{"id":"https://openalex.org/W7155373700","doi":"https://doi.org/10.1145/3810900.3810910","title":"Dynamic Range Filtering Beyond Worst-Case Bounds","display_name":"Dynamic Range Filtering Beyond Worst-Case Bounds","publication_year":2026,"publication_date":"2026-04-23","ids":{"openalex":"https://openalex.org/W7155373700","doi":"https://doi.org/10.1145/3810900.3810910"},"language":"en","primary_location":{"id":"doi:10.1145/3810900.3810910","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3810900.3810910","pdf_url":null,"source":{"id":"https://openalex.org/S47508943","display_name":"ACM SIGMOD Record","issn_l":"0163-5808","issn":["0163-5808","1943-5835"],"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":"ACM SIGMOD Record","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/A5133118865","display_name":"Navid Eslami","orcid":null},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Navid Eslami","raw_affiliation_strings":["University of Toronto, Toronto, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Toronto, Toronto, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016433369","display_name":"Ioana O. Bercea","orcid":"https://orcid.org/0000-0001-8430-2441"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Ioana O. Bercea","raw_affiliation_strings":["KTH Royal Institute of Technology, Stockholm, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003707725","display_name":"Niv Dayan","orcid":"https://orcid.org/0000-0003-0314-0167"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Niv Dayan","raw_affiliation_strings":["University of Toronto, Toronto, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Toronto, Toronto, Canada","institution_ids":["https://openalex.org/I185261750"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.61403324,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"55","issue":"1","first_page":"51","last_page":"60"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","score":0.29019999504089355,"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/T11269","display_name":"Algorithms and Data Compression","score":0.29019999504089355,"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/T12326","display_name":"Network Packet Processing and Optimization","score":0.241799995303154,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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":0.11129999905824661,"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/trie","display_name":"Trie","score":0.7077000141143799},{"id":"https://openalex.org/keywords/range-query","display_name":"Range query (database)","score":0.6955000162124634},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.6517999768257141},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5584999918937683},{"id":"https://openalex.org/keywords/prefix","display_name":"Prefix","score":0.4715999960899353},{"id":"https://openalex.org/keywords/data-structure","display_name":"Data structure","score":0.44909998774528503},{"id":"https://openalex.org/keywords/query-optimization","display_name":"Query optimization","score":0.3504999876022339},{"id":"https://openalex.org/keywords/hyperspace","display_name":"Hyperspace","score":0.3382999897003174}],"concepts":[{"id":"https://openalex.org/C190290938","wikidata":"https://www.wikidata.org/wiki/Q387015","display_name":"Trie","level":3,"score":0.7077000141143799},{"id":"https://openalex.org/C136736807","wikidata":"https://www.wikidata.org/wiki/Q818943","display_name":"Range query (database)","level":5,"score":0.6955000162124634},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.6517999768257141},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6255999803543091},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5584999918937683},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.505299985408783},{"id":"https://openalex.org/C141603448","wikidata":"https://www.wikidata.org/wiki/Q134830","display_name":"Prefix","level":2,"score":0.4715999960899353},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.44909998774528503},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43650001287460327},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4129999876022339},{"id":"https://openalex.org/C157692150","wikidata":"https://www.wikidata.org/wiki/Q2919848","display_name":"Query optimization","level":2,"score":0.3504999876022339},{"id":"https://openalex.org/C39368324","wikidata":"https://www.wikidata.org/wiki/Q5024959","display_name":"Hyperspace","level":2,"score":0.3382999897003174},{"id":"https://openalex.org/C2781092335","wikidata":"https://www.wikidata.org/wiki/Q867132","display_name":"Diva","level":2,"score":0.33469998836517334},{"id":"https://openalex.org/C182964748","wikidata":"https://www.wikidata.org/wiki/Q208216","display_name":"Triangle inequality","level":2,"score":0.32190001010894775},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3107999861240387},{"id":"https://openalex.org/C91154448","wikidata":"https://www.wikidata.org/wiki/Q623818","display_name":"Binary search tree","level":3,"score":0.3046000003814697},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.2971000075340271},{"id":"https://openalex.org/C134757568","wikidata":"https://www.wikidata.org/wiki/Q274089","display_name":"Heap (data structure)","level":2,"score":0.29649999737739563},{"id":"https://openalex.org/C121610932","wikidata":"https://www.wikidata.org/wiki/Q243754","display_name":"Binary search algorithm","level":3,"score":0.2948000133037567},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.29190000891685486},{"id":"https://openalex.org/C147224247","wikidata":"https://www.wikidata.org/wiki/Q885373","display_name":"Bloom filter","level":2,"score":0.28540000319480896},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2849999964237213},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3810900.3810910","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3810900.3810910","pdf_url":null,"source":{"id":"https://openalex.org/S47508943","display_name":"ACM SIGMOD Record","issn_l":"0163-5808","issn":["0163-5808","1943-5835"],"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":"ACM SIGMOD Record","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.624245285987854,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1764163631","https://openalex.org/W1967373117","https://openalex.org/W1985229168","https://openalex.org/W1986633843","https://openalex.org/W2055706406","https://openalex.org/W2057223122","https://openalex.org/W2060108852","https://openalex.org/W2068739275","https://openalex.org/W2090021115","https://openalex.org/W2115559007","https://openalex.org/W2116435146","https://openalex.org/W2123845384","https://openalex.org/W2127140580","https://openalex.org/W2145269645","https://openalex.org/W2161694911","https://openalex.org/W2170732565","https://openalex.org/W2612838847","https://openalex.org/W2798891709","https://openalex.org/W2945912251","https://openalex.org/W2962771342","https://openalex.org/W3018708672","https://openalex.org/W3034570653","https://openalex.org/W3096737792","https://openalex.org/W3173499193","https://openalex.org/W3174427814","https://openalex.org/W4255148642","https://openalex.org/W4281726021","https://openalex.org/W4283319958","https://openalex.org/W4381328627","https://openalex.org/W4385270179","https://openalex.org/W4393183875","https://openalex.org/W4398234086","https://openalex.org/W4399209859","https://openalex.org/W4401399649","https://openalex.org/W4402043624","https://openalex.org/W7080011846","https://openalex.org/W7151602384"],"related_works":[],"abstract_inverted_index":{"Range":[0],"filters":[1,48,211],"are":[2,13],"compact":[3],"data":[4,164],"structures":[5],"that":[6],"answer":[7],"approximate":[8],"range":[9,34,47,98,180],"emptiness":[10],"queries.":[11],"They":[12],"used":[14],"in":[15,19,30,42,118,142,154,161,196,220],"many":[16],"domains,":[17],"e.g.,":[18],"key-value":[20],"stores,":[21],"to":[22,38,100,148,172],"quickly":[23],"rule":[24],"out":[25],"the":[26,54,96,103,109,124,143,152,155,184,189,197,203,216,242],"existence":[27],"of":[28,53,191,205,208,218,236,244],"keys":[29,75,114,125,153],"a":[31,119,179],"given":[32],"query":[33,77,181,199],"and":[35,66,76,79,115,134,169,175,186,224,238],"avoid":[36],"having":[37],"search":[39],"for":[40,188],"them":[41,117],"storage.":[43],"However,":[44],"all":[45,102],"existing":[46],"exhibit":[49],"at":[50,192,215],"least":[51,193],"one":[52,194],"following":[55],"shortcomings:":[56],"(1)":[57],"they":[58,70,81],"do":[59,71,82],"not":[60,72,83],"provide":[61],"robust":[62],"false":[63],"positive":[64],"rate":[65],"performance":[67],"guarantees,":[68],"(2)":[69],"support":[73],"variable-length":[74],"ranges,":[78],"(3)":[80],"allow":[84,149],"dynamic":[85,163],"operations":[86],"such":[87],"as":[88],"insertions,":[89],"deletions,":[90],"or":[91],"expansions.":[92,176],"We":[93],"introduce":[94],"Diva,":[95],"first":[97],"filter":[99],"address":[101],"above":[104],"challenges":[105],"simultaneously.":[106],"Diva":[107,201,231],"learns":[108],"dataset's":[110],"distribution":[111],"by":[112,128,182],"sampling":[113],"storing":[116],"cacheefficient":[120],"trie.":[121],"It":[122,158,177],"compresses":[123],"in-between":[126],"samples":[127],"removing":[129],"their":[130,136],"longest":[131],"common":[132],"prefix":[133],"truncating":[135],"suffixes":[137],"while":[138],"leaving":[139],"enough":[140],"bits":[141],"middle":[144],"(i.e.,":[145],"an":[146],"infix)":[147],"differentiating":[150],"between":[151],"sorted":[156],"order.":[157],"stores":[159],"infixes":[160],"constant-time":[162],"blocks,":[165],"which":[166],"it":[167,240],"stretches":[168],"eventually":[170],"splits":[171],"handle":[173],"insertions":[174],"processes":[178],"traversing":[183],"trie":[185],"checking":[187],"inclusion":[190],"infix":[195],"target":[198],"range.":[200],"is":[202],"culmination":[204],"several":[206],"years":[207],"research":[209],"on":[210,233],"from":[212],"Orca":[213],"Lab":[214],"University":[217],"Toronto,":[219],"collaboration":[221],"with":[222],"KTH":[223],"Copenhagen":[225],"University.":[226],"This":[227],"paper":[228],"describes":[229],"how":[230,239],"builds":[232],"this":[234],"body":[235],"work,":[237],"addresses":[241],"limitations":[243],"prior":[245],"art.":[246]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-24T00:00:00"}
