{"id":"https://openalex.org/W3014359486","doi":"https://doi.org/10.1145/3341105.3374084","title":"Large-scale machine learning for business sector prediction","display_name":"Large-scale machine learning for business sector prediction","publication_year":2020,"publication_date":"2020-03-29","ids":{"openalex":"https://openalex.org/W3014359486","doi":"https://doi.org/10.1145/3341105.3374084","mag":"3014359486"},"language":"en","primary_location":{"id":"doi:10.1145/3341105.3374084","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3341105.3374084","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 35th Annual ACM Symposium on Applied Computing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/1887/3620818","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004677331","display_name":"Mitch N. Angenent","orcid":null},"institutions":[{"id":"https://openalex.org/I121797337","display_name":"Leiden University","ror":"https://ror.org/027bh9e22","country_code":"NL","type":"education","lineage":["https://openalex.org/I121797337"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Mitch N. Angenent","raw_affiliation_strings":["Leiden University, Leiden, the Netherlands"],"affiliations":[{"raw_affiliation_string":"Leiden University, Leiden, the Netherlands","institution_ids":["https://openalex.org/I121797337"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062840797","display_name":"Ant\u00f3nio Pereira Barata","orcid":null},"institutions":[{"id":"https://openalex.org/I121797337","display_name":"Leiden University","ror":"https://ror.org/027bh9e22","country_code":"NL","type":"education","lineage":["https://openalex.org/I121797337"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Ant\u00f3nio Pereira Barata","raw_affiliation_strings":["Leiden University, Leiden, the Netherlands"],"affiliations":[{"raw_affiliation_string":"Leiden University, Leiden, the Netherlands","institution_ids":["https://openalex.org/I121797337"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032475130","display_name":"Frank W. Takes","orcid":"https://orcid.org/0000-0001-5468-1030"},"institutions":[{"id":"https://openalex.org/I121797337","display_name":"Leiden University","ror":"https://ror.org/027bh9e22","country_code":"NL","type":"education","lineage":["https://openalex.org/I121797337"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Frank W. Takes","raw_affiliation_strings":["Leiden University, Leiden, the Netherlands"],"affiliations":[{"raw_affiliation_string":"Leiden University, Leiden, the Netherlands","institution_ids":["https://openalex.org/I121797337"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5004677331"],"corresponding_institution_ids":["https://openalex.org/I121797337"],"apc_list":null,"apc_paid":null,"fwci":1.6075,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.8480063,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1143","last_page":"1146"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11653","display_name":"Financial Distress and Bankruptcy Prediction","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9987999796867371,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6321686506271362},{"id":"https://openalex.org/keywords/bankruptcy","display_name":"Bankruptcy","score":0.610560953617096},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5779262185096741},{"id":"https://openalex.org/keywords/business-sector","display_name":"Business sector","score":0.5453150272369385},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.5302533507347107},{"id":"https://openalex.org/keywords/financial-sector","display_name":"Financial sector","score":0.5153957605361938},{"id":"https://openalex.org/keywords/bankruptcy-prediction","display_name":"Bankruptcy prediction","score":0.5037552714347839},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4971647560596466},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4929916560649872},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47209662199020386},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4163592755794525},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.3083474636077881},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.23336085677146912},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.10958054661750793}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6321686506271362},{"id":"https://openalex.org/C504631918","wikidata":"https://www.wikidata.org/wiki/Q152074","display_name":"Bankruptcy","level":2,"score":0.610560953617096},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5779262185096741},{"id":"https://openalex.org/C137757676","wikidata":"https://www.wikidata.org/wiki/Q3477367","display_name":"Business sector","level":2,"score":0.5453150272369385},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.5302533507347107},{"id":"https://openalex.org/C2986840890","wikidata":"https://www.wikidata.org/wiki/Q837171","display_name":"Financial sector","level":2,"score":0.5153957605361938},{"id":"https://openalex.org/C2777388754","wikidata":"https://www.wikidata.org/wiki/Q1664594","display_name":"Bankruptcy prediction","level":3,"score":0.5037552714347839},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4971647560596466},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4929916560649872},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47209662199020386},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4163592755794525},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.3083474636077881},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.23336085677146912},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.10958054661750793},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C136264566","wikidata":"https://www.wikidata.org/wiki/Q159810","display_name":"Economy","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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":3,"locations":[{"id":"doi:10.1145/3341105.3374084","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3341105.3374084","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 35th Annual ACM Symposium on Applied Computing","raw_type":"proceedings-article"},{"id":"pmh:oai:scholarlypublications.universiteitleiden.nl:item_3620818","is_oa":false,"landing_page_url":"https://hdl.handle.net/1887/3620818","pdf_url":null,"source":{"id":"https://openalex.org/S4306400850","display_name":"Leiden Repository (Leiden University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I121797337","host_organization_name":"Leiden University","host_organization_lineage":["https://openalex.org/I121797337"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the 35th ACM/SIGAPP Symposium on Applied Computing","raw_type":"Article in monograph or in proceedings"},{"id":"pmh:ul:oai:scholarlypublications.universiteitleiden.nl:item_3620818","is_oa":true,"landing_page_url":"http://hdl.handle.net/1887/3620818","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the 35th ACM/SIGAPP Symposium on Applied Computing, 1143 - 1146. New York, U.S.A.: Association for Computing Machinery","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:ul:oai:scholarlypublications.universiteitleiden.nl:item_3620818","is_oa":true,"landing_page_url":"http://hdl.handle.net/1887/3620818","pdf_url":null,"source":{"id":"https://openalex.org/S4306401843","display_name":"Data Archiving and Networked Services (DANS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1322597698","host_organization_name":"Royal Netherlands Academy of Arts and Sciences","host_organization_lineage":["https://openalex.org/I1322597698"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of the 35th ACM/SIGAPP Symposium on Applied Computing, 1143 - 1146. New York, U.S.A.: Association for Computing Machinery","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.6399999856948853,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1636890143","https://openalex.org/W1797640679","https://openalex.org/W1818008271","https://openalex.org/W1857165248","https://openalex.org/W1972666639","https://openalex.org/W1996031526","https://openalex.org/W2078423146","https://openalex.org/W2085573882","https://openalex.org/W2113242816","https://openalex.org/W2132966115","https://openalex.org/W2145123516","https://openalex.org/W2148143831","https://openalex.org/W2319270064","https://openalex.org/W2414539072","https://openalex.org/W2510142126","https://openalex.org/W2521200999","https://openalex.org/W2770490030","https://openalex.org/W2911964244","https://openalex.org/W2997591727","https://openalex.org/W4252684946","https://openalex.org/W4293713156"],"related_works":["https://openalex.org/W2285942202","https://openalex.org/W4237436108","https://openalex.org/W2241582670","https://openalex.org/W2347342407","https://openalex.org/W3180694154","https://openalex.org/W2270360991","https://openalex.org/W2940834140","https://openalex.org/W2738355008","https://openalex.org/W4238227620","https://openalex.org/W3012986183"],"abstract_inverted_index":{"In":[0,60,82],"this":[1,61],"study":[2],"we":[3,63,137,157],"use":[4],"machine":[5],"learning":[6,104],"to":[7],"perform":[8],"explainable":[9],"business":[10,68,112,143,172],"sector":[11,69,96,113,144],"prediction":[12,114],"from":[13,122,134],"financial":[14,26,36,132,205],"statements.":[15],"Financial":[16],"statements":[17,37,133,206],"are":[18,150],"a":[19,65,85,102,116,120,160,183,213],"valuable":[20,74],"source":[21],"of":[22,30,44,126,163,171,182,209],"information":[23],"on":[24,35,50,55,107],"the":[25,42,123,153,169,178,189,202,210],"state":[27],"and":[28,58,79,207],"performance":[29],"firms.":[31],"Recently,":[32],"large-scale":[33],"data":[34,46,52],"has":[38,72],"become":[39],"available":[40],"in":[41,90,152,175,199],"form":[43],"open":[45],"sets.":[47],"Previous":[48],"work":[49],"such":[51,84],"mainly":[53],"focused":[54],"predicting":[56,168],"fraud":[57,80],"bankruptcy.":[59],"paper":[62],"devise":[64],"model":[66,87,141],"for":[67,142,167],"prediction,":[70],"which":[71,148],"several":[73],"applications,":[75],"including":[76],"automated":[77],"error":[78],"detection.":[81],"addition,":[83],"predictive":[86],"may":[88,195],"help":[89],"completing":[91],"similar":[92],"datasets":[93],"with":[94],"missing":[95],"information.":[97],"The":[98,192],"proposed":[99],"method":[100],"employs":[101],"supervised":[103],"approach":[105],"based":[106],"random":[108],"forests":[109],"that":[110,159],"addresses":[111],"as":[115],"classification":[117,155],"task.":[118],"Using":[119],"dataset":[121],"Netherlands":[124],"Chamber":[125],"Commerce,":[127],"containing":[128],"over":[129],"1.5":[130],"million":[131],"Dutch":[135],"companies,":[136],"created":[138],"an":[139],"adequately-performing":[140],"prediction.":[145],"By":[146],"assessing":[147],"features":[149],"instrumental":[151],"final":[154],"model,":[156],"found":[158],"small":[161],"number":[162],"attributes":[164],"is":[165,212],"crucial":[166],"majority":[170],"sectors.":[173],"Interestingly,":[174],"some":[176],"cases":[177],"presence":[179],"or":[180],"absence":[181],"feature":[184],"was":[185],"more":[186],"important":[187],"than":[188],"value":[190],"itself.":[191],"resulting":[193],"insights":[194],"also":[196],"prove":[197],"useful":[198],"accounting,":[200],"where":[201],"relation":[203],"between":[204],"characteristics":[208],"company":[211],"frequently":[214],"studied":[215],"topic.":[216]},"counts_by_year":[{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
