{"id":"https://openalex.org/W4292829391","doi":"https://doi.org/10.1145/3548636.3548652","title":"Multi-label Learning with User Credit Data in China Based on MLKNN","display_name":"Multi-label Learning with User Credit Data in China Based on MLKNN","publication_year":2022,"publication_date":"2022-06-23","ids":{"openalex":"https://openalex.org/W4292829391","doi":"https://doi.org/10.1145/3548636.3548652"},"language":"en","primary_location":{"id":"doi:10.1145/3548636.3548652","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3548636.3548652","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 4th International Conference on Information Technology and Computer Communications (ITCC)","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/A5066719900","display_name":"Zhuangyi Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I137867983","display_name":"Central University of Finance and Economics","ror":"https://ror.org/008e3hf02","country_code":"CN","type":"education","lineage":["https://openalex.org/I137867983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuangyi Zhang","raw_affiliation_strings":["School of Management Science and Engineering, Central University of Finance and Economics, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Management Science and Engineering, Central University of Finance and Economics, China","institution_ids":["https://openalex.org/I137867983"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086894713","display_name":"Lu Han","orcid":"https://orcid.org/0000-0002-1120-3220"},"institutions":[{"id":"https://openalex.org/I137867983","display_name":"Central University of Finance and Economics","ror":"https://ror.org/008e3hf02","country_code":"CN","type":"education","lineage":["https://openalex.org/I137867983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lu Han","raw_affiliation_strings":["School of Management Science and Engineering, Central University of Finance and Economics, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Management Science and Engineering, Central University of Finance and Economics, China","institution_ids":["https://openalex.org/I137867983"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030677851","display_name":"Muzi Chen","orcid":"https://orcid.org/0000-0003-2078-2014"},"institutions":[{"id":"https://openalex.org/I137867983","display_name":"Central University of Finance and Economics","ror":"https://ror.org/008e3hf02","country_code":"CN","type":"education","lineage":["https://openalex.org/I137867983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Muzi Chen","raw_affiliation_strings":["School of Management Science and Engineering, Central University of Finance and Economics, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Management Science and Engineering, Central University of Finance and Economics, China","institution_ids":["https://openalex.org/I137867983"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I137867983"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"105","last_page":"111"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9997000098228455,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9997000098228455,"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/T11644","display_name":"Spam and Phishing Detection","score":0.9811000227928162,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9757999777793884,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/sample","display_name":"Sample (material)","score":0.7133855819702148},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6469225883483887},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5152721405029297},{"id":"https://openalex.org/keywords/credit-history","display_name":"Credit history","score":0.4996523857116699},{"id":"https://openalex.org/keywords/china","display_name":"China","score":0.44366633892059326},{"id":"https://openalex.org/keywords/credit-reference","display_name":"Credit reference","score":0.4409610331058502},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.43816953897476196},{"id":"https://openalex.org/keywords/credit-enhancement","display_name":"Credit enhancement","score":0.4339093267917633},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.37708359956741333},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3704613447189331},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36521655321121216},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.3348483443260193},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3225308060646057},{"id":"https://openalex.org/keywords/credit-risk","display_name":"Credit risk","score":0.27767282724380493},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.14771848917007446}],"concepts":[{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.7133855819702148},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6469225883483887},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5152721405029297},{"id":"https://openalex.org/C68842666","wikidata":"https://www.wikidata.org/wiki/Q1070699","display_name":"Credit history","level":2,"score":0.4996523857116699},{"id":"https://openalex.org/C191935318","wikidata":"https://www.wikidata.org/wiki/Q148","display_name":"China","level":2,"score":0.44366633892059326},{"id":"https://openalex.org/C24308983","wikidata":"https://www.wikidata.org/wiki/Q5183781","display_name":"Credit reference","level":3,"score":0.4409610331058502},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.43816953897476196},{"id":"https://openalex.org/C31348098","wikidata":"https://www.wikidata.org/wiki/Q3423719","display_name":"Credit enhancement","level":4,"score":0.4339093267917633},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.37708359956741333},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3704613447189331},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36521655321121216},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.3348483443260193},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3225308060646057},{"id":"https://openalex.org/C178350159","wikidata":"https://www.wikidata.org/wiki/Q162714","display_name":"Credit risk","level":2,"score":0.27767282724380493},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.14771848917007446},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3548636.3548652","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3548636.3548652","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 4th International Conference on Information Technology and Computer Communications (ITCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5724344245","display_name":"\u4fe1\u8d37\u6587\u672c\u7c7b\u66ff\u4ee3\u6570\u636e\u7684\u4fe1\u7528\u8bc4\u4f30\u65b9\u6cd5\u7814\u7a76","funder_award_id":"72101279","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1753402186","https://openalex.org/W1953606363","https://openalex.org/W1999954155","https://openalex.org/W2052684427","https://openalex.org/W2097706152","https://openalex.org/W2156935079","https://openalex.org/W3004553288","https://openalex.org/W3158777740","https://openalex.org/W6631445940","https://openalex.org/W6683097776","https://openalex.org/W6773366436"],"related_works":["https://openalex.org/W4206960362","https://openalex.org/W2385067002","https://openalex.org/W2390669606","https://openalex.org/W2380069629","https://openalex.org/W2356147009","https://openalex.org/W2376783430","https://openalex.org/W2356651304","https://openalex.org/W623125919","https://openalex.org/W2363741405","https://openalex.org/W2384142884"],"abstract_inverted_index":{"Aiming":[0],"at":[1],"the":[2,26,34,39,42,51,58,61,83,113],"problem":[3],"of":[4,13,41,48,54,57,76,89,100,118],"numerous":[5],"variables":[6],"in":[7,79,140],"credit":[8,35,77,90,101,107,119,125,143],"data,":[9,15],"a":[10],"large":[11],"amount":[12],"sample":[14,62],"and":[16,103,142],"inability":[17],"to":[18,29,38,106,124],"intuitively":[19],"reflect":[20],"user":[21],"portraits.":[22],"This":[23,127],"paper":[24,70],"uses":[25],"MLKNN":[27],"algorithm":[28,43,59],"perform":[30],"multi-label":[31],"learning":[32],"on":[33,60],"data.":[36],"According":[37],"results":[40],"training":[44],"under":[45],"24":[46],"sets":[47],"k":[49],"values,":[50],"optimal":[52],"number":[53],"neighbor":[55],"samples":[56],"set":[63],"is":[64],"14.":[65],"On":[66],"this":[67,69],"basis,":[68],"further":[71],"analyzes":[72],"The":[73],"general":[74],"portrait":[75],"users":[78,91,93,114],"my":[80],"country":[81],"has":[82],"following":[84],"characteristics:":[85],"more":[86,122],"than":[87],"50%":[88],"are":[92],"with":[94,115],"stable":[95],"personal":[96],"development,":[97],"low":[98],"frequency":[99,117],"activities,":[102],"low-to-medium":[104],"attention":[105,123],"status.":[108,126],"Meanwhile,":[109],"we":[110],"find":[111],"that":[112],"higher":[116],"activities":[120],"pay":[121],"research":[128],"can":[129],"provide":[130],"some":[131],"reference":[132],"for":[133],"commercial":[134],"banks":[135],"or":[136],"other":[137],"financial":[138],"institutions":[139],"lending":[141],"management.":[144]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}