{"id":"https://openalex.org/W2568060981","doi":"https://doi.org/10.1109/besc.2016.7804484","title":"A comparison study of semi-supervised SVM algorithms for small business credit prediction","display_name":"A comparison study of semi-supervised SVM algorithms for small business credit prediction","publication_year":2016,"publication_date":"2016-11-01","ids":{"openalex":"https://openalex.org/W2568060981","doi":"https://doi.org/10.1109/besc.2016.7804484","mag":"2568060981"},"language":"en","primary_location":{"id":"doi:10.1109/besc.2016.7804484","is_oa":false,"landing_page_url":"https://doi.org/10.1109/besc.2016.7804484","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Behavioral, Economic and Socio-cultural Computing (BESC)","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/A5100436682","display_name":"Jie Zhang","orcid":"https://orcid.org/0000-0002-0364-0404"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jie Zhang","raw_affiliation_strings":["School of Computer Science & Technology, Wuhan University of Technology, Wuhan, china"],"affiliations":[{"raw_affiliation_string":"School of Computer Science & Technology, Wuhan University of Technology, Wuhan, china","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100412848","display_name":"Lin Li","orcid":"https://orcid.org/0000-0002-2149-2898"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Li","raw_affiliation_strings":["School of Computer Science & Technology, Wuhan University of Technology, Wuhan, china"],"affiliations":[{"raw_affiliation_string":"School of Computer Science & Technology, Wuhan University of Technology, Wuhan, china","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101312657","display_name":"Ge Zhu","orcid":"https://orcid.org/0000-0003-0994-5476"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ge Zhu","raw_affiliation_strings":["School of Computer Science & Technology, Wuhan University of Technology, Wuhan, china"],"affiliations":[{"raw_affiliation_string":"School of Computer Science & Technology, Wuhan University of Technology, Wuhan, china","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101630444","display_name":"Xiangfu Meng","orcid":"https://orcid.org/0000-0001-7879-2368"},"institutions":[{"id":"https://openalex.org/I176808543","display_name":"Liaoning Technical University","ror":"https://ror.org/01n2bd587","country_code":"CN","type":"education","lineage":["https://openalex.org/I176808543"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangfu Meng","raw_affiliation_strings":["School of Electronic and Information Engineering, Liaoning Technical University, Huludao, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Liaoning Technical University, Huludao, China","institution_ids":["https://openalex.org/I176808543"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013657140","display_name":"Qing Xie","orcid":"https://orcid.org/0000-0003-4530-588X"},"institutions":[{"id":"https://openalex.org/I176808543","display_name":"Liaoning Technical University","ror":"https://ror.org/01n2bd587","country_code":"CN","type":"education","lineage":["https://openalex.org/I176808543"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Xie","raw_affiliation_strings":["School of Electronic and Information Engineering, Liaoning Technical University, Huludao, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Liaoning Technical University, Huludao, China","institution_ids":["https://openalex.org/I176808543"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100436682"],"corresponding_institution_ids":["https://openalex.org/I196699116"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.23765141,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"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":0.9952999949455261,"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":0.9952999949455261,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6926711797714233},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6076651811599731},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5880727171897888},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.5312792062759399},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5153569579124451},{"id":"https://openalex.org/keywords/small-business","display_name":"Small business","score":0.44273343682289124},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.43477416038513184},{"id":"https://openalex.org/keywords/loan","display_name":"Loan","score":0.4186537265777588},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4182496964931488},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.412733793258667},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.26975446939468384}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6926711797714233},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6076651811599731},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5880727171897888},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.5312792062759399},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5153569579124451},{"id":"https://openalex.org/C2777973936","wikidata":"https://www.wikidata.org/wiki/Q1109680","display_name":"Small business","level":2,"score":0.44273343682289124},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.43477416038513184},{"id":"https://openalex.org/C2777764128","wikidata":"https://www.wikidata.org/wiki/Q189539","display_name":"Loan","level":2,"score":0.4186537265777588},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4182496964931488},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.412733793258667},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.26975446939468384}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/besc.2016.7804484","is_oa":false,"landing_page_url":"https://doi.org/10.1109/besc.2016.7804484","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Behavioral, Economic and Socio-cultural Computing (BESC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W92894758","https://openalex.org/W1983320747","https://openalex.org/W2054489011","https://openalex.org/W2107275319","https://openalex.org/W2107968230","https://openalex.org/W2111504671","https://openalex.org/W2122565017","https://openalex.org/W2128097790","https://openalex.org/W2147025064","https://openalex.org/W2148603752","https://openalex.org/W2161877964","https://openalex.org/W3122744061","https://openalex.org/W6603760306","https://openalex.org/W6675920320","https://openalex.org/W6676348322","https://openalex.org/W6677987841","https://openalex.org/W6681719339"],"related_works":["https://openalex.org/W2033184148","https://openalex.org/W2747895175","https://openalex.org/W198774406","https://openalex.org/W2614669534","https://openalex.org/W2104406636","https://openalex.org/W2123014508","https://openalex.org/W3132139544","https://openalex.org/W2105512057","https://openalex.org/W4252625449","https://openalex.org/W3131201603"],"abstract_inverted_index":{"The":[0,117],"small":[1,22,34,39,86,109,121,133,179],"companies":[2,35,63,104,134],"become":[3],"increasingly":[4],"important":[5],"in":[6,20],"bank's":[7,15],"lending":[8],"business.":[9],"But":[10],"the":[11,30,33,48,55,62,73,97,103,139,143,147,176,198,202,211],"challenge":[12],"is":[13,18,76,125,135,150,214],"how":[14],"credit":[16,67,123,130,145,149,191],"assessment":[17],"made":[19],"a":[21,38,85,186],"amount":[23,40],"of":[24,41,61,101,110,120,132,142,178,188],"time":[25,80],"and":[26,64,81,146,161,163,169,197,216],"money.":[27],"Compare":[28],"with":[29,193],"big":[31],"companies,":[32],"often":[36],"need":[37],"cash":[42],"flow.":[43],"They":[44],"may":[45],"not":[46],"provide":[47],"complete":[49],"certificates":[50],"or":[51],"documents,":[52],"so":[53],"that":[54,201],"bank":[56],"has":[57],"to":[58,78,83,90,174],"collect":[59],"information":[60],"evaluate":[65],"their":[66],"rating":[68],"especially":[69,88],"by":[70],"experts.":[71],"For":[72],"bank,":[74],"it":[75],"worthless":[77],"spend":[79],"money":[82],"investigate":[84],"company,":[87],"just":[89],"lend":[91],"several":[92],"hundred":[93],"thousand":[94],"dollars.":[95],"In":[96,181],"real":[98],"life,":[99],"credits":[100,177],"most":[102],"are":[105],"good,":[106],"while":[107,127],"only":[108],"them":[111],"cannot":[112],"repay":[113],"for":[114],"some":[115],"reasons.":[116],"few":[118],"number":[119],"companies'":[122],"data":[124,131,212],"valuable":[126],"considerable":[128],"unknowing":[129],"within":[136],"reach.":[137],"Therefore,":[138],"binary":[140],"classification":[141,196],"good":[144],"bad":[148],"asymmetry.":[151,217],"we":[152,184],"choose":[153],"supervised":[154],"learning":[155,165],"algorithm":[156,166],"(Regularized":[157],"Least":[158],"Squares":[159],"Classification":[160],"SVM)":[162,173],"semi-supervised":[164],"(Transductive":[167],"SVM":[168,206],"Deterministic":[170,203],"Annealing":[171,204],"Semi-supervised":[172,205],"predict":[175],"companies.":[180],"this":[182],"paper,":[183],"conduct":[185],"series":[187],"experiments":[189],"on":[190],"datasets":[192],"different":[194],"proportion":[195],"results":[199],"show":[200],"(DAS3VM)":[207],"performance":[208],"better":[209],"when":[210],"set":[213],"rare":[215]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}