{"id":"https://openalex.org/W4405623283","doi":"https://doi.org/10.1145/3698799","title":"A Universal Sketch for Estimating Heavy Hitters and Per-Element Frequency Moments in Data Streams with Bounded Deletions","display_name":"A Universal Sketch for Estimating Heavy Hitters and Per-Element Frequency Moments in Data Streams with Bounded Deletions","publication_year":2024,"publication_date":"2024-12-18","ids":{"openalex":"https://openalex.org/W4405623283","doi":"https://doi.org/10.1145/3698799"},"language":"en","primary_location":{"id":"doi:10.1145/3698799","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3698799","pdf_url":null,"source":{"id":"https://openalex.org/S4387289859","display_name":"Proceedings of the ACM on Management of Data","issn_l":"2836-6573","issn":["2836-6573"],"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":"Proceedings of the ACM on Management of Data","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/A5013074804","display_name":"Liang Zheng","orcid":"https://orcid.org/0000-0002-4148-2531"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Zheng","raw_affiliation_strings":["Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-4148-2531","affiliations":[{"raw_affiliation_string":"Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103068268","display_name":"Qingjun Xiao","orcid":"https://orcid.org/0000-0001-8348-6277"},"institutions":[{"id":"https://openalex.org/I4210155350","display_name":"Purple Mountain Laboratories","ror":"https://ror.org/04zcbk583","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210155350"]},{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingjun Xiao","raw_affiliation_strings":["Southeast University &amp; Purple Mountain Laboratories, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-8348-6277","affiliations":[{"raw_affiliation_string":"Southeast University &amp; Purple Mountain Laboratories, Nanjing, China","institution_ids":["https://openalex.org/I4210155350","https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039789853","display_name":"Xuyuan Cai","orcid":"https://orcid.org/0009-0000-3498-3269"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xuyuan Cai","raw_affiliation_strings":["The Hong Kong Polytechnic University, Hong Kong, China"],"raw_orcid":"https://orcid.org/0009-0000-3498-3269","affiliations":[{"raw_affiliation_string":"The Hong Kong Polytechnic University, Hong Kong, China","institution_ids":["https://openalex.org/I14243506"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6109,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.75757161,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"2","issue":"6","first_page":"1","last_page":"28"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9943000078201294,"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":0.9943000078201294,"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/T11181","display_name":"Advanced Data Storage Technologies","score":0.9937000274658203,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9882000088691711,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.7515742778778076},{"id":"https://openalex.org/keywords/turnstile","display_name":"Turnstile","score":0.7296324968338013},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.7263516783714294},{"id":"https://openalex.org/keywords/sketch","display_name":"Sketch","score":0.7020381689071655},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6750717163085938},{"id":"https://openalex.org/keywords/moment","display_name":"Moment (physics)","score":0.6137876510620117},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.5109704732894897},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4776288866996765},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.363237202167511},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35354241728782654},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24921056628227234},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.21094515919685364},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.12931013107299805},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10225963592529297}],"concepts":[{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.7515742778778076},{"id":"https://openalex.org/C31370731","wikidata":"https://www.wikidata.org/wiki/Q7856108","display_name":"Turnstile","level":2,"score":0.7296324968338013},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7263516783714294},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.7020381689071655},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6750717163085938},{"id":"https://openalex.org/C179254644","wikidata":"https://www.wikidata.org/wiki/Q13222844","display_name":"Moment (physics)","level":2,"score":0.6137876510620117},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.5109704732894897},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4776288866996765},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.363237202167511},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35354241728782654},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24921056628227234},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.21094515919685364},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.12931013107299805},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10225963592529297},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3698799","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3698799","pdf_url":null,"source":{"id":"https://openalex.org/S4387289859","display_name":"Proceedings of the ACM on Management of Data","issn_l":"2836-6573","issn":["2836-6573"],"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":"Proceedings of the ACM on Management of Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8386001543","display_name":null,"funder_award_id":"62372106","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"}],"funders":[{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":86,"referenced_works":["https://openalex.org/W139562302","https://openalex.org/W934716473","https://openalex.org/W1493892051","https://openalex.org/W1553409264","https://openalex.org/W1603054560","https://openalex.org/W1967373117","https://openalex.org/W1982092405","https://openalex.org/W2008365755","https://openalex.org/W2013092187","https://openalex.org/W2031469255","https://openalex.org/W2034302520","https://openalex.org/W2044163187","https://openalex.org/W2069354103","https://openalex.org/W2079136461","https://openalex.org/W2080234606","https://openalex.org/W2089526311","https://openalex.org/W2109885200","https://openalex.org/W2149655761","https://openalex.org/W2150815390","https://openalex.org/W2153329411","https://openalex.org/W2170051345","https://openalex.org/W2396309311","https://openalex.org/W2439904216","https://openalex.org/W2487095677","https://openalex.org/W2744999500","https://openalex.org/W2762095987","https://openalex.org/W2762566515","https://openalex.org/W2791481841","https://openalex.org/W2794166030","https://openalex.org/W2795767639","https://openalex.org/W2798945787","https://openalex.org/W2808923818","https://openalex.org/W2834288129","https://openalex.org/W2891033072","https://openalex.org/W2912116129","https://openalex.org/W2914354916","https://openalex.org/W2919413299","https://openalex.org/W2950087731","https://openalex.org/W2953245460","https://openalex.org/W2963554098","https://openalex.org/W2963777735","https://openalex.org/W2963799254","https://openalex.org/W2963898466","https://openalex.org/W2969998124","https://openalex.org/W2981467700","https://openalex.org/W2985266342","https://openalex.org/W3006383271","https://openalex.org/W3031055876","https://openalex.org/W3047614006","https://openalex.org/W3080797160","https://openalex.org/W3089269561","https://openalex.org/W3108496275","https://openalex.org/W3145761337","https://openalex.org/W3146390850","https://openalex.org/W3160096331","https://openalex.org/W3177067869","https://openalex.org/W3177390287","https://openalex.org/W3187255254","https://openalex.org/W4206137901","https://openalex.org/W4214728981","https://openalex.org/W4281937774","https://openalex.org/W4282971155","https://openalex.org/W4283208007","https://openalex.org/W4283330163","https://openalex.org/W4283824866","https://openalex.org/W4292262069","https://openalex.org/W4294904071","https://openalex.org/W4295576077","https://openalex.org/W4309579729","https://openalex.org/W4319865713","https://openalex.org/W4366660704","https://openalex.org/W4367666238","https://openalex.org/W4380433098","https://openalex.org/W4380433194","https://openalex.org/W4385562482","https://openalex.org/W4385679864","https://openalex.org/W4386233238","https://openalex.org/W4387502232","https://openalex.org/W4387559950","https://openalex.org/W4387846849","https://openalex.org/W4388563087","https://openalex.org/W4388620448","https://openalex.org/W4389315109","https://openalex.org/W4396734360","https://openalex.org/W4405623283","https://openalex.org/W6839006050"],"related_works":["https://openalex.org/W2652858764","https://openalex.org/W2024933994","https://openalex.org/W1991681928","https://openalex.org/W2378994405","https://openalex.org/W2385974820","https://openalex.org/W2373478030","https://openalex.org/W2378679551","https://openalex.org/W4206455007","https://openalex.org/W2112927832","https://openalex.org/W2966643660"],"abstract_inverted_index":{"In":[0,43,154,183],"the":[1,23,37,56,142,159,170,187,200,231],"field":[2],"of":[3,39,58,72,79,189,203,225,233],"data":[4],"stream":[5,110],"processing,":[6],"there":[7,129,134],"are":[8,102,130],"two":[9,103],"prevalent":[10],"models,":[11],"i.e.,":[12],"insertion-only,":[13],"and":[14,35,86,98,168,207,229],"turnstile":[15,64,109,147],"models.":[16],"Most":[17],"previous":[18,116],"works":[19],"were":[20],"proposed":[21],"for":[22,106,118],"insertion-only":[24],"model,":[25,148],"which":[26,197],"assumes":[27],"new":[28,70],"elements":[29],"arrive":[30],"continuously":[31],"as":[32],"a":[33,48,53,63,69,108,124,164,173,193,204],"stream,":[34,65],"neglects":[36],"possibilities":[38],"removing":[40],"existing":[41],"elements.":[42],"this":[44,155],"paper,":[45,156],"we":[46,66,157,185],"make":[47],"bounded":[49,112,125],"deletion":[50,131],"assumption,":[51],"putting":[52],"constraint":[54],"on":[55,68],"number":[57],"deletions":[59],"allowed.":[60],"For":[61],"such":[62],"focus":[67],"problem":[71],"universal":[73],"measurement":[74],"that":[75,214],"estimates":[76],"multiple":[77],"kinds":[78],"statistical":[80],"metrics":[81],"simultaneously":[82],"using":[83],"limited":[84],"memory":[85,201],"in":[87,150,222],"an":[88,151,179],"online":[89,152],"fashion,":[90],"including":[91],"per-element":[92,143],"frequency,":[93],"heavy":[94,120,226],"hitters,":[95],"frequency":[96,99,144,190,205,234],"moments,":[97],"distribution.":[100],"There":[101],"key":[104],"challenges":[105],"processing":[107],"with":[111,178],"deletions.":[113],"Firstly,":[114],"most":[115],"methods":[117],"detecting":[119],"hitters":[121],"cannot":[122],"ensure":[123],"detection":[126],"error":[127],"when":[128],"events.":[132],"Secondly,":[133],"is":[135],"still":[136],"no":[137],"prior":[138],"work":[139],"to":[140],"estimate":[141],"moments":[145],"under":[146],"especially":[149],"fashion.":[153],"address":[158,169],"former":[160],"challenge":[161],"by":[162,172,192,220,237],"proposing":[163],"Removable":[165,174],"Augmented":[166],"Sketch,":[167,176],"latter":[171],"Universal":[175],"enhanced":[177],"Online":[180],"Moment":[181],"Estimator.":[182],"addition,":[184],"improve":[186],"accuracy":[188],"estimation":[191,236],"compressed":[194],"counter":[195,206],"design,":[196],"can":[198],"halve":[199],"cost":[202],"support":[208],"addition/minus":[209],"operations.":[210],"Our":[211],"experiments":[212],"show":[213],"our":[215],"solution":[216],"outperforms":[217],"other":[218],"algorithms":[219],"16%~69%":[221],"F1":[223],"Score":[224],"hitter":[227],"detection,":[228],"improves":[230],"throughput":[232],"moment":[235],"3.0x10":[238],"4":[239],"times.":[240]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
