{"id":"https://openalex.org/W2564743947","doi":"https://doi.org/10.1109/iisa.2016.7785435","title":"Effectiveness of semi-supervised learning in bankruptcy prediction","display_name":"Effectiveness of semi-supervised learning in bankruptcy prediction","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2564743947","doi":"https://doi.org/10.1109/iisa.2016.7785435","mag":"2564743947"},"language":"en","primary_location":{"id":"doi:10.1109/iisa.2016.7785435","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iisa.2016.7785435","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 7th International Conference on Information, Intelligence, Systems &amp; Applications (IISA)","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/A5073119708","display_name":"Stamatis Karlos","orcid":"https://orcid.org/0000-0002-5307-6186"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Stamatis Karlos","raw_affiliation_strings":["Department of Mathematics, University of Patras, Patras, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of Patras, Patras, Greece","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066370772","display_name":"Sotiris Kotsiantis","orcid":"https://orcid.org/0000-0002-2247-3082"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Sotiris Kotsiantis","raw_affiliation_strings":["Department of Electrical Engineering, University of Patras"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Patras","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061070955","display_name":"Nikos Fazakis","orcid":"https://orcid.org/0000-0001-7687-2380"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Nikos Fazakis","raw_affiliation_strings":["Department of Mathematics, University of Patras"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of Patras","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012058127","display_name":"Kyriakos Sgarbas","orcid":"https://orcid.org/0000-0002-1797-1343"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Kyrgiakos Sgarbas","raw_affiliation_strings":["Department of Electrical Engineering, University of Patras"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Patras","institution_ids":["https://openalex.org/I174878644"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I174878644"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9945999979972839,"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/bankruptcy","display_name":"Bankruptcy","score":0.7441667914390564},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6129060387611389},{"id":"https://openalex.org/keywords/bankruptcy-prediction","display_name":"Bankruptcy prediction","score":0.5480296611785889},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5441778898239136},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.502446174621582},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.1375313103199005},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.1206384003162384}],"concepts":[{"id":"https://openalex.org/C504631918","wikidata":"https://www.wikidata.org/wiki/Q152074","display_name":"Bankruptcy","level":2,"score":0.7441667914390564},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6129060387611389},{"id":"https://openalex.org/C2777388754","wikidata":"https://www.wikidata.org/wiki/Q1664594","display_name":"Bankruptcy prediction","level":3,"score":0.5480296611785889},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5441778898239136},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.502446174621582},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.1375313103199005},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.1206384003162384}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iisa.2016.7785435","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iisa.2016.7785435","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 7th International Conference on Information, Intelligence, Systems &amp; Applications (IISA)","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/W151056644","https://openalex.org/W189198445","https://openalex.org/W564562522","https://openalex.org/W1479758384","https://openalex.org/W1595276678","https://openalex.org/W1670132599","https://openalex.org/W1905214399","https://openalex.org/W1966873979","https://openalex.org/W1971141266","https://openalex.org/W1990334093","https://openalex.org/W2037603696","https://openalex.org/W2045516668","https://openalex.org/W2046792933","https://openalex.org/W2048679005","https://openalex.org/W2051046643","https://openalex.org/W2056926196","https://openalex.org/W2067223851","https://openalex.org/W2074719057","https://openalex.org/W2094490861","https://openalex.org/W2098307847","https://openalex.org/W2098708659","https://openalex.org/W2106401878","https://openalex.org/W2126686675","https://openalex.org/W2133556223","https://openalex.org/W2182722412","https://openalex.org/W2232707789","https://openalex.org/W2594788739","https://openalex.org/W6607691338","https://openalex.org/W6636883489"],"related_works":["https://openalex.org/W2285942202","https://openalex.org/W4237436108","https://openalex.org/W2241582670","https://openalex.org/W2961085424","https://openalex.org/W2347342407","https://openalex.org/W4306674287","https://openalex.org/W2270360991","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W3170094116"],"abstract_inverted_index":{"Adoption":[0],"of":[1,21,54,63],"techniques":[2],"from":[3,59,88],"fields":[4],"related":[5],"with":[6],"Data":[7,13],"Science,":[8],"such":[9],"as":[10],"Machine":[11],"Learning,":[12],"Mining":[14],"and":[15,33,75,105],"Predictive":[16],"Analysis,":[17],"in":[18,43,48,94],"the":[19,30,34,49,106],"task":[20,56],"bankruptcy":[22],"prediction":[23],"can":[24,76],"produce":[25],"useful":[26],"knowledge":[27],"for":[28,65],"both":[29],"policy":[31],"makers":[32],"organizations":[35],"that":[36],"are":[37,41,108],"already":[38],"funding":[39],"or":[40],"interested":[42],"acting":[44],"towards":[45],"this":[46,55,73,95],"direction":[47],"near":[50],"future.":[51],"The":[52],"nature":[53],"prevents":[57],"analysts":[58],"collecting":[60],"large":[61],"amount":[62],"data":[64,87],"building":[66],"accurate":[67],"predictive":[68],"models.":[69],"Semi-supervised":[70],"algorithms":[71,104],"overcome":[72],"phenomenon":[74],"perform":[77],"robust":[78],"behavior":[79],"based":[80],"on":[81],"a":[82],"few":[83],"data.":[84],"Experiments":[85],"using":[86],"Greek":[89],"firms":[90],"have":[91],"been":[92],"made":[93],"work,":[96],"comparing":[97],"many":[98],"semi-supervised":[99],"schemes":[100],"against":[101],"well-known":[102],"supervised":[103],"results":[107],"promising.":[109]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
