{"id":"https://openalex.org/W7118099246","doi":"https://doi.org/10.1145/3785417","title":"Ribbon: Fast Succinct Static Retrieval and Approximate Membership","display_name":"Ribbon: Fast Succinct Static Retrieval and Approximate Membership","publication_year":2026,"publication_date":"2026-01-03","ids":{"openalex":"https://openalex.org/W7118099246","doi":"https://doi.org/10.1145/3785417"},"language":"en","primary_location":{"id":"doi:10.1145/3785417","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3785417","pdf_url":null,"source":{"id":"https://openalex.org/S118992489","display_name":"Journal of the ACM","issn_l":"0004-5411","issn":["0004-5411","1557-735X"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the ACM","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1145/3785417","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067257613","display_name":"Martin Dietzfelbinger","orcid":"https://orcid.org/0000-0001-5484-3474"},"institutions":[{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Martin Dietzfelbinger","raw_affiliation_strings":["Technische Universit\u00e4t Ilmenau"],"raw_orcid":"https://orcid.org/0000-0001-5484-3474","affiliations":[{"raw_affiliation_string":"Technische Universit\u00e4t Ilmenau","institution_ids":["https://openalex.org/I119449181"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035029457","display_name":"Peter C. Dillinger","orcid":"https://orcid.org/0009-0000-2662-2607"},"institutions":[{"id":"https://openalex.org/I4210092558","display_name":"BC Platforms (Finland)","ror":"https://ror.org/002fen565","country_code":"FI","type":"company","lineage":["https://openalex.org/I4210092558"]},{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]}],"countries":["FI","US"],"is_corresponding":false,"raw_author_name":"Peter C. Dillinger","raw_affiliation_strings":["Meta Platforms Inc"],"raw_orcid":"https://orcid.org/0009-0000-2662-2607","affiliations":[{"raw_affiliation_string":"Meta Platforms Inc","institution_ids":["https://openalex.org/I4210092558","https://openalex.org/I4210114444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121873268","display_name":"Lorenz H\u00fcbschle","orcid":null},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]},{"id":"https://openalex.org/I4210108719","display_name":"EP Analytics (United States)","ror":"https://ror.org/020emvx88","country_code":"US","type":"company","lineage":["https://openalex.org/I4210108719"]}],"countries":["DE","US"],"is_corresponding":false,"raw_author_name":"Lorenz H\u00fcbschle","raw_affiliation_strings":["Firebolt Analytics","Karlsruhe Institute of Technology"],"raw_orcid":"https://orcid.org/0000-0002-4315-3264","affiliations":[{"raw_affiliation_string":"Firebolt Analytics","institution_ids":["https://openalex.org/I4210108719"]},{"raw_affiliation_string":"Karlsruhe Institute of Technology","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082922326","display_name":"Peter Sanders","orcid":"https://orcid.org/0000-0003-3330-9349"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Peter Sanders","raw_affiliation_strings":["Karlsruhe Institute of Technology"],"raw_orcid":"https://orcid.org/0000-0003-3330-9349","affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024860874","display_name":"Stefan Walzer","orcid":"https://orcid.org/0000-0002-6477-0106"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Stefan Walzer","raw_affiliation_strings":["Karlsruhe Institute of Technology"],"raw_orcid":"https://orcid.org/0000-0002-6477-0106","affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology","institution_ids":["https://openalex.org/I102335020"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"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":0.04438914,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"73","issue":"1","first_page":"1","last_page":"45"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10720","display_name":"Complexity and Algorithms in Graphs","score":0.1404999941587448,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10720","display_name":"Complexity and Algorithms in Graphs","score":0.1404999941587448,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.11949999630451202,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.07429999858140945,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/bloom-filter","display_name":"Bloom filter","score":0.7731000185012817},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5878000259399414},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.5174999833106995},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5005999803543091},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.49939998984336853},{"id":"https://openalex.org/keywords/data-structure","display_name":"Data structure","score":0.4950999915599823},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.48399999737739563},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4731999933719635}],"concepts":[{"id":"https://openalex.org/C147224247","wikidata":"https://www.wikidata.org/wiki/Q885373","display_name":"Bloom filter","level":2,"score":0.7731000185012817},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6575999855995178},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5878000259399414},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.5174999833106995},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5063999891281128},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5005999803543091},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.49939998984336853},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.4950999915599823},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4864000082015991},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.48399999737739563},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4731999933719635},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4578000009059906},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4542999863624573},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.4293000102043152},{"id":"https://openalex.org/C13336665","wikidata":"https://www.wikidata.org/wiki/Q125977","display_name":"Vector space","level":2,"score":0.38510000705718994},{"id":"https://openalex.org/C130590232","wikidata":"https://www.wikidata.org/wiki/Q1671754","display_name":"Inverted index","level":3,"score":0.3614000082015991},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.3361999988555908},{"id":"https://openalex.org/C150807984","wikidata":"https://www.wikidata.org/wiki/Q1992074","display_name":"Bit array","level":3,"score":0.30250000953674316},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.3019999861717224},{"id":"https://openalex.org/C41431624","wikidata":"https://www.wikidata.org/wiki/Q1053357","display_name":"Block size","level":3,"score":0.29829999804496765},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.2840000092983246},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.27079999446868896},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.2513999938964844}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3785417","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3785417","pdf_url":null,"source":{"id":"https://openalex.org/S118992489","display_name":"Journal of the ACM","issn_l":"0004-5411","issn":["0004-5411","1557-735X"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the ACM","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3785417","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3785417","pdf_url":null,"source":{"id":"https://openalex.org/S118992489","display_name":"Journal of the ACM","issn_l":"0004-5411","issn":["0004-5411","1557-735X"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the ACM","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6032996601","display_name":"Analyse von RandomWalk Einf\u00fcgungen in CuckooHashtabellen und praxisnahe FilterDatenstrukturen","funder_award_id":"465963632","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1589951627","https://openalex.org/W1987102081","https://openalex.org/W2014367232","https://openalex.org/W2015840019","https://openalex.org/W2023065712","https://openalex.org/W2068426410","https://openalex.org/W2071483197","https://openalex.org/W2097286495","https://openalex.org/W2103559118","https://openalex.org/W2105718791","https://openalex.org/W2115104320","https://openalex.org/W2116435146","https://openalex.org/W2123845384","https://openalex.org/W2125763460","https://openalex.org/W2136399778","https://openalex.org/W2146005787","https://openalex.org/W2952096314","https://openalex.org/W2965352442","https://openalex.org/W2994941531","https://openalex.org/W2999307977","https://openalex.org/W3118154643","https://openalex.org/W4243961364","https://openalex.org/W4254982796","https://openalex.org/W4414452381"],"related_works":[],"abstract_inverted_index":{"Given":[0],"a":[1,8,15,54,63,94,120,130,151,157,164,180,194,197,202,272,280,333,344,355],"set":[2],"\\(S":[3],"\\subseteq":[4],"\\mathcal":[5,42],"{U}\\)":[6],"and":[7,31,84,128,169,223,239,264,284,301,339,363],"function":[9],"\\(f:S\\rightarrow":[10],"\\lbrace":[11,125,133,184],"0,1\\rbrace":[12,37,126,134,185],"^r\\)":[13,38],",":[14,98,168,257,263,270],"static":[16,55],"retrieval":[17,250],"data":[18,47,60,217,352],"structure":[19],"for":[20,27,39,78,93,143,271],"f":[21],"supports":[22],"queries":[23],"that":[24,138,278],"return":[25],"\\(f(x)\\)":[26],"\\(x":[28,40,116,145],"\\in":[29,41,117,124,146,183],"S\\)":[30,44,118,147],"an":[32],"arbitrary":[33],"value":[34],"from":[35,332],"\\(\\lbrace":[36],"{U}\\setminus":[43],".":[45,72,106,148,212,227],"Retrieval":[46,222],"structures":[48,218],"can":[49],"be":[50,293],"used":[51],"to":[52,88,110,246,292,296],"implement":[53],"approximate":[56],"membership":[57],"query":[58,258],"(AMQ)":[59],"structure,":[61],"i.e.,":[62],"Bloom":[64],"filter":[65],"alternative,":[66],"with":[67,102,119,189,252,307],"false":[68],"positive":[69],"rate":[70],"\\(2^{-r}\\)":[71],"The":[73],"information-theoretic":[74],"space":[75,90,283,324],"lower":[76],"bound":[77],"both":[79],"tasks":[80],"is":[81,170],"\\(r|S|\\)":[82],"bits,":[83],"here":[85],"we":[86],"aim":[87],"use":[89],"\\(r|S|(1+\\varepsilon)\\)":[91],"bits":[92,162],"small":[95,299],"overhead":[96,253],"\\(\\varepsilon\\)":[97],"including":[99,328,354],"succinct":[100],"constructions":[101],"\\(\\varepsilon":[103],"=":[104,141],"o(1)\\)":[105],"A":[107],"well-known":[108],"approach":[109],"this":[111],"task":[112],"associates":[113],"each":[114],"key":[115],"row":[121,175],"vector":[122],"\\(\\smash{\\vec{h}}(x)":[123],"^{m}\\)":[127],"stores":[129],"matrix":[131,181],"\\(Z\\in":[132],"^{m\\times":[135],"r}\\)":[136],"such":[137],"\\(\\smash{\\vec{h}}(x)\\cdot":[139],"Z":[140,211],"f(x)\\)":[142],"every":[144],"We":[149,213,228,342],"propose":[150],"new":[152],"variant":[153,203,236],"where":[154],"\\(\\smash{\\vec{h}}(x)\\)":[155],"contains":[156],"short":[158],"block":[159],"of":[160,204,237,335,359],"random":[161,165],"at":[163,209],"position":[166],"\\(s(x)\\)":[167,178],"otherwise":[171],"zero.":[172],"Sorting":[173],"the":[174,231,294],"vectors":[176],"by":[177],"gives":[179],"\\(A":[182],"^{n":[186],"\\times":[187],"m}\\)":[188],"non-zero":[190],"entries":[191],"concentrated":[192],"in":[193,305],"\u201cribbon\u201d":[195],"along":[196],"generalized":[198],"diagonal.":[199],"This":[200,326],"makes":[201],"Gaussian":[205],"elimination":[206],"particularly":[207],"efficient":[208],"computing":[210],"thus":[214],"obtain":[215,247],"simple":[216],"called":[219],"Standard":[220],"Ribbon":[221,225],"Homogeneous":[224],"Filter":[226],"then":[229],"refine":[230],"construction":[232,266],"using":[233],"bumping":[234],"(a":[235],"backyarding)":[238],"overloading":[240],"(using":[241],"\\(m":[242],"\\lt":[243],"n\\)":[244],")":[245],"bumped":[248],"ribbon":[249],"(\u201cBuRR\u201d),":[251],"\\(\\mathcal":[254,260,268],"{O}\\!(\\frac{\\log":[255],"w}{rw^2})\\)":[256],"time":[259,267],"{O}\\!(1+\\frac{rw}{\\log":[261],"n})\\)":[262],"expected":[265],"{O}\\!\\left(nw\\right)\\)":[269],"tuning":[273],"parameter":[274],"\\(w=\\mathcal":[275],"{O}\\!\\left(\\log":[276],"n\\right)\\)":[277],"opens":[279],"trade-off":[281],"between":[282],"running":[285,303,361],"time.":[286],"Our":[287],"experiments":[288],"reveal":[289],"our":[290],"implementations":[291],"first":[295],"simultaneously":[297],"achieve":[298],"overheads":[300,310],"fast":[302],"times":[304,362],"practice,":[306],"BuRR":[308],"achieving":[309],"well":[311],"below":[312],"1":[313],"%":[314],"while":[315],"being":[316],"faster":[317],"than":[318],"most":[319],"competitors,":[320],"which":[321],"have":[322],"larger":[323],"overheads.":[325],"efficiency,":[327],"favorable":[329],"constants,":[330],"stems":[331],"combination":[334],"simplicity,":[336],"word":[337],"parallelism,":[338],"high":[340],"locality.":[341],"offer":[343],"unified":[345],"theoretical":[346],"perspective":[347],"on":[348],"these":[349],"three":[350],"ribbon-based":[351],"structures,":[353],"nontrivial":[356],"rigorous":[357],"analysis":[358],"their":[360],"memory":[364],"consumption.":[365]},"counts_by_year":[],"updated_date":"2026-06-22T08:00:12.763002","created_date":"2026-01-03T00:00:00"}
