{"id":"https://openalex.org/W4402352130","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651006","title":"Towards Total Dynamicity of a Feature Selection Method based on the Pareto Front","display_name":"Towards Total Dynamicity of a Feature Selection Method based on the Pareto Front","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402352130","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651006"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10651006","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10651006","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","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/A5019144108","display_name":"Anne M. P. Canuto","orcid":"https://orcid.org/0000-0002-3684-3814"},"institutions":[{"id":"https://openalex.org/I35046152","display_name":"Universidade Federal do Rio Grande do Norte","ror":"https://ror.org/04wn09761","country_code":"BR","type":"education","lineage":["https://openalex.org/I35046152"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Anne M P Canuto","raw_affiliation_strings":["Federal University of Rio Grande do Norte,Department of Informatics and Applied Mathematics,Natal,RN,Brazil"],"affiliations":[{"raw_affiliation_string":"Federal University of Rio Grande do Norte,Department of Informatics and Applied Mathematics,Natal,RN,Brazil","institution_ids":["https://openalex.org/I35046152"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018891554","display_name":"Jhoseph Jesus","orcid":"https://orcid.org/0000-0002-5834-3781"},"institutions":[{"id":"https://openalex.org/I35046152","display_name":"Universidade Federal do Rio Grande do Norte","ror":"https://ror.org/04wn09761","country_code":"BR","type":"education","lineage":["https://openalex.org/I35046152"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Jhoseph Kelvin Lopes de Jesus","raw_affiliation_strings":["Federal University of Rio Grande do Norte,Natal,RN,Brazil"],"affiliations":[{"raw_affiliation_string":"Federal University of Rio Grande do Norte,Natal,RN,Brazil","institution_ids":["https://openalex.org/I35046152"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069724907","display_name":"Daniel Ara\u00fajo","orcid":"https://orcid.org/0000-0001-5572-0505"},"institutions":[{"id":"https://openalex.org/I35046152","display_name":"Universidade Federal do Rio Grande do Norte","ror":"https://ror.org/04wn09761","country_code":"BR","type":"education","lineage":["https://openalex.org/I35046152"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Daniel S A de Araujo","raw_affiliation_strings":["Federal University of Rio Grande do Norte,Metropole Digital Institute,Natal,RN,Brazil"],"affiliations":[{"raw_affiliation_string":"Federal University of Rio Grande do Norte,Metropole Digital Institute,Natal,RN,Brazil","institution_ids":["https://openalex.org/I35046152"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5019144108"],"corresponding_institution_ids":["https://openalex.org/I35046152"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12912072,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"3","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9993000030517578,"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":0.9993000030517578,"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/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9954000115394592,"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/T10848","display_name":"Advanced Multi-Objective Optimization Algorithms","score":0.9937999844551086,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.6675882339477539},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6213019490242004},{"id":"https://openalex.org/keywords/pareto-principle","display_name":"Pareto principle","score":0.6026767492294312},{"id":"https://openalex.org/keywords/front","display_name":"Front (military)","score":0.5735025405883789},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5680776834487915},{"id":"https://openalex.org/keywords/multi-objective-optimization","display_name":"Multi-objective optimization","score":0.5592900514602661},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5045701265335083},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4466165602207184},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36958593130111694},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35126757621765137},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.2559114694595337},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.23541691899299622},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16660428047180176},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12937897443771362}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6675882339477539},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6213019490242004},{"id":"https://openalex.org/C137635306","wikidata":"https://www.wikidata.org/wiki/Q182667","display_name":"Pareto principle","level":2,"score":0.6026767492294312},{"id":"https://openalex.org/C2777551076","wikidata":"https://www.wikidata.org/wiki/Q842332","display_name":"Front (military)","level":2,"score":0.5735025405883789},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5680776834487915},{"id":"https://openalex.org/C68781425","wikidata":"https://www.wikidata.org/wiki/Q2052203","display_name":"Multi-objective optimization","level":2,"score":0.5592900514602661},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5045701265335083},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4466165602207184},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36958593130111694},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35126757621765137},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2559114694595337},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.23541691899299622},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16660428047180176},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12937897443771362},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10651006","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10651006","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W140777655","https://openalex.org/W1418108976","https://openalex.org/W1500895378","https://openalex.org/W1965555277","https://openalex.org/W1974758710","https://openalex.org/W1995875735","https://openalex.org/W2048957655","https://openalex.org/W2121410881","https://openalex.org/W2132862423","https://openalex.org/W2135904200","https://openalex.org/W2149772057","https://openalex.org/W2167101736","https://openalex.org/W2260771218","https://openalex.org/W2553126964","https://openalex.org/W2896196728","https://openalex.org/W2898901176","https://openalex.org/W2904740771","https://openalex.org/W2913879094","https://openalex.org/W2917892996","https://openalex.org/W2962755847","https://openalex.org/W2982627395","https://openalex.org/W2986368198","https://openalex.org/W2993975328","https://openalex.org/W2998216295","https://openalex.org/W3110406587","https://openalex.org/W3120740533","https://openalex.org/W4400762160","https://openalex.org/W6692628530","https://openalex.org/W7066667914"],"related_works":["https://openalex.org/W4386564352","https://openalex.org/W2952668426","https://openalex.org/W2090178682","https://openalex.org/W2001591765","https://openalex.org/W4241467429","https://openalex.org/W2073147994","https://openalex.org/W1588199609","https://openalex.org/W2384474142","https://openalex.org/W1550055091","https://openalex.org/W2744462909"],"abstract_inverted_index":{"Many":[0],"feature":[1,93],"selection":[2,21,51,62,94,159],"strategies":[3],"have":[4],"been":[5],"proposed":[6,146],"lately,":[7],"using":[8,27],"different":[9],"criteria":[10,29],"to":[11,31,70,113,152,156,171],"select":[12],"the":[13,33,47,56,88,98,115,119,133,144,157,172],"most":[14],"relevant":[15],"features.":[16],"The":[17,129],"use":[18,48],"of":[19,22,36,49,55,72,90,118],"dynamic":[20,50,92],"attributes,":[23],"however,":[24],"showed":[25],"that":[26,143],"multiple":[28],"simultaneously":[30],"determine":[32],"best":[34],"subset":[35],"attributes":[37],"for":[38,105],"similar":[39],"testing":[40],"instances":[41],"can":[42],"provide":[43],"encouraging":[44],"results.":[45],"Although":[46],"has":[52],"alleviated":[53],"some":[54,64],"limitations":[57,71],"found":[58,131],"in":[59,66,87,137,147],"traditional":[60],"(static)":[61],"methods,":[63],"characteristics":[65],"its":[67,127],"processing":[68,89,121],"lead":[69],"this":[73,80,82,138,148],"technique":[74],"on":[75,97,132],"complex":[76],"classification":[77],"problems.":[78],"In":[79],"context,":[81],"paper":[83,139,149],"proposes":[84],"an":[85],"extension":[86,145],"a":[91,124,163],"method":[95],"based":[96],"Pareto":[99,106],"Front":[100,107],"(named":[101],"PF-DFS,":[102],"which":[103],"stands":[104],"\u2013":[108],"Dynamic":[109],"Feature":[110],"Selection),":[111],"aiming":[112],"reach":[114],"total":[116],"dynamicity":[117],"PF-DFS":[120],"and,":[122],"as":[123,162,166,168],"consequence,":[125],"improving":[126],"efficiency.":[128],"results":[130,154],"empirical":[134],"analyses":[135],"employed":[136],"are":[140,150],"promising,":[141],"demonstrating":[142],"able":[151],"obtain":[153],"superior":[155],"attribute":[158],"methods":[160],"used":[161],"comparative":[164],"basis,":[165],"well":[167],"when":[169],"compared":[170],"original":[173],"data":[174],"set.":[175]},"counts_by_year":[],"updated_date":"2025-12-19T19:40:27.379048","created_date":"2025-10-10T00:00:00"}