{"id":"https://openalex.org/W2613277090","doi":"https://doi.org/10.1145/3063955.3063995","title":"Composed sketch framework for quantiles and cardinality queries over big data streams","display_name":"Composed sketch framework for quantiles and cardinality queries over big data streams","publication_year":2017,"publication_date":"2017-05-08","ids":{"openalex":"https://openalex.org/W2613277090","doi":"https://doi.org/10.1145/3063955.3063995","mag":"2613277090"},"language":"en","primary_location":{"id":"doi:10.1145/3063955.3063995","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3063955.3063995","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Turing 50th Celebration Conference - China","raw_type":"proceedings-article"},"type":"conference-paper","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/A5069857235","display_name":"Shuzhuang Zhang","orcid":"https://orcid.org/0000-0002-2676-8064"},"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":"Shuzhuang Zhang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101999289","display_name":"Hao Luo","orcid":"https://orcid.org/0000-0001-7849-3341"},"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":"Hao Luo","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101405311","display_name":"Zhigang Wu","orcid":"https://orcid.org/0000-0001-6144-7277"},"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":"Zhigang Wu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100364982","display_name":"Yi Wang","orcid":"https://orcid.org/0000-0002-8448-8570"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Wang","raw_affiliation_strings":["Huawei Future Network Theory Lab, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Future Network Theory Lab, China","institution_ids":["https://openalex.org/I2250955327"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9988999962806702,"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"}},"topics":[{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9988999962806702,"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"}},{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9983999729156494,"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9943000078201294,"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/computer-science","display_name":"Computer science","score":0.8175252676010132},{"id":"https://openalex.org/keywords/cardinality","display_name":"Cardinality (data modeling)","score":0.7778021097183228},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.739055871963501},{"id":"https://openalex.org/keywords/sketch","display_name":"Sketch","score":0.7124066948890686},{"id":"https://openalex.org/keywords/quantile","display_name":"Quantile","score":0.6051524877548218},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.6017370820045471},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5481474995613098},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.5014469623565674},{"id":"https://openalex.org/keywords/bloom-filter","display_name":"Bloom filter","score":0.44872891902923584},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.4209238290786743},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.41836756467819214},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.39552196860313416},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.23670107126235962},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11012351512908936},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08623233437538147}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8175252676010132},{"id":"https://openalex.org/C87117476","wikidata":"https://www.wikidata.org/wiki/Q362383","display_name":"Cardinality (data modeling)","level":2,"score":0.7778021097183228},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.739055871963501},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.7124066948890686},{"id":"https://openalex.org/C118671147","wikidata":"https://www.wikidata.org/wiki/Q578714","display_name":"Quantile","level":2,"score":0.6051524877548218},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6017370820045471},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5481474995613098},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.5014469623565674},{"id":"https://openalex.org/C147224247","wikidata":"https://www.wikidata.org/wiki/Q885373","display_name":"Bloom filter","level":2,"score":0.44872891902923584},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.4209238290786743},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.41836756467819214},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.39552196860313416},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.23670107126235962},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11012351512908936},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08623233437538147},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3063955.3063995","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3063955.3063995","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Turing 50th Celebration Conference - China","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1526735133","https://openalex.org/W1574338450","https://openalex.org/W1785933978","https://openalex.org/W1966446553","https://openalex.org/W1976597724","https://openalex.org/W1976821017","https://openalex.org/W1982092405","https://openalex.org/W1984220394","https://openalex.org/W1996641400","https://openalex.org/W2008365755","https://openalex.org/W2017203676","https://openalex.org/W2018030107","https://openalex.org/W2022858489","https://openalex.org/W2025051251","https://openalex.org/W2059788796","https://openalex.org/W2063029095","https://openalex.org/W2071425575","https://openalex.org/W2071989194","https://openalex.org/W2076538837","https://openalex.org/W2099480861","https://openalex.org/W2102008855","https://openalex.org/W2112452856","https://openalex.org/W2134113644","https://openalex.org/W2135472951","https://openalex.org/W2144982963","https://openalex.org/W2145555113","https://openalex.org/W2161118867","https://openalex.org/W2293983046","https://openalex.org/W2323881768","https://openalex.org/W2507560318","https://openalex.org/W2525740015","https://openalex.org/W2998368829"],"related_works":["https://openalex.org/W2372409997","https://openalex.org/W2358886482","https://openalex.org/W656971665","https://openalex.org/W2531041707","https://openalex.org/W3196777484","https://openalex.org/W4310912227","https://openalex.org/W2316183108","https://openalex.org/W3077268226","https://openalex.org/W3131475429","https://openalex.org/W2613277090"],"abstract_inverted_index":{"Quantiles":[0],"and":[1,26,66,82,87,105,113,119,134,141],"Cardinality":[2],"queries":[3,43,65,68,99],"are":[4],"important":[5],"tools":[6],"to":[7,16,34],"analyze":[8],"statistical":[9],"information":[10],"from":[11],"big":[12,48,137],"data":[13,49,71,138,153],"streams.":[14,50,72],"Due":[15],"the":[17,20,39,70],"features":[18],"of":[19,42,98,110],"streams,":[21],"such":[22],"as":[23],"huge":[24],"volume":[25],"high":[27],"velocity,":[28],"it":[29,142],"is":[30],"a":[31,56,78],"challenging":[32],"problem":[33],"quickly":[35],"provide":[36],"responses":[37],"for":[38],"two":[40,96],"types":[41,97],"using":[44],"constrained":[45],"space":[46],"over":[47,69],"In":[51],"this":[52],"paper,":[53],"we":[54],"propose":[55,83],"composed":[57],"sketch":[58,85],"framework,":[59],"which":[60],"can":[61,93,126],"support":[62,94],"both":[63],"quantiles":[64],"cardinality":[67,75],"We":[73,101],"introduce":[74],"estimators":[76],"into":[77],"baseline":[79],"q-digest":[80],"structure":[81],"unified":[84],"merging":[86],"query":[88,111,114],"processing":[89],"operations.":[90],"Our":[91],"approach":[92,125],"these":[95],"simultaneously.":[100],"conduct":[102],"detailed":[103],"theoretical":[104],"experimental":[106,120],"analysis":[107],"in":[108,136,150],"terms":[109],"accuracy":[112],"response":[115],"time.":[116],"The":[117],"analytical":[118],"results":[121],"show":[122],"that":[123],"our":[124],"obtain":[127],"accurate":[128],"estimates":[129],"quicker":[130],"than":[131,146],"traditional":[132],"method":[133],"system":[135],"streams":[139],"environments,":[140],"just":[143],"produces":[144],"less":[145],"0.8\u2030":[147],"storage":[148],"overhead":[149],"TB-scale":[151],"real-world":[152],"sets.":[154]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
