{"id":"https://openalex.org/W2156546584","doi":"https://doi.org/10.1109/icdm.2003.1250997","title":"K-d decision tree: an accelerated and memory efficient nearest neighbor classifier","display_name":"K-d decision tree: an accelerated and memory efficient nearest neighbor classifier","publication_year":2004,"publication_date":"2004-04-23","ids":{"openalex":"https://openalex.org/W2156546584","doi":"https://doi.org/10.1109/icdm.2003.1250997","mag":"2156546584"},"language":"en","primary_location":{"id":"doi:10.1109/icdm.2003.1250997","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm.2003.1250997","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Third IEEE International Conference on Data Mining","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/A5101693608","display_name":"Tomoyuki Shibata","orcid":"https://orcid.org/0000-0002-1633-0456"},"institutions":[{"id":"https://openalex.org/I75198481","display_name":"Wakayama University","ror":"https://ror.org/05wr49d48","country_code":"JP","type":"education","lineage":["https://openalex.org/I75198481"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"T. Shibata","raw_affiliation_strings":["Faculty of Systems Engineering, Wakayama University, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Systems Engineering, Wakayama University, Japan","institution_ids":["https://openalex.org/I75198481"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067332530","display_name":"T. Kato","orcid":"https://orcid.org/0000-0003-1061-5888"},"institutions":[{"id":"https://openalex.org/I75198481","display_name":"Wakayama University","ror":"https://ror.org/05wr49d48","country_code":"JP","type":"education","lineage":["https://openalex.org/I75198481"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"T. Kato","raw_affiliation_strings":["Faculty of Systems Engineering, Wakayama University, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Systems Engineering, Wakayama University, Japan","institution_ids":["https://openalex.org/I75198481"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085209922","display_name":"Takahiro Wada","orcid":"https://orcid.org/0000-0002-4518-8903"},"institutions":[{"id":"https://openalex.org/I75198481","display_name":"Wakayama University","ror":"https://ror.org/05wr49d48","country_code":"JP","type":"education","lineage":["https://openalex.org/I75198481"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"T. Wada","raw_affiliation_strings":["Faculty of Systems Engineering, Wakayama University, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Systems Engineering, Wakayama University, Japan","institution_ids":["https://openalex.org/I75198481"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.8504,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.88331893,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"641","last_page":"644"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9994000196456909,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9891999959945679,"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":0.9879999756813049,"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/computer-science","display_name":"Computer science","score":0.746527373790741},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.6938115358352661},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.6827614903450012},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6508312225341797},{"id":"https://openalex.org/keywords/voronoi-diagram","display_name":"Voronoi diagram","score":0.6310280561447144},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6038690805435181},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5631705522537231},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.5221496224403381},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4151320159435272},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32575762271881104},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1639588177204132}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.746527373790741},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.6938115358352661},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.6827614903450012},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6508312225341797},{"id":"https://openalex.org/C24881265","wikidata":"https://www.wikidata.org/wiki/Q757267","display_name":"Voronoi diagram","level":2,"score":0.6310280561447144},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6038690805435181},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5631705522537231},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.5221496224403381},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4151320159435272},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32575762271881104},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1639588177204132},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icdm.2003.1250997","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm.2003.1250997","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Third IEEE International Conference on Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.6200000047683716,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W100531594","https://openalex.org/W293526712","https://openalex.org/W1988790447","https://openalex.org/W1994410331","https://openalex.org/W2087434474","https://openalex.org/W2098631313","https://openalex.org/W2105306795","https://openalex.org/W2122111042","https://openalex.org/W2122389268","https://openalex.org/W2147169507","https://openalex.org/W2156909104","https://openalex.org/W2162583212","https://openalex.org/W2165558283","https://openalex.org/W2169351022","https://openalex.org/W2427881153","https://openalex.org/W4244238212","https://openalex.org/W6610461261"],"related_works":["https://openalex.org/W2148008870","https://openalex.org/W2381195555","https://openalex.org/W2368606575","https://openalex.org/W4246757943","https://openalex.org/W2132753198","https://openalex.org/W2369874856","https://openalex.org/W2182477562","https://openalex.org/W2792185758","https://openalex.org/W2787484455","https://openalex.org/W2119808169"],"abstract_inverted_index":{"Most":[0],"nearest":[1],"neighbor":[2],"(NN)":[3],"classifiers":[4,63],"employ":[5],"NN":[6,13,20,49,60],"search":[7,61],"algorithms":[8],"for":[9],"the":[10,19,65],"acceleration.":[11],"However,":[12],"classification":[14],"does":[15],"not":[16],"always":[17],"require":[18],"search.":[21],"Based":[22],"on":[23],"this":[24],"idea,":[25],"we":[26],"propose":[27],"a":[28],"novel":[29],"algorithm":[30],"named":[31],"k-d":[32],"decision":[33],"tree":[34],"(KDDT).":[35],"Since":[36],"KDDT":[37,55],"uses":[38],"Voronoi":[39],"condensed":[40],"prototypes,":[41],"it":[42],"is":[43,56],"less":[44],"memory":[45],"consuming":[46],"than":[47,59],"naive":[48],"classifiers.":[50],"We":[51],"have":[52],"confirmed":[53],"that":[54],"much":[57],"faster":[58],"based":[62],"through":[64],"comparative":[66],"experiment":[67],"(from":[68],"9":[69],"to":[70],"369":[71],"times":[72],"faster).":[73]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}