{"id":"https://openalex.org/W2997010037","doi":"https://doi.org/10.18466/cbayarfbe.618964","title":"A Weighted Similarity Measure for k-Nearest Neighbors Algorithm","display_name":"A Weighted Similarity Measure for k-Nearest Neighbors Algorithm","publication_year":2019,"publication_date":"2019-12-30","ids":{"openalex":"https://openalex.org/W2997010037","doi":"https://doi.org/10.18466/cbayarfbe.618964","mag":"2997010037"},"language":"en","primary_location":{"id":"doi:10.18466/cbayarfbe.618964","doi":"https://doi.org/10.18466/cbayarfbe.618964","is_oa":true,"landing_page_url":"https://doi.org/10.18466/cbayarfbe.618964","pdf_url":"https://dergipark.org.tr/en/download/article-file/904927","source":{"id":"https://openalex.org/S2738732733","display_name":"Celal Bayar \u00dcniversitesi Fen Bilimleri Dergisi","issn_l":"1305-130X","issn":["1305-130X","1305-1385"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":["tr-dizin"],"host_organization":"https://openalex.org/P4310318361","host_organization_name":"Manisa Celal Bayar University","host_organization_lineage":["https://openalex.org/P4310318361"],"host_organization_lineage_names":["Manisa Celal Bayar University"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Celal Bayar \u00dcniversitesi Fen Bilimleri Dergisi","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://dergipark.org.tr/en/download/article-file/904927","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022985201","display_name":"Bergen Karabulut","orcid":"https://orcid.org/0000-0003-0755-1289","observed_orcids":["https://orcid.org/0000-0003-0755-1289"]},"institutions":[{"id":"https://openalex.org/I45642913","display_name":"K\u0131r\u0131kkale University","ror":"https://ror.org/01zhwwf82","country_code":"TR","type":"education","lineage":["https://openalex.org/I45642913"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Bergen KARABULUT","raw_affiliation_strings":["Dr., K\u0131r\u0131kkale University,"],"raw_orcid":"https://orcid.org/0000-0003-0755-1289","affiliations":[{"raw_affiliation_string":"Dr., K\u0131r\u0131kkale University,","institution_ids":["https://openalex.org/I45642913"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008930926","display_name":"G\u00fcven\u00e7 Arslan","orcid":"https://orcid.org/0000-0002-4770-2689","observed_orcids":["https://orcid.org/0000-0002-4770-2689","https://orcid.org/0009-0006-4019-6716"]},"institutions":[{"id":"https://openalex.org/I45642913","display_name":"K\u0131r\u0131kkale University","ror":"https://ror.org/01zhwwf82","country_code":"TR","type":"education","lineage":["https://openalex.org/I45642913"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"G\u00fcven\u00e7 ARSLAN","raw_affiliation_strings":["Dr., K\u0131r\u0131kkale University,"],"raw_orcid":"https://orcid.org/0000-0002-4770-2689","affiliations":[{"raw_affiliation_string":"Dr., K\u0131r\u0131kkale University,","institution_ids":["https://openalex.org/I45642913"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035708458","display_name":"Halil Murat \u00dcnver","orcid":"https://orcid.org/0000-0001-9959-8425","observed_orcids":["https://orcid.org/0000-0001-9959-8425"]},"institutions":[{"id":"https://openalex.org/I45642913","display_name":"K\u0131r\u0131kkale University","ror":"https://ror.org/01zhwwf82","country_code":"TR","type":"education","lineage":["https://openalex.org/I45642913"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Halil Murat \u00dcNVER","raw_affiliation_strings":["Dr., K\u0131r\u0131kkale University,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dr., K\u0131r\u0131kkale University,","institution_ids":["https://openalex.org/I45642913"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I45642913"],"apc_list":null,"apc_paid":null,"fwci":0.2216,"has_fulltext":true,"cited_by_count":18,"citation_normalized_percentile":{"value":0.68080845,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":"15","issue":"4","first_page":"393","last_page":"400"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.8690999746322632,"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"}},"topics":[{"id":"https://openalex.org/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.8690999746322632,"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"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.08579999953508377,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.013399999588727951,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/k-nearest-neighbors","display_name":"k-nearest neighbors","score":0.9490000009536743},{"id":"https://openalex.org/keywords/weighted-similarity","display_name":"weighted similarity","score":0.8830000162124634},{"id":"https://openalex.org/keywords/proximity-measures","display_name":"proximity measures","score":0.7639999985694885},{"id":"https://openalex.org/keywords/similarity-measures","display_name":"similarity measures","score":0.6420000195503235},{"id":"https://openalex.org/keywords/feature-weighting","display_name":"feature weighting","score":0.9129999876022339},{"id":"https://openalex.org/keywords/classification-accuracy","display_name":"classification accuracy","score":0.7609999775886536},{"id":"https://openalex.org/keywords/euclidean-distance-comparison","display_name":"Euclidean distance comparison","score":0.7870000004768372}],"concepts":[{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.7334303855895996},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.7298216819763184},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.7065308690071106},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.705990731716156},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.651307225227356},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5776265859603882},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5491523742675781},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49968600273132324},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45850545167922974},{"id":"https://openalex.org/C2639959","wikidata":"https://www.wikidata.org/wiki/Q1344778","display_name":"Distance measures","level":2,"score":0.44398200511932373},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43415719270706177},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4330507516860962},{"id":"https://openalex.org/C129782007","wikidata":"https://www.wikidata.org/wiki/Q162886","display_name":"Euclidean geometry","level":2,"score":0.41506046056747437},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.13928577303886414},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.18466/cbayarfbe.618964","doi":"https://doi.org/10.18466/cbayarfbe.618964","is_oa":true,"landing_page_url":"https://doi.org/10.18466/cbayarfbe.618964","pdf_url":"https://dergipark.org.tr/en/download/article-file/904927","source":{"id":"https://openalex.org/S2738732733","display_name":"Celal Bayar \u00dcniversitesi Fen Bilimleri Dergisi","issn_l":"1305-130X","issn":["1305-130X","1305-1385"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":["tr-dizin"],"host_organization":"https://openalex.org/P4310318361","host_organization_name":"Manisa Celal Bayar University","host_organization_lineage":["https://openalex.org/P4310318361"],"host_organization_lineage_names":["Manisa Celal Bayar University"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Celal Bayar \u00dcniversitesi Fen Bilimleri Dergisi","raw_type":"journal-article"},{"id":"pmh:oai:dergipark.org.tr:article/618964","doi":null,"is_oa":false,"landing_page_url":"https://dergipark.org.tr/tr/pub/cbayarfbe/issue/50875/618964","pdf_url":null,"source":{"id":"https://openalex.org/S4306401840","display_name":"DergiPark (Istanbul University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67581229","host_organization_name":"Istanbul University","host_organization_lineage":["https://openalex.org/I67581229"],"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":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.18466/cbayarfbe.618964","doi":"https://doi.org/10.18466/cbayarfbe.618964","is_oa":true,"landing_page_url":"https://doi.org/10.18466/cbayarfbe.618964","pdf_url":"https://dergipark.org.tr/en/download/article-file/904927","source":{"id":"https://openalex.org/S2738732733","display_name":"Celal Bayar \u00dcniversitesi Fen Bilimleri Dergisi","issn_l":"1305-130X","issn":["1305-130X","1305-1385"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":["tr-dizin"],"host_organization":"https://openalex.org/P4310318361","host_organization_name":"Manisa Celal Bayar University","host_organization_lineage":["https://openalex.org/P4310318361"],"host_organization_lineage_names":["Manisa Celal Bayar University"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Celal Bayar \u00dcniversitesi Fen Bilimleri Dergisi","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2997010037.pdf","grobid_xml":"https://content.openalex.org/works/W2997010037.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W1901616594","https://openalex.org/W1919024784","https://openalex.org/W2092777731","https://openalex.org/W2101285186","https://openalex.org/W2113680389","https://openalex.org/W2332271625","https://openalex.org/W2510620627","https://openalex.org/W2560633845","https://openalex.org/W2560937854","https://openalex.org/W2561539065","https://openalex.org/W2753683282","https://openalex.org/W2793284597","https://openalex.org/W2796884049","https://openalex.org/W2802363156","https://openalex.org/W2803808916","https://openalex.org/W3098996042"],"related_works":["https://openalex.org/W2376685399","https://openalex.org/W4409968655","https://openalex.org/W3205187516","https://openalex.org/W3215324699","https://openalex.org/W2075760253","https://openalex.org/W2763573675","https://openalex.org/W4205661764","https://openalex.org/W2381208607","https://openalex.org/W2023878529","https://openalex.org/W3095451592"],"abstract_inverted_index":{"One":[0,48],"of":[1,45,49,74,82,90,122,171,223,232],"the":[2,43,61,72,75,80,88,91,98,114,120,128,131,158,164,169,183,197,221,229],"most":[3],"important":[4],"problems":[5],"in":[6,13,26,71,113,130],"machine":[7],"learning,":[8],"which":[9,105],"has":[10],"gained":[11],"importance":[12],"recent":[14],"years,":[15],"is":[16,23,31,51,64,155],"classification.":[17],"The":[18,152],"k-nearest":[19],"neighbors":[20],"(kNN)":[21],"algorithm":[22,103,154,200,211],"widely":[24],"used":[25,66],"classification":[27,191,204,230],"problem":[28],"because":[29],"it":[30,118,135],"a":[32,68,107,143],"simple":[33],"and":[34,125,141],"effective":[35],"method.":[36],"However,":[37],"there":[38],"are":[39,175],"several":[40],"factors":[41],"affecting":[42],"performance":[44,89,170],"kNN":[46,115,160,233],"algorithm.":[47,116,234],"them":[50],"determining":[52],"an":[53],"appropriate":[54],"proximity":[55,69,84,111,150,225],"(distance":[56],"or":[57],"similarity)":[58],"measure.":[59,151],"Although":[60],"Euclidean":[62,165],"distance":[63],"often":[65],"as":[67,110,149],"measure":[70,112],"application":[73],"kNN,":[76],"studies":[77],"show":[78,195],"that":[79,196,220],"use":[81,106,148,222],"different":[83,179,224],"measures":[85,226],"can":[86,201,227],"improve":[87],"kNN.":[92],"In":[93,216],"this":[94,209],"study,":[95],"we":[96,218],"propose":[97],"Weighted":[99],"Similarity":[100],"k-Nearest":[101],"Neighbors":[102],"(WS-kNN)":[104],"weighted":[108,144],"similarity":[109,126,145],"Firstly,":[117],"calculates":[119],"weight":[121],"each":[123],"attribute":[124,139],"between":[127],"instances":[129],"dataset.":[132],"And":[133],"then,":[134],"weights":[136,140],"similarities":[137],"by":[138,190],"creates":[142],"matrix":[146],"to":[147],"proposed":[153,198],"compared":[156],"with":[157],"classical":[159],"method":[161],"based":[162],"on":[163,177],"distance.":[166],"To":[167],"verify":[168],"our":[172],"algorithm,":[173],"experiments":[174],"made":[176],"10":[178],"real-life":[180],"datasets":[181],"from":[182],"UCI":[184],"(UC":[185],"Irvine":[186],"Machine":[187],"Learning":[188],"Repository)":[189],"accuracy.":[192,205],"Experimental":[193],"results":[194],"WS-kNN":[199],"achieve":[202],"comparative":[203],"For":[206],"some":[207],"datasets,":[208],"new":[210],"gives":[212],"highly":[213],"good":[214],"results.":[215],"addition,":[217],"demonstrated":[219],"affect":[228],"accuracy":[231]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2026-11-09T13:22:03.289127","created_date":"2020-01-10T00:00:00"}
