],"estimation":[119],"at":[122],"query":[123],"time.":[124],"Ideally,":[125],"estimate":[127],"given":[131],",":[134],"our":[135,238,270],"sample":[136,226,297],"would":[137],"include":[138],"key":[140],"w":[143,151],"probability":[145],"roughly":[146],"proportional":[147,186,222],"(":[150],").":[152],"The":[153],"challenge":[154],"that":[156,184,206,256],"while":[157,290],"\u201cgold-standard\u201d":[159],"easily":[163],"computed":[164],"after":[165],"aggregating":[166],"(computing":[169],"set":[171],"key-frequency":[173],"pairs),":[174],"this":[175],"aggregation":[176],"costly:":[178],"It":[179],"requires":[180],"structure":[181,220],"size":[183,221],"keys,":[192],"large.":[197],"We":[198],"present":[199],"sampling":[201],"framework":[202],"unaggregated":[204],"uses":[207],"single":[209],"pass":[210],"(for":[211,216],"streams)":[212],"two":[214],"passes":[215],"data)":[218],"desired":[225],"size.":[227,298],"Our":[228],"design":[229],"unifies":[230],"classic":[231],"solutions":[232],"Sum.":[236],"Specifically,":[237],"\u2113-capped":[239],"provide":[241,273],"nonnegative":[242,285],"unbiased":[243],"estimates":[244],"any":[246],"monotone":[247],"non-decreasing":[248],"statistical":[252,275],"guarantees":[253,276],"quality":[255,278],"close":[258],"gold":[260],"standard":[261],"=\u0398":[267],"(\u2113).":[268],"Furthermore,":[269],"multi-objective":[271],"these":[274],"all":[280],"concave":[281],"sub-linear":[282],"span":[286],"functions)":[289],"incurring":[291],"only":[292],"logarithmic":[294],"overhead":[295]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
