{"id":"https://openalex.org/W2607643809","doi":"https://doi.org/10.1109/icpr.2016.7899676","title":"WENN for individualized cleaning in imbalanced data","display_name":"WENN for individualized cleaning in imbalanced data","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2607643809","doi":"https://doi.org/10.1109/icpr.2016.7899676","mag":"2607643809"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2016.7899676","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7899676","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5079099916","display_name":"Hengyu Guan","orcid":"https://orcid.org/0009-0007-6168-285X"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongjiao Guan","raw_affiliation_strings":["Harbin Institute of Technology, Harbin, P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Harbin, P.R. China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032429023","display_name":"Yingtao Zhang","orcid":"https://orcid.org/0000-0002-8587-9645"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingtao Zhang","raw_affiliation_strings":["Harbin Institute of Technology, Harbin, P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Harbin, P.R. China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080652935","display_name":"Min Xian","orcid":"https://orcid.org/0000-0001-6098-4441"},"institutions":[{"id":"https://openalex.org/I121980950","display_name":"Utah State University","ror":"https://ror.org/00h6set76","country_code":"US","type":"education","lineage":["https://openalex.org/I121980950"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Min Xian","raw_affiliation_strings":["Utah State University, Logan, UT, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Utah State University, Logan, UT, USA","institution_ids":["https://openalex.org/I121980950"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101890714","display_name":"Heng-Da Cheng","orcid":"https://orcid.org/0000-0003-3569-7621"},"institutions":[{"id":"https://openalex.org/I121980950","display_name":"Utah State University","ror":"https://ror.org/00h6set76","country_code":"US","type":"education","lineage":["https://openalex.org/I121980950"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"H.D. Cheng","raw_affiliation_strings":["Utah State University, Logan, UT, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Utah State University, Logan, UT, USA","institution_ids":["https://openalex.org/I121980950"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066017268","display_name":"Xianglong Tang","orcid":"https://orcid.org/0000-0002-1119-2138"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianglong Tang","raw_affiliation_strings":["Harbin Institute of Technology, Harbin, P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Harbin, P.R. China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"456","last_page":"461"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9987999796867371,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9987999796867371,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9915000200271606,"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/T11719","display_name":"Data Quality and Management","score":0.9656000137329102,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.8284665942192078},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7584809064865112},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7309136390686035},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6187376976013184},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5950922966003418},{"id":"https://openalex.org/keywords/real-world-data","display_name":"Real world data","score":0.44004905223846436},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.43522417545318604},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4324858486652374},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.4252853989601135},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4213988184928894},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.19442829489707947}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.8284665942192078},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7584809064865112},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7309136390686035},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6187376976013184},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5950922966003418},{"id":"https://openalex.org/C3020493868","wikidata":"https://www.wikidata.org/wiki/Q55631277","display_name":"Real world data","level":2,"score":0.44004905223846436},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.43522417545318604},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4324858486652374},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.4252853989601135},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4213988184928894},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.19442829489707947},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr.2016.7899676","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7899676","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.46000000834465027}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W102369970","https://openalex.org/W146100937","https://openalex.org/W752888290","https://openalex.org/W1036088323","https://openalex.org/W1592804209","https://openalex.org/W1993023793","https://openalex.org/W1993220166","https://openalex.org/W2023639956","https://openalex.org/W2070808135","https://openalex.org/W2107138773","https://openalex.org/W2107686700","https://openalex.org/W2115012618","https://openalex.org/W2129785984","https://openalex.org/W2148143831","https://openalex.org/W2163952039","https://openalex.org/W2164873210","https://openalex.org/W2165466912","https://openalex.org/W3120740533","https://openalex.org/W6605896687","https://openalex.org/W6622294026"],"related_works":["https://openalex.org/W4380150146","https://openalex.org/W3024870410","https://openalex.org/W2410652950","https://openalex.org/W4283773154","https://openalex.org/W3139174110","https://openalex.org/W4289597203","https://openalex.org/W2085630472","https://openalex.org/W1977098485","https://openalex.org/W4285201053","https://openalex.org/W4256612600"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"individualized":[3],"cleaning":[4,14,124],"for":[5,12],"diverse":[6],"imbalanced":[7,74],"data":[8,13,48,105,113,123],"sets.":[9],"Existing":[10],"techniques":[11],"have":[15],"difficulties":[16],"with":[17],"rare":[18],"cases":[19],"and":[20,34,45,60,80,111],"outliers":[21],"in":[22,26],"minority":[23,102],"class,":[24],"especially,":[25],"highly":[27],"unbalanced":[28],"data.":[29],"The":[30,83],"drawback":[31],"leads":[32],"incomplete":[33],"imprecise":[35],"examples":[36,63],"to":[37,41,91],"removal.":[38],"In":[39],"order":[40],"enhance":[42],"the":[43,87,97,101,116],"robustness":[44],"perform":[46],"thorough":[47],"cleaning,":[49],"we":[50],"propose":[51],"a":[52],"weighted":[53],"edited":[54],"nearest":[55],"neighbor":[56],"(WENN),":[57],"which":[58],"detects":[59],"removes":[61],"noisy":[62],"from":[64],"both":[65],"classes":[66],"intelligently.":[67],"It":[68],"considers":[69],"individual":[70],"characteristics":[71],"of":[72,86,118],"each":[73],"data,":[75],"involving":[76],"global":[77],"class":[78,99,103],"imbalance":[79],"local":[81],"distribution.":[82],"main":[84],"idea":[85],"proposed":[88],"method":[89],"is":[90],"carefully":[92],"put":[93],"more":[94],"focus":[95],"on":[96],"majority":[98],"than":[100],"during":[104],"cleaning.":[106],"Extensive":[107],"experiments":[108],"over":[109],"synthetic":[110],"real":[112],"clearly":[114],"validate":[115],"superiority":[117],"our":[119],"approach":[120],"against":[121],"other":[122],"methods.":[125]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}