{"id":"https://openalex.org/W4411891798","doi":"https://doi.org/10.54364/aaiml.2025.52208","title":"Improving Financial Distress Prediction through Clustered SMOTE for Imbalanced Data","display_name":"Improving Financial Distress Prediction through Clustered SMOTE for Imbalanced Data","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4411891798","doi":"https://doi.org/10.54364/aaiml.2025.52208"},"language":"en","primary_location":{"id":"doi:10.54364/aaiml.2025.52208","is_oa":true,"landing_page_url":"https://doi.org/10.54364/aaiml.2025.52208","pdf_url":"https://doi.org/10.54364/aaiml.2025.52208","source":{"id":"https://openalex.org/S4210238872","display_name":"Advances in Artificial Intelligence and Machine Learning","issn_l":"2582-9793","issn":["2582-9793"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advances in Artificial Intelligence and Machine Learning","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://doi.org/10.54364/aaiml.2025.52208","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5115434088","display_name":"Kalina Kitova","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kalina Kitova","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040384388","display_name":"Borislava Toleva","orcid":"https://orcid.org/0000-0001-9335-6927"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Borislava Toleva","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5101948369","display_name":"Ivan Ivanov","orcid":"https://orcid.org/0000-0002-9019-072X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ivan Ivanov","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5115434088"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.0146,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.93219321,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"05","issue":"02","first_page":"3663","last_page":"3681"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.9567000269889832,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.9567000269889832,"subfield":{"id":"https://openalex.org/subfields/1402","display_name":"Accounting"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9190999865531921,"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/financial-distress","display_name":"Financial distress","score":0.7470033168792725},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5347420573234558},{"id":"https://openalex.org/keywords/distress","display_name":"Distress","score":0.5167319178581238},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5015296936035156},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4361759126186371},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43198639154434204},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.3378567099571228},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.2858712673187256},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.17689630389213562},{"id":"https://openalex.org/keywords/financial-system","display_name":"Financial system","score":0.09538787603378296}],"concepts":[{"id":"https://openalex.org/C2984760201","wikidata":"https://www.wikidata.org/wiki/Q1785212","display_name":"Financial distress","level":2,"score":0.7470033168792725},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5347420573234558},{"id":"https://openalex.org/C139265228","wikidata":"https://www.wikidata.org/wiki/Q5283089","display_name":"Distress","level":2,"score":0.5167319178581238},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5015296936035156},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4361759126186371},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43198639154434204},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.3378567099571228},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.2858712673187256},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.17689630389213562},{"id":"https://openalex.org/C73283319","wikidata":"https://www.wikidata.org/wiki/Q1416617","display_name":"Financial system","level":1,"score":0.09538787603378296},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.54364/aaiml.2025.52208","is_oa":true,"landing_page_url":"https://doi.org/10.54364/aaiml.2025.52208","pdf_url":"https://doi.org/10.54364/aaiml.2025.52208","source":{"id":"https://openalex.org/S4210238872","display_name":"Advances in Artificial Intelligence and Machine Learning","issn_l":"2582-9793","issn":["2582-9793"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advances in Artificial Intelligence and Machine Learning","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.54364/aaiml.2025.52208","is_oa":true,"landing_page_url":"https://doi.org/10.54364/aaiml.2025.52208","pdf_url":"https://doi.org/10.54364/aaiml.2025.52208","source":{"id":"https://openalex.org/S4210238872","display_name":"Advances in Artificial Intelligence and Machine Learning","issn_l":"2582-9793","issn":["2582-9793"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Advances in Artificial Intelligence and Machine Learning","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411891798.pdf","grobid_xml":"https://content.openalex.org/works/W4411891798.grobid-xml"},"referenced_works_count":17,"referenced_works":["https://openalex.org/W2002830978","https://openalex.org/W2003146103","https://openalex.org/W2148143831","https://openalex.org/W2565188366","https://openalex.org/W2800788706","https://openalex.org/W2896206046","https://openalex.org/W2963613787","https://openalex.org/W2967663220","https://openalex.org/W3154657359","https://openalex.org/W3172873108","https://openalex.org/W3175748729","https://openalex.org/W3189035319","https://openalex.org/W4205666686","https://openalex.org/W4210422014","https://openalex.org/W4224295954","https://openalex.org/W4401020123","https://openalex.org/W6677954473"],"related_works":["https://openalex.org/W4281976195","https://openalex.org/W4404964782","https://openalex.org/W2961085424","https://openalex.org/W2058929387","https://openalex.org/W3124028778","https://openalex.org/W3194230739","https://openalex.org/W2284898608","https://openalex.org/W4224009465","https://openalex.org/W2368843981","https://openalex.org/W2027109559"],"abstract_inverted_index":{"Financial":[0],"distress":[1,35,125],"prediction":[2,36,126],"remains":[3],"fundamental":[4],"to":[5,28,64,112],"identifying":[6],"troubled":[7],"businesses":[8],"since":[9],"it":[10],"determines":[11,50],"business":[12],"stability":[13],"along":[14],"with":[15,74],"economic":[16],"forecast":[17],"accuracy.":[18],"The":[19,48],"research":[20,49],"evaluates":[21],"the":[22,83],"Synthetic":[23],"Minority":[24],"Over-sampling":[25],"Technique":[26],"(SMOTE)":[27],"correct":[29],"class":[30,109],"imbalance":[31],"issues":[32],"in":[33,127],"financial":[34,69,124],"by":[37,56,107],"studying":[38],"its":[39],"results":[40],"when":[41],"standardized":[42],"through":[43],"clustering":[44,53,73,94,116],"and":[45,89,118],"non-clustering":[46],"approaches.":[47],"how":[51],"K-means":[52,72],"strengthens":[54],"SMOTE":[55,75,97,119],"applying":[57],"data":[58],"balancing":[59],"techniques":[60],"inside":[61],"separate":[62],"clusters":[63],"improve":[65],"model":[66,78],"predictions":[67],"for":[68,123],"distress.":[70],"Combining":[71],"substantially":[76],"improves":[77],"performance":[79],"because":[80],"XGBoost":[81],"demonstrates":[82,120],"peak":[84],"results,":[85,114],"including":[86],"99%":[87,90],"accuracy":[88,106],"F1":[91],"score.":[92],"Incorporating":[93],"methods":[95,117],"helps":[96],"produce":[98],"more":[99],"accurate":[100],"synthetic":[101],"samples,":[102],"achieving":[103],"better":[104],"predictive":[105],"improving":[108],"balance.":[110],"According":[111],"these":[113],"combining":[115],"great":[121],"potential":[122],"imbalanced":[128],"datasets.":[129]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
