{"id":"https://openalex.org/W2011539065","doi":"https://doi.org/10.1109/icde.2014.6816728","title":"Near neighbor join","display_name":"Near neighbor join","publication_year":2014,"publication_date":"2014-03-01","ids":{"openalex":"https://openalex.org/W2011539065","doi":"https://doi.org/10.1109/icde.2014.6816728","mag":"2011539065"},"language":"en","primary_location":{"id":"doi:10.1109/icde.2014.6816728","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde.2014.6816728","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE 30th International Conference on Data Engineering","raw_type":"proceedings-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/A5026098275","display_name":"Herald Kllapi","orcid":null},"institutions":[{"id":"https://openalex.org/I200777214","display_name":"National and Kapodistrian University of Athens","ror":"https://ror.org/04gnjpq42","country_code":"GR","type":"education","lineage":["https://openalex.org/I200777214"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Herald Kllapi","raw_affiliation_strings":["Dept. of Informatics and Telecommunications, University of Athens Panepistimiopolis, Athens, Greece","Department of Informatics and Telecommunications, University of Athens, Panepistimiopolis, Ilissia 15784, Greece#TAB#"],"affiliations":[{"raw_affiliation_string":"Dept. of Informatics and Telecommunications, University of Athens Panepistimiopolis, Athens, Greece","institution_ids":["https://openalex.org/I200777214"]},{"raw_affiliation_string":"Department of Informatics and Telecommunications, University of Athens, Panepistimiopolis, Ilissia 15784, Greece#TAB#","institution_ids":["https://openalex.org/I200777214"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112448435","display_name":"Boulos Harb","orcid":null},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Boulos Harb","raw_affiliation_strings":["Google Research, New York, NY, USA","Google Research, 75 Ninth Avenue, New York, 10011, USA"],"affiliations":[{"raw_affiliation_string":"Google Research, New York, NY, USA","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"Google Research, 75 Ninth Avenue, New York, 10011, USA","institution_ids":["https://openalex.org/I1291425158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043275971","display_name":"Cong Yu","orcid":"https://orcid.org/0000-0001-7331-2345"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cong Yu","raw_affiliation_strings":["Google Research, New York, NY, USA","Google Research, 75 Ninth Avenue, New York, 10011, USA"],"affiliations":[{"raw_affiliation_string":"Google Research, New York, NY, USA","institution_ids":["https://openalex.org/I1291425158"]},{"raw_affiliation_string":"Google Research, 75 Ninth Avenue, New York, 10011, USA","institution_ids":["https://openalex.org/I1291425158"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5026098275"],"corresponding_institution_ids":["https://openalex.org/I200777214"],"apc_list":null,"apc_paid":null,"fwci":1.7469,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.84682599,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1120","last_page":"1131"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9993000030517578,"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":0.9993000030517578,"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/T11719","display_name":"Data Quality and Management","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/join","display_name":"Join (topology)","score":0.9388048648834229},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.7525155544281006},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7390176057815552},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.512442409992218},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4986906051635742},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.48500534892082214},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4428270757198334},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.42847463488578796},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33275195956230164},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2407226860523224},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.1616915464401245},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.12952548265457153},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1267559826374054},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10422655940055847}],"concepts":[{"id":"https://openalex.org/C2776124973","wikidata":"https://www.wikidata.org/wiki/Q3183033","display_name":"Join (topology)","level":2,"score":0.9388048648834229},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.7525155544281006},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7390176057815552},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.512442409992218},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4986906051635742},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.48500534892082214},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4428270757198334},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.42847463488578796},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33275195956230164},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2407226860523224},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.1616915464401245},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.12952548265457153},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1267559826374054},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10422655940055847},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icde.2014.6816728","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde.2014.6816728","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE 30th International Conference on Data Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1502916507","https://openalex.org/W1509426348","https://openalex.org/W1566397396","https://openalex.org/W1976219590","https://openalex.org/W1978924650","https://openalex.org/W1979666709","https://openalex.org/W1987403831","https://openalex.org/W1987777228","https://openalex.org/W1994655805","https://openalex.org/W2000482994","https://openalex.org/W2029960028","https://openalex.org/W2049003051","https://openalex.org/W2060765209","https://openalex.org/W2061601738","https://openalex.org/W2096598900","https://openalex.org/W2097184821","https://openalex.org/W2097673300","https://openalex.org/W2097776316","https://openalex.org/W2098935637","https://openalex.org/W2100344784","https://openalex.org/W2100369465","https://openalex.org/W2104599107","https://openalex.org/W2105436061","https://openalex.org/W2115500858","https://openalex.org/W2119528150","https://openalex.org/W2119714163","https://openalex.org/W2121516976","https://openalex.org/W2121713321","https://openalex.org/W2130258443","https://openalex.org/W2132399973","https://openalex.org/W2137139422","https://openalex.org/W2150916025","https://openalex.org/W2151930506","https://openalex.org/W2154879298","https://openalex.org/W2157092487","https://openalex.org/W2157234796","https://openalex.org/W2168649524","https://openalex.org/W2173213060","https://openalex.org/W4241298546","https://openalex.org/W4251805162","https://openalex.org/W6629956336","https://openalex.org/W6633772308","https://openalex.org/W6674576723","https://openalex.org/W6674908998","https://openalex.org/W6678291700","https://openalex.org/W6682969285"],"related_works":["https://openalex.org/W4205996836","https://openalex.org/W2151692181","https://openalex.org/W4392498349","https://openalex.org/W2093960938","https://openalex.org/W3214148052","https://openalex.org/W4392216655","https://openalex.org/W2807741550","https://openalex.org/W794462722","https://openalex.org/W2029625042","https://openalex.org/W4256664196"],"abstract_inverted_index":{"An":[0],"increasing":[1],"number":[2,114],"of":[3,45,63,73,95,115,180,183,185],"Web":[4],"applications":[5],"such":[6],"as":[7],"friends":[8],"recommendation":[9],"depend":[10],"on":[11,37,70,100],"the":[12,42,49,59,71,74,77,93,102,145,160],"ability":[13],"to":[14,34,55],"join":[15,26,40,78,83,103,111,119,139,161],"objects":[16,46,50,75,116,186],"at":[17,155],"scale.":[18],"The":[19,61],"traditional":[20],"approach":[21,67,135],"taken":[22],"is":[23,33,178,200],"nearest":[24],"neighbor":[25,138],"(also":[27],"called":[28,136],"similarity":[29],"join),":[30],"whose":[31],"goal":[32],"find,":[35],"based":[36],"a":[38,52,107,124,132,171],"given":[39],"function,":[41],"closest":[43,146],"set":[44],"or":[47],"all":[48],"within":[51],"distance":[53],"threshold":[54],"each":[56],"object":[57],"in":[58],"input.":[60],"scalability":[62],"techniques":[64],"utilizing":[65],"this":[66,128],"often":[68],"depends":[69],"characteristics":[72],"and":[76,88,151,169,202],"function.":[79],"However,":[80],"many":[81],"real-world":[82,194],"functions":[84,120,162],"are":[85,163],"intricately":[86],"engineered":[87],"constantly":[89],"evolving,":[90],"which":[91],"makes":[92],"design":[94,168],"white-box":[96],"methods":[97],"that":[98,109,177,198],"rely":[99],"understanding":[101],"function":[104],"impractical.":[105],"Finding":[106],"technique":[108],"can":[110,152],"extremely":[112,156],"large":[113,157,195],"with":[117],"complex":[118,188],"has":[121],"always":[122],"been":[123],"tough":[125],"challenge.":[126],"In":[127,165],"paper,":[129],"we":[130,167,174],"propose":[131],"practical":[133],"alternative":[134],"near":[137],"that,":[140],"although":[141],"does":[142],"not":[143],"find":[144],"neighbors,":[147,150],"finds":[148],"close":[149],"do":[153],"so":[154],"scale":[158],"when":[159],"complex.":[164],"particular,":[166],"implement":[170],"super-scalable":[172],"system":[173],"name":[175],"SAJ":[176,199],"capable":[179],"best-effort":[181],"joining":[182],"billions":[184],"for":[187],"functions.":[189],"Extensive":[190],"experimental":[191],"analysis":[192],"over":[193],"datasets":[196],"shows":[197],"scalable":[201],"generates":[203],"good":[204],"results.":[205]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2016-06-24T00:00:00"}
