{"id":"https://openalex.org/W2907352566","doi":"https://doi.org/10.1109/bigdata.2018.8622307","title":"K-nearest Neighbor Search by Random Projection Forests","display_name":"K-nearest Neighbor Search by Random Projection Forests","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2907352566","doi":"https://doi.org/10.1109/bigdata.2018.8622307","mag":"2907352566"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2018.8622307","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2018.8622307","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1812.11689","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060954578","display_name":"Donghui Yan","orcid":"https://orcid.org/0000-0002-5131-1509"},"institutions":[{"id":"https://openalex.org/I100633361","display_name":"University of Massachusetts Dartmouth","ror":"https://ror.org/00fzmm222","country_code":"US","type":"education","lineage":["https://openalex.org/I100633361"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Donghui Yan","raw_affiliation_strings":["Department of Mathematics and Program in Data Science, University of Massachusetts, Dartmouth, USA"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Program in Data Science, University of Massachusetts, Dartmouth, USA","institution_ids":["https://openalex.org/I100633361"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108672281","display_name":"Yingjie Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I100633361","display_name":"University of Massachusetts Dartmouth","ror":"https://ror.org/00fzmm222","country_code":"US","type":"education","lineage":["https://openalex.org/I100633361"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yingjie Wang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Massachusetts, Dartmouth, MA 02747, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Massachusetts, Dartmouth, MA 02747, USA","institution_ids":["https://openalex.org/I100633361"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100346197","display_name":"Jin Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I100633361","display_name":"University of Massachusetts Dartmouth","ror":"https://ror.org/00fzmm222","country_code":"US","type":"education","lineage":["https://openalex.org/I100633361"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jin Wang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Massachusetts, Dartmouth, MA 02747, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Massachusetts, Dartmouth, MA 02747, USA","institution_ids":["https://openalex.org/I100633361"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100419573","display_name":"Honggang Wang","orcid":"https://orcid.org/0000-0001-9475-2630"},"institutions":[{"id":"https://openalex.org/I100633361","display_name":"University of Massachusetts Dartmouth","ror":"https://ror.org/00fzmm222","country_code":"US","type":"education","lineage":["https://openalex.org/I100633361"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Honggang Wang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Massachusetts, Dartmouth, MA 02747, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Massachusetts, Dartmouth, MA 02747, USA","institution_ids":["https://openalex.org/I100633361"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101993204","display_name":"Zhenpeng Li","orcid":"https://orcid.org/0000-0001-7908-358X"},"institutions":[{"id":"https://openalex.org/I6593398","display_name":"Dali University","ror":"https://ror.org/02y7rck89","country_code":"CN","type":"education","lineage":["https://openalex.org/I6593398"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenpeng Li","raw_affiliation_strings":["Department of Applied Statistics, Dali University, Yunnan, China"],"affiliations":[{"raw_affiliation_string":"Department of Applied Statistics, Dali University, Yunnan, China","institution_ids":["https://openalex.org/I6593398"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5060954578"],"corresponding_institution_ids":["https://openalex.org/I100633361"],"apc_list":null,"apc_paid":null,"fwci":0.8292,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.74939586,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"4775","last_page":"4781"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9980999827384949,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.9775999784469604,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.7709402441978455},{"id":"https://openalex.org/keywords/random-projection","display_name":"Random projection","score":0.7579032182693481},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.6464371085166931},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.59471195936203},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.580041229724884},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5705598592758179},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5008172988891602},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.4677676558494568},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.46443161368370056},{"id":"https://openalex.org/keywords/exponential-growth","display_name":"Exponential growth","score":0.45758381485939026},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45137539505958557},{"id":"https://openalex.org/keywords/best-bin-first","display_name":"Best bin first","score":0.44823262095451355},{"id":"https://openalex.org/keywords/nearest-neighbor-chain-algorithm","display_name":"Nearest-neighbor chain algorithm","score":0.44621214270591736},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.435067355632782},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43338701128959656},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3979516625404358},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34304702281951904},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.12845072150230408},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.10243692994117737}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7709402441978455},{"id":"https://openalex.org/C2777036070","wikidata":"https://www.wikidata.org/wiki/Q18393452","display_name":"Random projection","level":2,"score":0.7579032182693481},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.6464371085166931},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.59471195936203},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.580041229724884},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5705598592758179},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5008172988891602},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.4677676558494568},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.46443161368370056},{"id":"https://openalex.org/C75235859","wikidata":"https://www.wikidata.org/wiki/Q582659","display_name":"Exponential growth","level":2,"score":0.45758381485939026},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45137539505958557},{"id":"https://openalex.org/C161986146","wikidata":"https://www.wikidata.org/wiki/Q4896845","display_name":"Best bin first","level":3,"score":0.44823262095451355},{"id":"https://openalex.org/C102164700","wikidata":"https://www.wikidata.org/wiki/Q17162702","display_name":"Nearest-neighbor chain algorithm","level":5,"score":0.44621214270591736},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.435067355632782},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43338701128959656},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3979516625404358},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34304702281951904},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.12845072150230408},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.10243692994117737},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bigdata.2018.8622307","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2018.8622307","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1812.11689","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1812.11689","pdf_url":"https://arxiv.org/pdf/1812.11689","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1812.11689","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1812.11689","pdf_url":"https://arxiv.org/pdf/1812.11689","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Life in Land","score":0.7200000286102295,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2907352566.pdf","grobid_xml":"https://content.openalex.org/works/W2907352566.grobid-xml"},"referenced_works_count":62,"referenced_works":["https://openalex.org/W1509388613","https://openalex.org/W1513618424","https://openalex.org/W1530232915","https://openalex.org/W1549123574","https://openalex.org/W1565486828","https://openalex.org/W1670132599","https://openalex.org/W1832247271","https://openalex.org/W1869127374","https://openalex.org/W1985879444","https://openalex.org/W1998951954","https://openalex.org/W2024668293","https://openalex.org/W2038276547","https://openalex.org/W2045263322","https://openalex.org/W2050913223","https://openalex.org/W2070276049","https://openalex.org/W2073214884","https://openalex.org/W2086504823","https://openalex.org/W2097921974","https://openalex.org/W2099253838","https://openalex.org/W2105234758","https://openalex.org/W2110026675","https://openalex.org/W2112076978","https://openalex.org/W2115854352","https://openalex.org/W2116810533","https://openalex.org/W2118123209","https://openalex.org/W2122646361","https://openalex.org/W2129281431","https://openalex.org/W2133296809","https://openalex.org/W2134370969","https://openalex.org/W2151518054","https://openalex.org/W2157169955","https://openalex.org/W2165558283","https://openalex.org/W2170605888","https://openalex.org/W2213673037","https://openalex.org/W2341251094","https://openalex.org/W2403927937","https://openalex.org/W2545201814","https://openalex.org/W2814803617","https://openalex.org/W2885659414","https://openalex.org/W2911964244","https://openalex.org/W2962712507","https://openalex.org/W2962923175","https://openalex.org/W2964216716","https://openalex.org/W3037609093","https://openalex.org/W3101568187","https://openalex.org/W3101570666","https://openalex.org/W3105198801","https://openalex.org/W3195149063","https://openalex.org/W3208688400","https://openalex.org/W4212883601","https://openalex.org/W4253461361","https://openalex.org/W6631860268","https://openalex.org/W6636883489","https://openalex.org/W6638865775","https://openalex.org/W6639153832","https://openalex.org/W6674878074","https://openalex.org/W6676769703","https://openalex.org/W6683389101","https://openalex.org/W6684723771","https://openalex.org/W6713637495","https://openalex.org/W6756516108","https://openalex.org/W7064111672"],"related_works":["https://openalex.org/W2182477562","https://openalex.org/W2245581955","https://openalex.org/W2169618946","https://openalex.org/W2375128115","https://openalex.org/W2011582495","https://openalex.org/W1558159560","https://openalex.org/W2148008870","https://openalex.org/W2381195555","https://openalex.org/W325985789","https://openalex.org/W2143679819"],"abstract_inverted_index":{"K-nearest":[0],"neighbor":[1],"(kNN)":[2],"search":[3],"has":[4,92],"wide":[5],"applications":[6],"in":[7,72,77,87,107,171],"many":[8,17],"areas,":[9],"including":[10],"data":[11],"mining,":[12],"machine":[13],"learning,":[14],"statistics":[15],"and":[16,27,83,176],"applied":[18],"domains.":[19],"Inspired":[20],"by":[21,45,135,149],"the":[22,28,78,88,114,125,137,141,155,166,172,180],"success":[23],"of":[24,30,51,62,74,81,85,101,127,140,168,174],"ensemble":[25,50,99,150,156],"methods":[26],"flexibility":[29],"tree-based":[31],"methodology,":[32],"we":[33],"propose":[34],"random":[35,52,65,151,169],"projection":[36,53,152],"forests,":[37],"rpForests,":[38],"for":[39],"kNN":[40,89],"search.":[41],"rpForests":[42,67,91,102],"finds":[43],"kNNs":[44,82],"aggregating":[46],"results":[47],"from":[48],"an":[49],"trees":[54,153],"with":[55],"each":[56],"constructed":[57],"recursively":[58],"through":[59],"a":[60,69,93],"series":[61],"carefully":[63],"chosen":[64],"projections.":[66],"achieves":[68],"remarkable":[70],"accuracy":[71],"terms":[73],"fast":[75],"decay":[76,139],"missing":[79],"rate":[80],"that":[84,143,179],"discrepancy":[86],"distances.":[90],"very":[94],"low":[95],"computational":[96],"complexity.":[97],"The":[98],"nature":[100],"makes":[103],"it":[104],"easily":[105],"run":[106],"parallel":[108],"on":[109],"multicore":[110],"or":[111,129],"clustered":[112],"computers;":[113],"running":[115],"time":[116],"is":[117,182],"expected":[118],"to":[119,124,164],"be":[120,147,162],"nearly":[121],"inversely":[122],"proportional":[123],"number":[126],"cores":[128],"machines.":[130],"We":[131],"give":[132],"theoretical":[133],"insights":[134],"showing":[136],"exponential":[138],"probability":[142],"neighboring":[144],"points":[145],"would":[146],"separated":[148],"when":[154],"size":[157],"increases.":[158],"Our":[159],"theory":[160],"can":[161],"used":[163],"refine":[165],"choice":[167],"projections":[170],"growth":[173],"trees,":[175],"experiments":[177],"show":[178],"effect":[181],"remarkable.":[183]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}