{"id":"https://openalex.org/W2020110631","doi":"https://doi.org/10.1145/1254882.1254916","title":"Building high accuracy bloom filters using partitioned hashing","display_name":"Building high accuracy bloom filters using partitioned hashing","publication_year":2007,"publication_date":"2007-06-12","ids":{"openalex":"https://openalex.org/W2020110631","doi":"https://doi.org/10.1145/1254882.1254916","mag":"2020110631"},"language":"en","primary_location":{"id":"doi:10.1145/1254882.1254916","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1254882.1254916","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100604066","display_name":"Hao Fang","orcid":"https://orcid.org/0009-0006-7951-5796"},"institutions":[{"id":"https://openalex.org/I176714629","display_name":"Bell (Canada)","ror":"https://ror.org/00xdg8m59","country_code":"CA","type":"company","lineage":["https://openalex.org/I176714629"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Fang Hao","raw_affiliation_strings":["Bell Laboratroies"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bell Laboratroies","institution_ids":["https://openalex.org/I176714629"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108507325","display_name":"Murali Kodialam","orcid":null},"institutions":[{"id":"https://openalex.org/I176714629","display_name":"Bell (Canada)","ror":"https://ror.org/00xdg8m59","country_code":"CA","type":"company","lineage":["https://openalex.org/I176714629"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Murali Kodialam","raw_affiliation_strings":["Bell Laboratroies"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bell Laboratroies","institution_ids":["https://openalex.org/I176714629"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079816803","display_name":"T. V. Lakshman","orcid":null},"institutions":[{"id":"https://openalex.org/I176714629","display_name":"Bell (Canada)","ror":"https://ror.org/00xdg8m59","country_code":"CA","type":"company","lineage":["https://openalex.org/I176714629"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"T. V. Lakshman","raw_affiliation_strings":["Bell Laboratroies"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bell Laboratroies","institution_ids":["https://openalex.org/I176714629"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I176714629"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":68,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"277","last_page":"288"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11478","display_name":"Caching and Content Delivery","score":1.0,"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/T11478","display_name":"Caching and Content Delivery","score":1.0,"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/T12038","display_name":"Covalent Organic Framework Applications","score":0.9580000042915344,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9452999830245972,"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/bloom-filter","display_name":"Bloom filter","score":0.9844546914100647},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.7457261681556702},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7419021725654602},{"id":"https://openalex.org/keywords/false-positive-paradox","display_name":"False positive paradox","score":0.6711875200271606},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5800753831863403},{"id":"https://openalex.org/keywords/network-packet","display_name":"Network packet","score":0.575373649597168},{"id":"https://openalex.org/keywords/bit-array","display_name":"Bit array","score":0.540825605392456},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5260132551193237},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4522436857223511},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4079054296016693},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.16418859362602234},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.133540540933609},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.07277518510818481}],"concepts":[{"id":"https://openalex.org/C147224247","wikidata":"https://www.wikidata.org/wiki/Q885373","display_name":"Bloom filter","level":2,"score":0.9844546914100647},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.7457261681556702},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7419021725654602},{"id":"https://openalex.org/C64869954","wikidata":"https://www.wikidata.org/wiki/Q1859747","display_name":"False positive paradox","level":2,"score":0.6711875200271606},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5800753831863403},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"score":0.575373649597168},{"id":"https://openalex.org/C150807984","wikidata":"https://www.wikidata.org/wiki/Q1992074","display_name":"Bit array","level":3,"score":0.540825605392456},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5260132551193237},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4522436857223511},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4079054296016693},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.16418859362602234},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.133540540933609},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.07277518510818481},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C2777299769","wikidata":"https://www.wikidata.org/wiki/Q3707858","display_name":"Type (biology)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1254882.1254916","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1254882.1254916","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems","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":17,"referenced_works":["https://openalex.org/W42204834","https://openalex.org/W1709754610","https://openalex.org/W1977141583","https://openalex.org/W1993284846","https://openalex.org/W2069074882","https://openalex.org/W2081869611","https://openalex.org/W2103644027","https://openalex.org/W2115297415","https://openalex.org/W2123845384","https://openalex.org/W2126540423","https://openalex.org/W2154127540","https://openalex.org/W2156660460","https://openalex.org/W2164322063","https://openalex.org/W2295428206","https://openalex.org/W4206137901","https://openalex.org/W4251360957","https://openalex.org/W6671108768"],"related_works":["https://openalex.org/W2227807207","https://openalex.org/W2370014100","https://openalex.org/W2127784084","https://openalex.org/W2950578529","https://openalex.org/W2086416962","https://openalex.org/W4383553080","https://openalex.org/W4287264924","https://openalex.org/W3137108924","https://openalex.org/W1852009617","https://openalex.org/W2352764755"],"abstract_inverted_index":{"The":[0,78],"growing":[1],"importance":[2],"of":[3,27,43,81,113,137],"operations":[4],"such":[5],"as":[6,159,161],"packet-content":[7],"inspection,":[8],"packet":[9],"classification":[10],"based":[11],"on":[12],"non-IP":[13],"headers,":[14],"maintaining":[15],"flow-state,":[16],"etc.":[17],"has":[18],"led":[19],"to":[20,74,96,142],"increased":[21],"interest":[22],"in":[23,63,94,110,121,158,165],"the":[24,47,122,130,138,175],"networking":[25],"applications":[26],"Bloom":[28,33,51,123,169,186],"filters.":[29,170,187],"This":[30,99,133],"is":[31,49,84,100],"because":[32],"filters":[34,52],"provide":[35,54],"a":[36,55,85,104,111,143,162],"relatively":[37],"easy":[38],"method":[39,86,107],"for":[40,87,184],"hardware":[41],"implementation":[42],"set-membership":[44],"queries.":[45],"However,":[46],"tradeoff":[48],"that":[50,116,152,174],"only":[53],"probabilistic":[56],"test":[57],"and":[58],"membership":[59],"queries":[60],"can":[61,156],"result":[62,157],"false":[64,71,91,146],"positives.":[65],"Ideally,":[66],"we":[67],"would":[68,128],"like":[69],"this":[70,82,90,153],"positive":[72,92,147],"probability":[73,93],"be":[75,129],"very":[76],"low.":[77],"main":[79],"contribution":[80],"paper":[83],"significantly":[88],"reducing":[89],"comparison":[95],"existing":[97],"schemes.":[98],"done":[101],"by":[102],"developing":[103],"partitioned":[105],"hashing":[106],"which":[108],"results":[109],"choice":[112,155],"hash":[114],"functions":[115],"set":[117],"far":[118],"fewer":[119],"bits":[120],"filter":[124],"bit":[125,139],"vector":[126,140],"than":[127,180],"case":[131],"otherwise.":[132],"lower":[134,145],"fill":[135],"factor":[136],"translates":[141],"much":[144,160,178],"probability.":[148],"We":[149,171],"show":[150,173],"experimentally":[151],"improved":[154],"ten-fold":[163],"increase":[164],"accuracy":[166],"over":[167],"standard":[168],"also":[172],"scheme":[176],"performs":[177],"better":[179],"other":[181],"proposed":[182],"schemes":[183],"improving":[185]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":8},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":12},{"year":2012,"cited_by_count":8}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
