{"id":"https://openalex.org/W2977628355","doi":"https://doi.org/10.1109/ijcnn.2019.8851946","title":"A Data Stratification Process for Instances Selection in Semi-Supervised Learning","display_name":"A Data Stratification Process for Instances Selection in Semi-Supervised Learning","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2977628355","doi":"https://doi.org/10.1109/ijcnn.2019.8851946","mag":"2977628355"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8851946","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8851946","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 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/A5012461592","display_name":"Karliane Medeiros Ovidio Vale","orcid":"https://orcid.org/0000-0001-9845-8156"},"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":"Karliane M. O. Vale","raw_affiliation_strings":["Dept. of Informatics and Applicated Mathematics (DIMAp), Federal University of Rio Grande do Norte (UFRN), Natal, Brazil"],"affiliations":[{"raw_affiliation_string":"Dept. of Informatics and Applicated Mathematics (DIMAp), Federal University of Rio Grande do Norte (UFRN), Natal, Brazil","institution_ids":["https://openalex.org/I35046152"]}]},{"author_position":"middle","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":false,"raw_author_name":"Anne Magaly de P. Canuto","raw_affiliation_strings":["Dept. of Informatics and Applicated Mathematics (DIMAp), Federal University of Rio Grande do Norte (UFRN), Natal, Brazil"],"affiliations":[{"raw_affiliation_string":"Dept. of Informatics and Applicated Mathematics (DIMAp), Federal University of Rio Grande do Norte (UFRN), Natal, Brazil","institution_ids":["https://openalex.org/I35046152"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005185037","display_name":"Flavius L. Gorg\u00f4nio","orcid":"https://orcid.org/0000-0002-4926-3990"},"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":"Flavius L. Gorgonio","raw_affiliation_strings":["Dept. of Computing and Technology (DCT), Federal University of Rio Grande do Norte (UFRN), Caic\u00f3, Brazil"],"affiliations":[{"raw_affiliation_string":"Dept. of Computing and Technology (DCT), Federal University of Rio Grande do Norte (UFRN), Caic\u00f3, Brazil","institution_ids":["https://openalex.org/I35046152"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026600484","display_name":"Amarildo J. F. Lucena","orcid":null},"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":"Amarildo J. F. Lucena","raw_affiliation_strings":["Dept. of Computing and Technology (DCT), Federal University of Rio Grande do Norte (UFRN), Caic\u00f3, Brazil"],"affiliations":[{"raw_affiliation_string":"Dept. of Computing and Technology (DCT), Federal University of Rio Grande do Norte (UFRN), Caic\u00f3, Brazil","institution_ids":["https://openalex.org/I35046152"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085543266","display_name":"Cainan T. Alves","orcid":null},"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":"Cainan T. Alves","raw_affiliation_strings":["Dept. of Computing and Technology (DCT), Federal University of Rio Grande do Norte (UFRN), Caic\u00f3, Brazil"],"affiliations":[{"raw_affiliation_string":"Dept. of Computing and Technology (DCT), Federal University of Rio Grande do Norte (UFRN), Caic\u00f3, Brazil","institution_ids":["https://openalex.org/I35046152"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081806326","display_name":"Arthur C. Gorg\u00f4nio","orcid":"https://orcid.org/0000-0002-1824-9600"},"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":"Arthur C. Gorgonio","raw_affiliation_strings":["Dept. of Computing and Technology (DCT), Federal University of Rio Grande do Norte (UFRN), Caic\u00f3, Brazil"],"affiliations":[{"raw_affiliation_string":"Dept. of Computing and Technology (DCT), Federal University of Rio Grande do Norte (UFRN), Caic\u00f3, Brazil","institution_ids":["https://openalex.org/I35046152"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113792275","display_name":"Araken M. Santos","orcid":null},"institutions":[{"id":"https://openalex.org/I84554738","display_name":"Universidade Federal Rural do Semi-\u00c1rido","ror":"https://ror.org/05x2svh05","country_code":"BR","type":"education","lineage":["https://openalex.org/I84554738"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Araken M. Santos","raw_affiliation_strings":["Exact, Science and Information Technology Dept. (DCETI), Federal Rural University of Semi-Arido (UFERSA), Angicos, Brazil"],"affiliations":[{"raw_affiliation_string":"Exact, Science and Information Technology Dept. (DCETI), Federal Rural University of Semi-Arido (UFERSA), Angicos, Brazil","institution_ids":["https://openalex.org/I84554738"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5012461592"],"corresponding_institution_ids":["https://openalex.org/I35046152"],"apc_list":null,"apc_paid":null,"fwci":0.8401,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.80606332,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":96},"biblio":{"volume":null,"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":0.9932000041007996,"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":0.9932000041007996,"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":0.9886999726295471,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9793000221252441,"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/computer-science","display_name":"Computer science","score":0.7472679615020752},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6946134567260742},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6761735677719116},{"id":"https://openalex.org/keywords/representativeness-heuristic","display_name":"Representativeness heuristic","score":0.6498060822486877},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.591631293296814},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5912346839904785},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4979231357574463},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.47018539905548096},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.44981318712234497},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.44824159145355225},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35251933336257935},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18094372749328613},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.1372910737991333},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13234615325927734}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7472679615020752},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6946134567260742},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6761735677719116},{"id":"https://openalex.org/C37381756","wikidata":"https://www.wikidata.org/wiki/Q20203288","display_name":"Representativeness heuristic","level":2,"score":0.6498060822486877},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.591631293296814},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5912346839904785},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4979231357574463},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.47018539905548096},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.44981318712234497},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.44824159145355225},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35251933336257935},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18094372749328613},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.1372910737991333},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13234615325927734}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2019.8851946","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8851946","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.5699999928474426,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1479807131","https://openalex.org/W1541145887","https://openalex.org/W1570448133","https://openalex.org/W1968817125","https://openalex.org/W2005890377","https://openalex.org/W2021739900","https://openalex.org/W2048679005","https://openalex.org/W2049832889","https://openalex.org/W2080656324","https://openalex.org/W2101210369","https://openalex.org/W2124868070","https://openalex.org/W2182722412","https://openalex.org/W2195092867","https://openalex.org/W2235571288","https://openalex.org/W2239420864","https://openalex.org/W2304932561","https://openalex.org/W2486791387","https://openalex.org/W2607290190","https://openalex.org/W2619296796","https://openalex.org/W2772176048","https://openalex.org/W2782190632","https://openalex.org/W2895931117","https://openalex.org/W3120740533","https://openalex.org/W4248018214","https://openalex.org/W6632481002","https://openalex.org/W6736928820","https://openalex.org/W6755344646","https://openalex.org/W6989699103"],"related_works":["https://openalex.org/W4389954502","https://openalex.org/W2771255398","https://openalex.org/W2930428186","https://openalex.org/W3200027047","https://openalex.org/W4385770464","https://openalex.org/W3125536479","https://openalex.org/W3120363735","https://openalex.org/W4214820172","https://openalex.org/W2394323384","https://openalex.org/W4387382336"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,25,40,130],"study":[4],"in":[5,17,21,29,51,57,142],"the":[6,18,30,52,58,65,74,78,82,122,135,145,151],"field":[7],"of":[8,33,54,81,134],"semi-supervised":[9],"learning":[10],"and,":[11],"more":[12],"specifically,":[13],"it":[14],"proposes":[15,39],"changes":[16],"self-training":[19,153],"algorithm":[20],"order":[22,87],"to":[23,47,88,128],"apply":[24,48],"data":[26,49,60,100],"stratification":[27,50],"method":[28],"labeling":[31,75],"process":[32],"this":[34,37,63,90],"algorithm.":[35],"Therefore,":[36],"work":[38],"method,":[41],"called":[42],"FlexCon-CS,":[43],"whose":[44],"objective":[45],"is":[46],"inclusion":[53],"new":[55],"instances":[56],"training":[59],"set.":[61],"In":[62,86],"sense,":[64],"representativeness":[66],"and":[67,117],"class":[68],"distribution":[69,101],"will":[70],"be":[71],"maintained":[72],"throughout":[73],"process,":[76],"with":[77,98,107],"same":[79],"proportions":[80],"initially":[83],"labeled":[84],"dataset.":[85],"evaluate":[89],"proposal,":[91],"we":[92],"performed":[93],"experiments":[94],"on":[95],"27":[96],"databases":[97],"different":[99,109],"features.":[102],"Each":[103],"dataset":[104],"was":[105,126],"trained":[106],"four":[108],"classification":[110],"algorithms,":[111],"Naive":[112],"Bayes,":[113],"Decision":[114],"Tree,":[115],"ripper,":[116],"K-Nearest":[118],"Neighbor":[119],"classifiers.":[120],"Moreover,":[121],"Friedman":[123],"statistical":[124],"test":[125],"applied":[127],"provide":[129],"statistically":[131],"significant":[132],"analysis":[133],"obtained":[136],"results.":[137],"Our":[138],"findings":[139],"indicate":[140],"that,":[141],"most":[143],"cases,":[144],"proposed":[146],"methods":[147],"perform":[148],"better":[149],"than":[150],"original":[152],"method.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-25T21:42:39.735039","created_date":"2025-10-10T00:00:00"}