{"id":"https://openalex.org/W2009036829","doi":"https://doi.org/10.1109/icde.2008.4497520","title":"A Fast Similarity Join Algorithm Using Graphics Processing Units","display_name":"A Fast Similarity Join Algorithm Using Graphics Processing Units","publication_year":2008,"publication_date":"2008-04-01","ids":{"openalex":"https://openalex.org/W2009036829","doi":"https://doi.org/10.1109/icde.2008.4497520","mag":"2009036829"},"language":"en","primary_location":{"id":"doi:10.1109/icde.2008.4497520","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde.2008.4497520","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE 24th International Conference on Data Engineering","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/A5103833167","display_name":"Michael D. Lieberman","orcid":null},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael D. Lieberman","raw_affiliation_strings":["Department of Computer Science Center for Automation Research, Institute for Advanced Computer Studies University of Maryland, College Park, MD, USA","Dept. of Comput. Sci., Maryland Univ., College Park, MD"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science Center for Automation Research, Institute for Advanced Computer Studies University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"Dept. of Comput. Sci., Maryland Univ., College Park, MD","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050157577","display_name":"Jagan Sankaranarayanan","orcid":"https://orcid.org/0009-0006-0369-816X"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jagan Sankaranarayanan","raw_affiliation_strings":["Department of Computer Science Center for Automation Research, Institute for Advanced Computer Studies University of Maryland, College Park, MD, USA","Dept. of Comput. Sci., Maryland Univ., College Park, MD"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science Center for Automation Research, Institute for Advanced Computer Studies University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"Dept. of Comput. Sci., Maryland Univ., College Park, MD","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087437068","display_name":"Hanan Samet","orcid":"https://orcid.org/0000-0001-8230-0653"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hanan Samet","raw_affiliation_strings":["Department of Computer Science Center for Automation Research, Institute for Advanced Computer Studies University of Maryland, College Park, MD, USA","Dept. of Comput. Sci., Maryland Univ., College Park, MD"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science Center for Automation Research, Institute for Advanced Computer Studies University of Maryland, College Park, MD, USA","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"Dept. of Comput. Sci., Maryland Univ., College Park, MD","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":126,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1111","last_page":"1120"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9994000196456909,"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/T11106","display_name":"Data Management and Algorithms","score":0.9994000196456909,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9991000294685364,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9984999895095825,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/joins","display_name":"Joins","score":0.844096302986145},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7461563348770142},{"id":"https://openalex.org/keywords/join","display_name":"Join (topology)","score":0.7036606073379517},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.7004401683807373},{"id":"https://openalex.org/keywords/graphics-processing-unit","display_name":"Graphics processing unit","score":0.5575613379478455},{"id":"https://openalex.org/keywords/sort","display_name":"sort","score":0.5435161590576172},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5274071097373962},{"id":"https://openalex.org/keywords/sorting","display_name":"Sorting","score":0.5141251683235168},{"id":"https://openalex.org/keywords/hash-join","display_name":"Hash join","score":0.4986546039581299},{"id":"https://openalex.org/keywords/graphics","display_name":"Graphics","score":0.47142499685287476},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.46375396847724915},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46352890133857727},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41885846853256226},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.35193705558776855},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3339548707008362},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3241649866104126},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.19450163841247559},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16460585594177246},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.15237239003181458},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.1219712495803833},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09326836466789246}],"concepts":[{"id":"https://openalex.org/C2778692605","wikidata":"https://www.wikidata.org/wiki/Q4041866","display_name":"Joins","level":2,"score":0.844096302986145},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7461563348770142},{"id":"https://openalex.org/C2776124973","wikidata":"https://www.wikidata.org/wiki/Q3183033","display_name":"Join (topology)","level":2,"score":0.7036606073379517},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.7004401683807373},{"id":"https://openalex.org/C2779851693","wikidata":"https://www.wikidata.org/wiki/Q183484","display_name":"Graphics processing unit","level":2,"score":0.5575613379478455},{"id":"https://openalex.org/C88548561","wikidata":"https://www.wikidata.org/wiki/Q347599","display_name":"sort","level":2,"score":0.5435161590576172},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5274071097373962},{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.5141251683235168},{"id":"https://openalex.org/C188805328","wikidata":"https://www.wikidata.org/wiki/Q4060691","display_name":"Hash join","level":3,"score":0.4986546039581299},{"id":"https://openalex.org/C21442007","wikidata":"https://www.wikidata.org/wiki/Q1027879","display_name":"Graphics","level":2,"score":0.47142499685287476},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.46375396847724915},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46352890133857727},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41885846853256226},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.35193705558776855},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3339548707008362},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3241649866104126},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.19450163841247559},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16460585594177246},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.15237239003181458},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.1219712495803833},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09326836466789246},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icde.2008.4497520","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde.2008.4497520","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE 24th International Conference on Data Engineering","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.119.9965","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.119.9965","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.umiacs.umd.edu/~hjs/pubs/GPUicde2008.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.4000000059604645}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W194498636","https://openalex.org/W772774554","https://openalex.org/W1492783156","https://openalex.org/W1497953515","https://openalex.org/W1502916507","https://openalex.org/W1548638602","https://openalex.org/W1575124099","https://openalex.org/W1579838312","https://openalex.org/W1595783387","https://openalex.org/W1770825568","https://openalex.org/W1963704089","https://openalex.org/W1976219590","https://openalex.org/W1998512964","https://openalex.org/W2011415853","https://openalex.org/W2024409132","https://openalex.org/W2045848492","https://openalex.org/W2052050139","https://openalex.org/W2054468361","https://openalex.org/W2058903936","https://openalex.org/W2110286878","https://openalex.org/W2114640218","https://openalex.org/W2133542527","https://openalex.org/W2135346934","https://openalex.org/W2141389982","https://openalex.org/W2146476558","https://openalex.org/W2154852471","https://openalex.org/W2169893912","https://openalex.org/W2205071250","https://openalex.org/W2283267175","https://openalex.org/W2769954494","https://openalex.org/W4240774490","https://openalex.org/W6629254060","https://openalex.org/W6629956336","https://openalex.org/W6635487903","https://openalex.org/W6676640400","https://openalex.org/W6680874277","https://openalex.org/W6682914382"],"related_works":["https://openalex.org/W2393491644","https://openalex.org/W650102067","https://openalex.org/W4206577045","https://openalex.org/W1550806730","https://openalex.org/W2589740103","https://openalex.org/W2172084996","https://openalex.org/W1501284171","https://openalex.org/W2397450670","https://openalex.org/W1966967794","https://openalex.org/W3086237447"],"abstract_inverted_index":{"A":[0,4,58],"similarity":[1,60,105,198,215],"join":[2,61,106,216],"operation":[3,107],"BOWTIE":[5],"<sub":[6],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[7],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">epsiv</sub>":[8],"B":[9,16],"takes":[10],"two":[11,100,212],"sets":[12],"of":[13,26,48,95,121,126,142,155,157],"points":[14,27],"A,":[15],"and":[17,23,55,78,93,174,187,204],"a":[18,46,70,104,109,119,131,182],"value":[19],"epsiv":[20],"isin":[21,29,31],"Ropf,":[22],"outputs":[24],"pairs":[25,166],"p":[28,141,169],"A,q":[30],"B,":[32],"such":[33,50,89],"that":[34,67,193,205],"the":[35,91,117,143,158,165],"distance":[36],"D(p,":[37],"q)":[38],"les":[39],"epsiv.":[40],"Similarity":[41],"joins":[42,199],"find":[43],"use":[44],"in":[45,146,167,200],"variety":[47],"fields,":[49],"as":[51,90,108],"clustering,":[52],"text":[53],"mining,":[54],"multimedia":[56],"databases.":[57],"novel":[59],"algorithm":[62],"called":[63],"LSS":[64,97,137,177,194],"is":[65,178,195],"presented":[66],"executes":[68],"on":[69,116,124],"graphics":[71],"processing":[72],"unit":[73],"(GPU),":[74],"exploiting":[75],"its":[76,127],"parallelism":[77],"high":[79],"data":[80,87],"throughput.":[81],"As":[82],"GPUs":[83],"only":[84],"allow":[85],"simple":[86],"operations":[88,101],"sorting":[92],"searching":[94],"arrays,":[96],"uses":[98],"these":[99],"to":[102,162,180],"cast":[103],"GPU":[110,133],"sort-and-search":[111],"problem.":[112],"It":[113],"first":[114],"creates,":[115],"fly,":[118],"set":[120],"space-filling":[122,159],"curves":[123,160],"one":[125,156],"input":[128],"datasets,":[129,203],"using":[130],"parallel":[132],"sort":[134],"routine.":[135],"Next,":[136],"processes":[138],"each":[139,149],"point":[140],"other":[144],"dataset":[145],"parallel.":[147],"For":[148],"p,":[150],"it":[151,206],"searches":[152],"an":[153],"interval":[154],"guaranteed":[161],"contain":[163],"all":[164],"which":[168],"participates.":[170],"Using":[171],"extensive":[172],"theoretical":[173],"experimental":[175],"analysis,":[176],"shown":[179],"offer":[181],"good":[183],"balance":[184],"between":[185],"time":[186],"work":[188],"efficiency.":[189],"Experimental":[190],"results":[191],"demonstrate":[192],"suitable":[196],"for":[197],"large":[201],"high-dimensional":[202],"performs":[207],"well":[208],"when":[209],"compared":[210],"against":[211],"existing":[213],"prominent":[214],"methods.":[217]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":7},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":14},{"year":2012,"cited_by_count":15}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}