{"id":"https://openalex.org/W2145281652","doi":"https://doi.org/10.1109/tkde.2003.1198391","title":"Efficient approximation of correlated sums on data streams","display_name":"Efficient approximation of correlated sums on data streams","publication_year":2003,"publication_date":"2003-05-01","ids":{"openalex":"https://openalex.org/W2145281652","doi":"https://doi.org/10.1109/tkde.2003.1198391","mag":"2145281652"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2003.1198391","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2003.1198391","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","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/A5064908055","display_name":"R. Ananthakrishna","orcid":null},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"R. Ananthakrishna","raw_affiliation_strings":["Department of Computer Science, Cornell University, Ithaca, NY, USA","[Dept. of Comput. Sci., Cornell Univ., Ithaca, NY, USA]"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Cornell University, Ithaca, NY, USA","institution_ids":["https://openalex.org/I205783295"]},{"raw_affiliation_string":"[Dept. of Comput. Sci., Cornell Univ., Ithaca, NY, USA]","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102972112","display_name":"Abhishek Das","orcid":"https://orcid.org/0000-0002-4718-4316"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"A. Das","raw_affiliation_strings":["Department of Computer Science, Cornell University, Ithaca, NY, USA","[Dept. of Comput. Sci., Cornell Univ., Ithaca, NY, USA]"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Cornell University, Ithaca, NY, USA","institution_ids":["https://openalex.org/I205783295"]},{"raw_affiliation_string":"[Dept. of Comput. Sci., Cornell Univ., Ithaca, NY, USA]","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023537206","display_name":"Johannes Gehrke","orcid":"https://orcid.org/0009-0006-6293-5209"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J. Gehrke","raw_affiliation_strings":["Department of Computer Science, Cornell University, Ithaca, NY, USA","[Dept. of Comput. Sci., Cornell Univ., Ithaca, NY, USA]"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Cornell University, Ithaca, NY, USA","institution_ids":["https://openalex.org/I205783295"]},{"raw_affiliation_string":"[Dept. of Comput. Sci., Cornell Univ., Ithaca, NY, USA]","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110197814","display_name":"Flip Korn","orcid":null},"institutions":[{"id":"https://openalex.org/I1283103587","display_name":"AT&T (United States)","ror":"https://ror.org/02bbd5539","country_code":"US","type":"company","lineage":["https://openalex.org/I1283103587"]},{"id":"https://openalex.org/I36253440","display_name":"IEEE Computer Society","ror":"https://ror.org/05nxk6n24","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I36253440"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"F. Korn","raw_affiliation_strings":["AT and T Research Laboratories, Florham Park, NJ, USA","IEEE Computer Society#TAB#"],"affiliations":[{"raw_affiliation_string":"AT and T Research Laboratories, Florham Park, NJ, USA","institution_ids":["https://openalex.org/I1283103587"]},{"raw_affiliation_string":"IEEE Computer Society#TAB#","institution_ids":["https://openalex.org/I36253440"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075159410","display_name":"S. Muthukrishnan","orcid":"https://orcid.org/0009-0007-8936-5709"},"institutions":[{"id":"https://openalex.org/I1283103587","display_name":"AT&T (United States)","ror":"https://ror.org/02bbd5539","country_code":"US","type":"company","lineage":["https://openalex.org/I1283103587"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"S. Muthukrishnan","raw_affiliation_strings":["AT and T Research Laboratories, Florham Park, NJ, USA","School of Arts and Sciences, Computer Science"],"affiliations":[{"raw_affiliation_string":"AT and T Research Laboratories, Florham Park, NJ, USA","institution_ids":["https://openalex.org/I1283103587"]},{"raw_affiliation_string":"School of Arts and Sciences, Computer Science","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088315797","display_name":"Divesh Srivastava","orcid":"https://orcid.org/0000-0002-7609-9217"},"institutions":[{"id":"https://openalex.org/I1283103587","display_name":"AT&T (United States)","ror":"https://ror.org/02bbd5539","country_code":"US","type":"company","lineage":["https://openalex.org/I1283103587"]},{"id":"https://openalex.org/I36253440","display_name":"IEEE Computer Society","ror":"https://ror.org/05nxk6n24","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I36253440"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"D. Srivastava","raw_affiliation_strings":["AT and T Research Laboratories, Florham Park, NJ, USA","IEEE Computer Society#TAB#"],"affiliations":[{"raw_affiliation_string":"AT and T Research Laboratories, Florham Park, NJ, USA","institution_ids":["https://openalex.org/I1283103587"]},{"raw_affiliation_string":"IEEE Computer Society#TAB#","institution_ids":["https://openalex.org/I36253440"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5064908055"],"corresponding_institution_ids":["https://openalex.org/I205783295"],"apc_list":null,"apc_paid":null,"fwci":1.8719,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.88257283,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"15","issue":"3","first_page":"569","last_page":"572"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9968000054359436,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9968000054359436,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9939000010490417,"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/T11321","display_name":"Error Correcting Code Techniques","score":0.9905999898910522,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/quantile","display_name":"Quantile","score":0.8539878129959106},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.741474449634552},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.725948691368103},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.7122460603713989},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6344371438026428},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5904351472854614},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.5462749004364014},{"id":"https://openalex.org/keywords/data-structure","display_name":"Data structure","score":0.5231049060821533},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4699552059173584},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.45523667335510254},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.34796759486198425},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3229452073574066},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3093583583831787},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.28445953130722046},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16019904613494873}],"concepts":[{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.8539878129959106},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.741474449634552},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.725948691368103},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.7122460603713989},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6344371438026428},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5904351472854614},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.5462749004364014},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.5231049060821533},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4699552059173584},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.45523667335510254},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.34796759486198425},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3229452073574066},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3093583583831787},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28445953130722046},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16019904613494873},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tkde.2003.1198391","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2003.1198391","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.13.6581","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.13.6581","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.cornell.edu/johannes/papers/2003/tkde2003-corragg.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W176053229","https://openalex.org/W1483324348","https://openalex.org/W2001474264","https://openalex.org/W2039100193","https://openalex.org/W2080745194","https://openalex.org/W2081189989","https://openalex.org/W2112452856","https://openalex.org/W2148706674","https://openalex.org/W2156943642","https://openalex.org/W3004286518","https://openalex.org/W3196751543","https://openalex.org/W4210949648","https://openalex.org/W4237421257","https://openalex.org/W4256417298","https://openalex.org/W6607119070","https://openalex.org/W6628796795"],"related_works":["https://openalex.org/W4389449520","https://openalex.org/W127192698","https://openalex.org/W2570600173","https://openalex.org/W2893008024","https://openalex.org/W2743735673","https://openalex.org/W4361801939","https://openalex.org/W2360131081","https://openalex.org/W2985941356","https://openalex.org/W2802243998","https://openalex.org/W1521014365"],"abstract_inverted_index":{"In":[0],"many":[1],"applications":[2],"such":[3],"as":[4],"IP":[5],"network":[6],"management,":[7],"data":[8,77,126,179],"arrives":[9],"in":[10,72,102,181],"streams":[11,16],"and":[12,43,61,114,143],"queries":[13,33],"over":[14,177],"those":[15],"need":[17],"to":[18],"be":[19,57,69,100,175,190],"processed":[20],"online":[21],"using":[22,79,109],"limited":[23,80,103,182],"storage.":[24],"Correlated-sum":[25],"(CS)":[26],"aggregates":[27,38],"are":[28,44,64],"a":[29,76,93,148,160,171,178,187],"natural":[30],"class":[31],"of":[32,45,87,112,122,134,152,186],"formed":[34],"by":[35],"composing":[36],"basic":[37,59],"on":[39],"(x,":[40],"y)":[41],"pairs":[42],"the":[46,85,119,135,153,158,184],"form":[47],"SUM{g(y)":[48],":":[49],"x":[50],"/spl":[51],"les/":[52],"f(AGG(x))},":[53],"where":[54],"AGG(x)":[55,98,169],"can":[56,99,189],"any":[58],"aggregate":[60],"f(),":[62],"g()":[63],"user-specified":[65],"functions.":[66],"CS-aggregates":[67],"cannot":[68,174],"computed":[70,101,176],"exactly":[71],"one":[73],"pass":[74],"through":[75],"stream":[78,180],"storage;":[81],"hence,":[82],"we":[83,128,165],"study":[84],"problem":[86],"computing":[88],"approximate":[89,120],"CS-aggregates.":[90],"We":[91],"guarantee":[92],"priori":[94],"error":[95,162,185],"bounds":[96],"when":[97,168],"space":[104],"(e.g.,":[105],"MIN,":[106],"MAX,":[107],"AVG),":[108],"two":[110],"variants":[111],"Greenwald":[113],"Khanna's":[115],"summary":[116,137,155],"structure":[117,138],"for":[118,157],"computation":[121],"quantiles.":[123],"Using":[124],"real":[125],"sets,":[127],"experimentally":[129],"demonstrate":[130],"that":[131],"an":[132],"adaptation":[133],"quantile":[136,154,172],"uses":[139],"much":[140],"less":[141],"space,":[142],"is":[144,170],"significantly":[145],"faster,":[146],"than":[147],"more":[149],"direct":[150],"use":[151],"structure,":[156],"same":[159],"posteriori":[161],"bounds.":[163],"Finally,":[164],"prove":[166],"that,":[167],"(which":[173],"space),":[183],"CS-aggregate":[188],"arbitrarily":[191],"large.":[192]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
