{"id":"https://openalex.org/W4401863411","doi":"https://doi.org/10.1145/3637528.3671695","title":"QSketch: An Efficient Sketch for Weighted Cardinality Estimation in Streams","display_name":"QSketch: An Efficient Sketch for Weighted Cardinality Estimation in Streams","publication_year":2024,"publication_date":"2024-08-24","ids":{"openalex":"https://openalex.org/W4401863411","doi":"https://doi.org/10.1145/3637528.3671695"},"language":"en","primary_location":{"id":"doi:10.1145/3637528.3671695","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3637528.3671695","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-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/A5056609151","display_name":"Yiyan Qi","orcid":"https://orcid.org/0000-0002-8078-5834"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yiyan Qi","raw_affiliation_strings":["International Digital Economy Academy (IDEA), Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"International Digital Economy Academy (IDEA), Shenzhen, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101780303","display_name":"Rundong Li","orcid":"https://orcid.org/0000-0003-0354-9536"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rundong Li","raw_affiliation_strings":["MOE KLINNS Lab, Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"MOE KLINNS Lab, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102845337","display_name":"Pinghui Wang","orcid":"https://orcid.org/0000-0002-1434-837X"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pinghui Wang","raw_affiliation_strings":["MOE KLINNS Lab, Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"MOE KLINNS Lab, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100556199","display_name":"Yufang Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yufang Sun","raw_affiliation_strings":["MOE KLINNS Lab, Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"MOE KLINNS Lab, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106713430","display_name":"Rui Xing","orcid":null},"institutions":[{"id":"https://openalex.org/I88830068","display_name":"Shaanxi Normal University","ror":"https://ror.org/0170z8493","country_code":"CN","type":"education","lineage":["https://openalex.org/I88830068"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Xing","raw_affiliation_strings":["MOE KLINNS Lab, Shaanxi Normal University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"MOE KLINNS Lab, Shaanxi Normal University, Xi'an, China","institution_ids":["https://openalex.org/I88830068"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5056609151"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.047,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.78220883,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2432","last_page":"2443"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.9984999895095825,"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":0.9984999895095825,"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":0.9970999956130981,"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":0.9945999979972839,"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/sketch","display_name":"Sketch","score":0.9024950861930847},{"id":"https://openalex.org/keywords/cardinality","display_name":"Cardinality (data modeling)","score":0.8251050710678101},{"id":"https://openalex.org/keywords/streams","display_name":"STREAMS","score":0.7145675420761108},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7034979462623596},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.41017013788223267},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2783408761024475},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.26202595233917236},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.10476440191268921},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06868621706962585}],"concepts":[{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.9024950861930847},{"id":"https://openalex.org/C87117476","wikidata":"https://www.wikidata.org/wiki/Q362383","display_name":"Cardinality (data modeling)","level":2,"score":0.8251050710678101},{"id":"https://openalex.org/C42090638","wikidata":"https://www.wikidata.org/wiki/Q4048907","display_name":"STREAMS","level":2,"score":0.7145675420761108},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7034979462623596},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.41017013788223267},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2783408761024475},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26202595233917236},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.10476440191268921},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06868621706962585},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3637528.3671695","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3637528.3671695","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1555239021","https://openalex.org/W1603054560","https://openalex.org/W1965575862","https://openalex.org/W1977841655","https://openalex.org/W1979819093","https://openalex.org/W1997707785","https://openalex.org/W2002231822","https://openalex.org/W2005731313","https://openalex.org/W2008365755","https://openalex.org/W2010582541","https://openalex.org/W2025051251","https://openalex.org/W2034302520","https://openalex.org/W2068696370","https://openalex.org/W2075279061","https://openalex.org/W2099480861","https://openalex.org/W2103126020","https://openalex.org/W2107275319","https://openalex.org/W2111806841","https://openalex.org/W2134786002","https://openalex.org/W2144982963","https://openalex.org/W2148665392","https://openalex.org/W2150102617","https://openalex.org/W2168305032","https://openalex.org/W2372409997","https://openalex.org/W2418258478","https://openalex.org/W2604248105","https://openalex.org/W2762566515","https://openalex.org/W2792538726","https://openalex.org/W3012739726","https://openalex.org/W3120832396","https://openalex.org/W3210289779","https://openalex.org/W4232254113","https://openalex.org/W4255783720","https://openalex.org/W4290944102","https://openalex.org/W4317987633","https://openalex.org/W4381621962","https://openalex.org/W4391305444","https://openalex.org/W6749368518"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2378994405","https://openalex.org/W2385974820","https://openalex.org/W2373478030","https://openalex.org/W2378679551","https://openalex.org/W3149739944","https://openalex.org/W2392363776","https://openalex.org/W2063051341","https://openalex.org/W2591066345"],"abstract_inverted_index":{"Estimating":[0],"cardinality,":[1,48],"i.e.,":[2],"the":[3,169,175],"number":[4],"of":[5,8,100,137,165,174],"distinct":[6],"elements,":[7],"a":[9,13,29,36,77,89,97,133,144],"data":[10],"stream":[11],"is":[12,157],"fundamental":[14],"problem":[15],"in":[16,85],"areas":[17],"like":[18,67],"databases,":[19],"computer":[20],"networks,":[21],"and":[22,55,64,131,151,162],"information":[23],"retrieval.":[24],"This":[25],"study":[26],"delves":[27],"into":[28,96],"broader":[30],"scenario":[31],"where":[32],"each":[33,104],"element":[34],"carries":[35],"positive":[37],"weight.":[38],"Unlike":[39],"traditional":[40],"cardinality":[41,84],"estimation,":[42],"limited":[43,62],"research":[44],"exists":[45],"on":[46,149],"weighted":[47,83],"with":[49,61,103],"current":[50],"methods":[51],"requiring":[52,106],"substantial":[53],"memory":[54],"computational":[56],"resources,":[57],"challenging":[58],"for":[59,81,139],"devices":[60],"capabilities":[63],"real-time":[65],"applications":[66],"anomaly":[68],"detection.":[69],"To":[70],"address":[71],"these":[72],"issues,":[73],"we":[74,119],"propose":[75],"QSketch,":[76],"memory-efficient":[78],"sketch":[79],"method":[80],"estimating":[82],"streams.":[86],"QSketch":[87,124,156],"uses":[88],"quantization":[90],"technique":[91],"to":[92,126],"condense":[93],"continuous":[94],"variables":[95],"compact":[98],"set":[99],"integer":[101],"variables,":[102],"variable":[105],"only":[107,172],"8":[108,112],"bits,":[109],"making":[110],"it":[111],"times":[113],"smaller":[114],"than":[115,168],"previous":[116],"methods.":[117],"Furthermore,":[118],"leverage":[120],"dynamic":[121],"properties":[122],"during":[123],"generation":[125],"significantly":[127],"enhance":[128],"estimation":[129],"accuracy":[130],"achieve":[132],"lower":[134],"time":[135],"complexity":[136],"O(1)":[138],"updating":[140],"estimations":[141],"upon":[142],"encountering":[143],"new":[145],"element.":[146],"Experimental":[147],"results":[148],"synthetic":[150],"real-world":[152],"datasets":[153],"show":[154],"that":[155],"approximately":[158],"30%":[159],"more":[160],"accurate":[161],"two":[163],"orders":[164],"magnitude":[166],"faster":[167],"state-of-the-art,":[170],"using":[171],"1/8":[173],"memory.":[176]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}