{"id":"https://openalex.org/W4307346205","doi":"https://doi.org/10.1145/3558819.3565209","title":"An Improved k-Nearest Centroid Neighbor Classification Method for Incomplete Data","display_name":"An Improved k-Nearest Centroid Neighbor Classification Method for Incomplete Data","publication_year":2022,"publication_date":"2022-09-23","ids":{"openalex":"https://openalex.org/W4307346205","doi":"https://doi.org/10.1145/3558819.3565209"},"language":"en","primary_location":{"id":"doi:10.1145/3558819.3565209","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3558819.3565209","pdf_url":null,"source":{"id":"https://openalex.org/S4363608855","display_name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","issn_l":null,"issn":null,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th International Conference on Cyber Security and Information 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/A5027368431","display_name":"Yezhen Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yezhen Wang","raw_affiliation_strings":["Fuzhou University, China"],"affiliations":[{"raw_affiliation_string":"Fuzhou University, China","institution_ids":["https://openalex.org/I80947539"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5027368431"],"corresponding_institution_ids":["https://openalex.org/I80947539"],"apc_list":null,"apc_paid":null,"fwci":0.1457,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.40951276,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"869","last_page":"873"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9944999814033508,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9944999814033508,"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/T10057","display_name":"Face and Expression Recognition","score":0.993399977684021,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9782999753952026,"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/centroid","display_name":"Centroid","score":0.8103452920913696},{"id":"https://openalex.org/keywords/closeness","display_name":"Closeness","score":0.7859523296356201},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.6903874278068542},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.68927001953125},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.6813893914222717},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6425271034240723},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5757694840431213},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.562503457069397},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4647810459136963},{"id":"https://openalex.org/keywords/nearest-neighbour","display_name":"Nearest neighbour","score":0.45762476325035095},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4528929591178894},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24188876152038574},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2395136058330536}],"concepts":[{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.8103452920913696},{"id":"https://openalex.org/C2779545769","wikidata":"https://www.wikidata.org/wiki/Q5135364","display_name":"Closeness","level":2,"score":0.7859523296356201},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.6903874278068542},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.68927001953125},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.6813893914222717},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6425271034240723},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5757694840431213},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.562503457069397},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4647810459136963},{"id":"https://openalex.org/C2983946233","wikidata":"https://www.wikidata.org/wiki/Q4088109","display_name":"Nearest neighbour","level":2,"score":0.45762476325035095},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4528929591178894},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24188876152038574},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2395136058330536},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3558819.3565209","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3558819.3565209","pdf_url":null,"source":{"id":"https://openalex.org/S4363608855","display_name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","issn_l":null,"issn":null,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th International Conference on Cyber Security and Information Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1963656568","https://openalex.org/W1992329416","https://openalex.org/W2156238897","https://openalex.org/W2346100606","https://openalex.org/W3013814861","https://openalex.org/W6600100092","https://openalex.org/W6603395906","https://openalex.org/W6693465786"],"related_works":["https://openalex.org/W2499112530","https://openalex.org/W2362413895","https://openalex.org/W4283655540","https://openalex.org/W2888231351","https://openalex.org/W4283824693","https://openalex.org/W2622145841","https://openalex.org/W1591806955","https://openalex.org/W4206315490","https://openalex.org/W2062957446","https://openalex.org/W615122461"],"abstract_inverted_index":{"Missing":[0],"values":[1],"often":[2],"exist":[3],"in":[4,34],"scientific":[5],"datasets.":[6],"Therefore,":[7],"practical":[8],"methods":[9],"for":[10,18,91],"missing":[11,35,45,114],"data":[12,21,36,46],"imputation":[13,37],"and":[14,31,38,49,73,80],"classification":[15,47,53,65,96],"are":[16],"necessary":[17],"machine":[19],"learning,":[20],"analysis.":[22],"The":[23],"k-Nearest":[24],"Neighbor":[25],"(KNN)":[26],"algorithm":[27,33],"is":[28,113],"a":[29,51,127],"simple":[30],"effective":[32],"classification.":[39],"This":[40],"paper":[41],"focuses":[42],"on":[43,56,99],"the":[44,57,67,71,77,82,87,107,120,132],"problem":[48],"proposes":[50],"new":[52],"method":[54,69,109,125],"based":[55],"local":[58,83],"mean":[59],"k-nearest":[60],"centroid":[61,89],"neighbour.":[62],"When":[63],"making":[64],"judgments,":[66],"proposed":[68,108,124],"examines":[70],"closeness":[72],"symmetrical":[74],"arrangement":[75],"of":[76,86,122],"k":[78,88],"neighbours":[79,90],"adopts":[81],"mean-based":[84],"vector":[85],"each":[92],"class.":[93],"We":[94],"run":[95],"error":[97],"experiments":[98],"six":[100],"UCI":[101],"datasets":[102],"to":[103,131],"see":[104],"how":[105],"well":[106],"performs":[110],"when":[111],"there":[112],"data.":[115],"Experimental":[116],"results":[117],"show":[118],"that":[119],"performance":[121],"our":[123],"obtains":[126],"significant":[128],"improvement":[129],"compared":[130],"most":[133],"advanced":[134],"KNN-based":[135],"algorithms.":[136]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}