{"id":"https://openalex.org/W1992267648","doi":"https://doi.org/10.1145/1740592.1740595","title":"Efficient k-nearest neighbor searching in nonordered discrete data spaces","display_name":"Efficient k-nearest neighbor searching in nonordered discrete data spaces","publication_year":2010,"publication_date":"2010-05-01","ids":{"openalex":"https://openalex.org/W1992267648","doi":"https://doi.org/10.1145/1740592.1740595","mag":"1992267648"},"language":"en","primary_location":{"id":"doi:10.1145/1740592.1740595","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1740592.1740595","pdf_url":null,"source":{"id":"https://openalex.org/S4394735545","display_name":"ACM Transactions on Information Systems","issn_l":"1046-8188","issn":["1046-8188","1558-2868"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Information Systems","raw_type":"journal-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/A5062727152","display_name":"Dashiell Kolbe","orcid":null},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Dashiell Kolbe","raw_affiliation_strings":["Michigan State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Michigan State University","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103136845","display_name":"Qiang Zhu","orcid":"https://orcid.org/0000-0001-7094-9236"},"institutions":[{"id":"https://openalex.org/I4210130704","display_name":"University of Michigan\u2013Dearborn","ror":"https://ror.org/035wtm547","country_code":"US","type":"education","lineage":["https://openalex.org/I4210130704"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qiang Zhu","raw_affiliation_strings":["University of Michigan\u2014Dearborn"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Michigan\u2014Dearborn","institution_ids":["https://openalex.org/I4210130704"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059755229","display_name":"Sakti Pramanik","orcid":null},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sakti Pramanik","raw_affiliation_strings":["Michigan State University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Michigan State University","institution_ids":["https://openalex.org/I87216513"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5062727152"],"corresponding_institution_ids":["https://openalex.org/I87216513"],"apc_list":null,"apc_paid":null,"fwci":1.015,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.74779127,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"28","issue":"2","first_page":"1","last_page":"33"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9998000264167786,"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":0.9998000264167786,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9948999881744385,"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"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9782999753952026,"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/hamming-distance","display_name":"Hamming distance","score":0.7916550040245056},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.7552266120910645},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7550959587097168},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.7235540747642517},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.6997641921043396},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.6619672775268555},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5440913438796997},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5080430507659912},{"id":"https://openalex.org/keywords/hamming-space","display_name":"Hamming space","score":0.5079503655433655},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.5003068447113037},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42418813705444336},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.39650028944015503},{"id":"https://openalex.org/keywords/hamming-code","display_name":"Hamming code","score":0.39402538537979126},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35709840059280396},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23198425769805908}],"concepts":[{"id":"https://openalex.org/C193319292","wikidata":"https://www.wikidata.org/wiki/Q272172","display_name":"Hamming distance","level":2,"score":0.7916550040245056},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.7552266120910645},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7550959587097168},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.7235540747642517},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.6997641921043396},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.6619672775268555},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5440913438796997},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5080430507659912},{"id":"https://openalex.org/C2779494224","wikidata":"https://www.wikidata.org/wiki/Q5645799","display_name":"Hamming space","level":5,"score":0.5079503655433655},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.5003068447113037},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42418813705444336},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.39650028944015503},{"id":"https://openalex.org/C73150493","wikidata":"https://www.wikidata.org/wiki/Q853922","display_name":"Hamming code","level":4,"score":0.39402538537979126},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35709840059280396},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23198425769805908},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.0},{"id":"https://openalex.org/C157125643","wikidata":"https://www.wikidata.org/wiki/Q884707","display_name":"Block code","level":3,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1740592.1740595","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1740592.1740595","pdf_url":null,"source":{"id":"https://openalex.org/S4394735545","display_name":"ACM Transactions on Information Systems","issn_l":"1046-8188","issn":["1046-8188","1558-2868"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Information Systems","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.164.789","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.164.789","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cse.msu.edu/~pramanik/research/papers/papers/tois.10.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6237420211","display_name":null,"funder_award_id":"#IIS-0414576#IIS-04145940","funder_id":"https://openalex.org/F4320337389","funder_display_name":"Division of Information and Intelligent Systems"}],"funders":[{"id":"https://openalex.org/F4320337389","display_name":"Division of Information and Intelligent Systems","ror":"https://ror.org/053a2cp42"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1507589574","https://openalex.org/W1527356121","https://openalex.org/W1543003006","https://openalex.org/W1580166843","https://openalex.org/W1770616178","https://openalex.org/W1893622764","https://openalex.org/W1980073965","https://openalex.org/W2038044292","https://openalex.org/W2046144220","https://openalex.org/W2066799613","https://openalex.org/W2090900495","https://openalex.org/W2118269922","https://openalex.org/W2123837096","https://openalex.org/W2134627110","https://openalex.org/W2135631159","https://openalex.org/W2136145671","https://openalex.org/W2136572524","https://openalex.org/W2151135734","https://openalex.org/W2157092487","https://openalex.org/W2162990662","https://openalex.org/W2166050755","https://openalex.org/W2169413171","https://openalex.org/W2171129114","https://openalex.org/W2238624099","https://openalex.org/W2342204193","https://openalex.org/W3179878372","https://openalex.org/W7043153843"],"related_works":["https://openalex.org/W2371167013","https://openalex.org/W2036753599","https://openalex.org/W2182731056","https://openalex.org/W4212842756","https://openalex.org/W2613408642","https://openalex.org/W2772529866","https://openalex.org/W1993530675","https://openalex.org/W4235868261","https://openalex.org/W1519122282","https://openalex.org/W1503555387"],"abstract_inverted_index":{"Numerous":[0],"techniques":[1],"have":[2,119],"been":[3,25],"proposed":[4],"in":[5,18,27,34,45,65,81,129,183,187,194,202],"the":[6,28,59,70,74,93,110,134,143,153,204],"past":[7],"for":[8,30,92,115],"supporting":[9],"efficient":[10,182],"k":[11,15,31,42,78,122,178,185],"-nearest":[12],"neighbor":[13],"(":[14],"-NN)":[16],"queries":[17,33,44,124],"continuous":[19],"data":[20,38,172,192],"spaces.":[21],"Limited":[22],"work":[23],"has":[24],"reported":[26],"literature":[29],"-NN":[32,43,79,123,179],"a":[35,77,87,98,116,161],"nonordered":[36],"discrete":[37],"space":[39],"(NDDS).":[40],"Performing":[41],"an":[46,66,82],"NDDS":[47,83,139],"raises":[48],"new":[49,99,162],"challenges.":[50],"The":[51],"Hamming":[52,75,104],"distance":[53,60,100],"is":[54,157,181],"usually":[55],"used":[56,158],"to":[57,69,86,141,159],"measure":[58],"between":[61],"two":[62],"vectors":[63],"(objects)":[64],"NDDS.":[67],"Due":[68],"coarse":[71],"granularity":[72],"of":[73,90,112,136,145,152,206],"distance,":[76,106],"query":[80,94],"may":[84],"lead":[85],"high":[88],"degree":[89],"nondeterminism":[91],"result.":[95],"We":[96,118],"propose":[97],"measure,":[101],"called":[102],"Granularity-Enhanced":[103],"(GEH)":[105],"which":[107],"effectively":[108],"reduces":[109],"number":[111],"candidate":[113],"solutions":[114],"query.":[117],"also":[120],"implemented":[121],"using":[125],"multidimensional":[126,138],"database":[127],"indexing":[128],"NDDSs.":[130],"Further,":[131],"we":[132],"use":[133],"properties":[135],"our":[137,176,198],"index":[140],"derive":[142],"probability":[144,156],"encountering":[146],"valid":[147],"neighbors":[148],"within":[149],"specific":[150],"regions":[151],"index.":[154],"This":[155],"develop":[160],"search":[163],"ordering":[164],"heuristic.":[165],"Our":[166],"experiments":[167],"on":[168],"synthetic":[169],"and":[170,190,196],"genomic":[171],"sets":[173,193],"demonstrate":[174],"that":[175,197],"index-based":[177],"algorithm":[180],"finding":[184],"-NNs":[186],"both":[188],"uniform":[189],"nonuniform":[191],"NDDSs":[195],"heuristics":[199],"are":[200],"effective":[201],"improving":[203],"performance":[205],"such":[207],"queries.":[208]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-05-21T09:19:25.381259","created_date":"2025-10-10T00:00:00"}