{"id":"https://openalex.org/W2537910863","doi":"https://doi.org/10.1109/acpr.2011.6166552","title":"Instance selection for speeding up multi-class SVMs with neighborhoods","display_name":"Instance selection for speeding up multi-class SVMs with neighborhoods","publication_year":2011,"publication_date":"2011-11-01","ids":{"openalex":"https://openalex.org/W2537910863","doi":"https://doi.org/10.1109/acpr.2011.6166552","mag":"2537910863"},"language":"en","primary_location":{"id":"doi:10.1109/acpr.2011.6166552","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acpr.2011.6166552","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The First Asian Conference on Pattern Recognition","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/A5019484454","display_name":"Jingnian Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingnian Chen","raw_affiliation_strings":["National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100714202","display_name":"Cheng\u2010Lin Liu","orcid":"https://orcid.org/0000-0002-6743-4175"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng-Lin Liu","raw_affiliation_strings":["National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8793,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.82608696,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"2","issue":null,"first_page":"264","last_page":"268"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9983000159263611,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9983000159263611,"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":0.9973000288009644,"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/T10057","display_name":"Face and Expression Recognition","score":0.992900013923645,"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/support-vector-machine","display_name":"Support vector machine","score":0.8255656361579895},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7729557156562805},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6433500647544861},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6295906901359558},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5874984860420227},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5485823154449463},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.4864821135997772},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4183986783027649},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4119139015674591},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4019958972930908}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8255656361579895},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7729557156562805},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6433500647544861},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6295906901359558},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5874984860420227},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5485823154449463},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.4864821135997772},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4183986783027649},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4119139015674591},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4019958972930908}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acpr.2011.6166552","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acpr.2011.6166552","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The First Asian Conference on Pattern Recognition","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W740415","https://openalex.org/W184442817","https://openalex.org/W1521723576","https://openalex.org/W1531648066","https://openalex.org/W1993926867","https://openalex.org/W2014986661","https://openalex.org/W2053724458","https://openalex.org/W2095885101","https://openalex.org/W2100038678","https://openalex.org/W2117990954","https://openalex.org/W2124351082","https://openalex.org/W2127406992","https://openalex.org/W2132407367","https://openalex.org/W2137472923","https://openalex.org/W2143821562","https://openalex.org/W2149684865","https://openalex.org/W2155415049","https://openalex.org/W2156909104","https://openalex.org/W2157239837","https://openalex.org/W2159737176","https://openalex.org/W2912934387","https://openalex.org/W4212883601","https://openalex.org/W4285719527","https://openalex.org/W6607466906","https://openalex.org/W6631390839","https://openalex.org/W6631884152","https://openalex.org/W6677732001","https://openalex.org/W6683380652"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W1948992892","https://openalex.org/W2104657898","https://openalex.org/W1886884218","https://openalex.org/W1910826599","https://openalex.org/W1980100242","https://openalex.org/W2346511343","https://openalex.org/W2357114597","https://openalex.org/W2115416187"],"abstract_inverted_index":{"Although":[0],"support":[1],"vector":[2],"machines":[3],"(SVMs)":[4],"are":[5],"an":[6,36,97],"excellent":[7],"technology":[8],"for":[9,17,73],"classification,":[10],"it":[11],"is":[12,101,112],"still":[13],"a":[14,52,110,124],"serious":[15],"challenge":[16],"this":[18],"method":[19,143],"to":[20,23,46,103,114],"be":[21],"applied":[22],"massive":[24],"datasets":[25,128,140],"with":[26],"large":[27],"number":[28],"of":[29,51,60,69,83,94,118,127,132,161],"classes":[30,86],"and":[31,55,106,158],"instances.":[32,108],"This":[33],"paper":[34],"presents":[35],"instance":[37],"selection":[38],"method,":[39],"the":[40,49,58,64,84,116,130,141,149,155],"Filtered":[41],"Nearest":[42],"Enemies":[43],"(FINE)":[44],"algorithm,":[45],"substantially":[47],"reduce":[48,104],"scale":[50],"multi-class":[53,71],"dataset":[54],"speed":[56],"up":[57],"training":[59,70,119,156,159],"SVM":[61],"models.":[62],"With":[63],"one":[65],"versus":[66],"rest":[67],"style":[68],"SVMs,":[72],"each":[74,82],"instance,":[75],"FINE":[76,133],"selects":[77],"k":[78],"nearest":[79],"neighbors":[80],"from":[81],"other":[85,135],"(named":[87],"k-Nearest":[88],"Enemies).":[89],"After":[90],"selecting":[91],"k-nearest":[92],"enemies":[93],"all":[95],"instances,":[96],"effective":[98],"filtering":[99],"procedure":[100],"used":[102],"redundant":[105],"noisy":[107],"Furthermore,":[109],"strategy":[111],"adopted":[113],"control":[115],"imbalance":[117],"data.":[120],"Experiments":[121],"performed":[122],"on":[123],"wide":[125],"variety":[126],"demonstrate":[129],"superiority":[131],"over":[134],"competitive":[136],"algorithms.":[137],"On":[138],"most":[139],"proposed":[142],"can":[144],"keep":[145],"or":[146],"even":[147],"improve":[148],"classification":[150],"accuracy":[151],"while":[152],"sharply":[153],"reducing":[154],"data":[157],"time":[160],"SVMs.":[162]},"counts_by_year":[{"year":2014,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
