{"id":"https://openalex.org/W2752425993","doi":"https://doi.org/10.14778/3137628.3137645","title":"ASAP","display_name":"ASAP","publication_year":2017,"publication_date":"2017-08-01","ids":{"openalex":"https://openalex.org/W2752425993","doi":"https://doi.org/10.14778/3137628.3137645","mag":"2752425993"},"language":"en","primary_location":{"id":"doi:10.14778/3137628.3137645","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3137628.3137645","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"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 VLDB Endowment","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1703.00983","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Kexin Rong","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kexin Rong","raw_affiliation_strings":["Stanford InfoLab"],"affiliations":[{"raw_affiliation_string":"Stanford InfoLab","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Peter Bailis","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peter Bailis","raw_affiliation_strings":["Stanford InfoLab"],"affiliations":[{"raw_affiliation_string":"Stanford InfoLab","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.5513,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.94005878,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"10","issue":"11","first_page":"1358","last_page":"1369"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9998999834060669,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9998999834060669,"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/T10799","display_name":"Data Visualization and Analytics","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9860000014305115,"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/visualization","display_name":"Visualization","score":0.5673999786376953},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5414999723434448},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.4912000000476837},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.47049999237060547},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.4672999978065491},{"id":"https://openalex.org/keywords/interface","display_name":"Interface (matter)","score":0.45750001072883606},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4562999904155731},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.4431999921798706},{"id":"https://openalex.org/keywords/stream-processing","display_name":"Stream processing","score":0.4392000138759613}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.795199990272522},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5702999830245972},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5673999786376953},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5414999723434448},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.5060999989509583},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.4912000000476837},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.47049999237060547},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.4672999978065491},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.45750001072883606},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4562999904155731},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.4431999921798706},{"id":"https://openalex.org/C107027933","wikidata":"https://www.wikidata.org/wiki/Q2006448","display_name":"Stream processing","level":2,"score":0.4392000138759613},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.4117000102996826},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.3921999931335449},{"id":"https://openalex.org/C167651023","wikidata":"https://www.wikidata.org/wiki/Q1474611","display_name":"Plot (graphics)","level":2,"score":0.390500009059906},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.34529998898506165},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.3400999903678894},{"id":"https://openalex.org/C31462909","wikidata":"https://www.wikidata.org/wiki/Q1045782","display_name":"Scatter plot","level":2,"score":0.3382999897003174},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.337799996137619},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.32100000977516174},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.31299999356269836},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3043999969959259},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.26249998807907104},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.2605000138282776},{"id":"https://openalex.org/C89505385","wikidata":"https://www.wikidata.org/wiki/Q47146","display_name":"User interface","level":2,"score":0.25450000166893005},{"id":"https://openalex.org/C5297727","wikidata":"https://www.wikidata.org/wiki/Q786970","display_name":"Autocorrelation","level":2,"score":0.25279998779296875}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.14778/3137628.3137645","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3137628.3137645","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"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 VLDB Endowment","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1703.00983","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1703.00983","pdf_url":"https://arxiv.org/pdf/1703.00983","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1703.00983","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1703.00983","pdf_url":"https://arxiv.org/pdf/1703.00983","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W659481405","https://openalex.org/W1961845056","https://openalex.org/W1972833205","https://openalex.org/W1981934656","https://openalex.org/W1989243075","https://openalex.org/W1989417989","https://openalex.org/W1995003166","https://openalex.org/W1996021349","https://openalex.org/W2003501387","https://openalex.org/W2040148652","https://openalex.org/W2047877155","https://openalex.org/W2066796814","https://openalex.org/W2079351568","https://openalex.org/W2097747115","https://openalex.org/W2098515641","https://openalex.org/W2101717554","https://openalex.org/W2105510466","https://openalex.org/W2106595237","https://openalex.org/W2111736285","https://openalex.org/W2113131123","https://openalex.org/W2119111481","https://openalex.org/W2122430112","https://openalex.org/W2147768899","https://openalex.org/W2152922709","https://openalex.org/W2166597031","https://openalex.org/W2191950414","https://openalex.org/W2242977838","https://openalex.org/W2245828441","https://openalex.org/W2294510862","https://openalex.org/W2294581520","https://openalex.org/W2296760620","https://openalex.org/W2496675188","https://openalex.org/W2613751718","https://openalex.org/W2752425993","https://openalex.org/W2963707382","https://openalex.org/W4251696430"],"related_works":[],"abstract_inverted_index":{"Time":[0],"series":[1,59,89,160],"visualization":[2],"of":[3,8,113,180],"streaming":[4,87],"telemetry":[5],"(i.e.,":[6,98,103],"charting":[7],"key":[9],"metrics":[10,107,125],"such":[11],"as":[12,36,61,63],"server":[13],"load":[14],"over":[15],"time)":[16],"is":[17],"increasingly":[18],"prevalent":[19],"in":[20,154,158],"modern":[21],"data":[22,34],"platforms":[23],"and":[24,100,116,135,143],"applications.":[25],"However,":[26],"many":[27],"existing":[28],"systems":[29],"simply":[30],"plot":[31],"the":[32,93,111],"raw":[33],"streams":[35],"they":[37],"arrive,":[38],"often":[39],"obscuring":[40],"large-scale":[41,70],"trends":[42],"due":[43],"to":[44,51,65,72,108,163,171],"small-scale":[45],"noise.":[46],"We":[47,76,105,146],"propose":[48],"an":[49,118],"alternative:":[50],"better":[52],"prioritize":[53],"end":[54],"users'":[55,152],"attention,":[56],"smooth":[57],"time":[58,88,159],"visualizations":[60],"much":[62],"possible":[64],"remove":[66],"noise,":[67],"while":[68,165],"retaining":[69],"structure":[71],"highlight":[73],"significant":[74],"deviations.":[75],"develop":[77],"a":[78],"new":[79],"analytics":[80],"operator":[81],"called":[82],"ASAP":[83,149,174],"that":[84,126,148],"automatically":[85],"smooths":[86],"by":[90,161,169],"adaptively":[91],"optimizing":[92,123],"trade-off":[94],"between":[95],"noise":[96],"reduction":[97],"variance)":[99],"trend":[101],"retention":[102],"kurtosis).":[104],"introduce":[106],"quantitatively":[109],"assess":[110],"quality":[112],"smoothed":[114],"plots":[115],"provide":[117],"efficient":[119],"search":[120,185],"strategy":[121],"for":[122],"these":[124,176],"combines":[127],"techniques":[128],"from":[129],"stream":[130],"processing,":[131],"user":[132],"interface":[133],"design,":[134],"signal":[136],"processing":[137],"via":[138],"autocorrelation-based":[139],"pruning,":[140],"pixel-aware":[141],"preaggregation,":[142],"on-demand":[144],"refresh.":[145],"demonstrate":[147],"can":[150],"improve":[151],"accuracy":[153],"identifying":[155],"long-term":[156],"deviations":[157],"up":[162,170],"38.4%":[164],"reducing":[166],"response":[167],"times":[168],"44.3%.":[172],"Moreover,":[173],"delivers":[175],"results":[177],"several":[178],"orders":[179],"magnitude":[181],"faster":[182],"than":[183],"alternative":[184],"strategies.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2017-09-15T00:00:00"}