{"id":"https://openalex.org/W3155441061","doi":"https://doi.org/10.1109/tnnls.2021.3069647","title":"Effective Collaborative Representation Learning for Multilabel Text Categorization","display_name":"Effective Collaborative Representation Learning for Multilabel Text Categorization","publication_year":2021,"publication_date":"2021-04-14","ids":{"openalex":"https://openalex.org/W3155441061","doi":"https://doi.org/10.1109/tnnls.2021.3069647","mag":"3155441061","pmid":"https://pubmed.ncbi.nlm.nih.gov/33852392"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2021.3069647","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3069647","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5005207362","display_name":"Hao Wu","orcid":"https://orcid.org/0000-0002-3696-9281"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Wu","raw_affiliation_strings":["School of Information Science and Engineering, Yunnan University, Kunming, China"],"raw_orcid":"https://orcid.org/0000-0002-3696-9281","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Yunnan University, Kunming, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038000287","display_name":"Shaowei Qin","orcid":"https://orcid.org/0000-0002-9774-0851"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaowei Qin","raw_affiliation_strings":["School of Information Science and Engineering, Yunnan University, Kunming, China"],"raw_orcid":"https://orcid.org/0000-0002-9774-0851","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Yunnan University, Kunming, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080341760","display_name":"Rencan Nie","orcid":"https://orcid.org/0000-0003-0568-1231"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]},{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rencan Nie","raw_affiliation_strings":["School of Information Science and Engineering, Yunnan University, Kunming, China","School of Automation, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0003-0568-1231","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Yunnan University, Kunming, China","institution_ids":["https://openalex.org/I189210763"]},{"raw_affiliation_string":"School of Automation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017808266","display_name":"Jinde Cao","orcid":"https://orcid.org/0000-0003-3133-7119"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]},{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN","KR"],"is_corresponding":false,"raw_author_name":"Jinde Cao","raw_affiliation_strings":["School of Mathematics, Southeast University, Nanjing, China","Yonsei Frontier Laboratory, Yonsei University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-3133-7119","affiliations":[{"raw_affiliation_string":"School of Mathematics, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"Yonsei Frontier Laboratory, Yonsei University, Seoul, South Korea","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039427759","display_name":"Sergey Gorbachev","orcid":"https://orcid.org/0000-0001-8096-1327"},"institutions":[{"id":"https://openalex.org/I196355604","display_name":"National Research Tomsk State University","ror":"https://ror.org/02he2nc27","country_code":"RU","type":"education","lineage":["https://openalex.org/I196355604"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Sergey Gorbachev","raw_affiliation_strings":["Department of Innovative Technologies, National Research Tomsk State University, Tomsk, Russia"],"raw_orcid":"https://orcid.org/0000-0001-8096-1327","affiliations":[{"raw_affiliation_string":"Department of Innovative Technologies, National Research Tomsk State University, Tomsk, Russia","institution_ids":["https://openalex.org/I196355604"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.3789,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.90413255,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"33","issue":"10","first_page":"5200","last_page":"5214"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":1.0,"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":1.0,"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/T10028","display_name":"Topic Modeling","score":0.9983000159263611,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9937999844551086,"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/computer-science","display_name":"Computer science","score":0.7195000648498535},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6722283363342285},{"id":"https://openalex.org/keywords/pointwise-mutual-information","display_name":"Pointwise mutual information","score":0.6576189398765564},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.645100474357605},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5693586468696594},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.5497435331344604},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.49674779176712036},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.4699820578098297},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.46262288093566895},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4531276226043701},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.44515687227249146},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4312606751918793},{"id":"https://openalex.org/keywords/pointwise","display_name":"Pointwise","score":0.4303205907344818},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.425035297870636},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.19247177243232727},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10573175549507141}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7195000648498535},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6722283363342285},{"id":"https://openalex.org/C7797323","wikidata":"https://www.wikidata.org/wiki/Q3798612","display_name":"Pointwise mutual information","level":3,"score":0.6576189398765564},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.645100474357605},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5693586468696594},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.5497435331344604},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49674779176712036},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.4699820578098297},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.46262288093566895},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4531276226043701},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.44515687227249146},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4312606751918793},{"id":"https://openalex.org/C2777984123","wikidata":"https://www.wikidata.org/wiki/Q9248237","display_name":"Pointwise","level":2,"score":0.4303205907344818},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.425035297870636},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.19247177243232727},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10573175549507141},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2021.3069647","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2021.3069647","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:33852392","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33852392","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1317898902","display_name":"\u5927\u6570\u636e\u73af\u5883\u4e0b\u7684\u4e91\u5357\u8fb9\u7586\u6c11\u65cf\u6587\u5316\u8ba1\u7b97\u652f\u6491\u6280\u672f\u4e0e\u5b9e\u8bc1\u7814\u7a76","funder_award_id":"U1802271","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3863222636","display_name":"\u9762\u5411\u591a\u6e90\u56fe\u50cf\u878d\u5408\u8d21\u732e\u4f30\u8ba1\u7684\u591a\u6e90\u8109\u51b2\u4fe1\u606f\u4ea4\u6362\u7f16\u7801\u4e0e\u5206\u6570\u9636\u53d8\u5206\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61966037","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4279245431","display_name":"\u9762\u5411Web API\u6316\u6398\u7684\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\u6784\u5efa\u7814\u7a76","funder_award_id":"61962061","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4585534567","display_name":"\u57fa\u4e8e\u7fa4\u4f53\u667a\u80fd\u7684\u5206\u5e03\u5f0f\u4f18\u5316\u7406\u8bba\u3001\u65b9\u6cd5\u53ca\u5e94\u7528\u7814\u7a76","funder_award_id":"61833005","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7032097175","display_name":"\u89c6\u611f\u77e5\u6a21\u578b\u8109\u51b2\u8026\u5408\u795e\u7ecf\u7f51\u7edc\u7684\u56fe\u50cf\u7279\u5f81\u63d0\u53d6\u53ca\u5e94\u7528\u7814\u7a76","funder_award_id":"61463052","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"},{"id":"https://openalex.org/F4320324731","display_name":"Yunnan University","ror":"https://ror.org/0040axw97"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1576514601","https://openalex.org/W1826494934","https://openalex.org/W1832693441","https://openalex.org/W2061873838","https://openalex.org/W2094934653","https://openalex.org/W2095705004","https://openalex.org/W2105482032","https://openalex.org/W2113552117","https://openalex.org/W2135790056","https://openalex.org/W2146241755","https://openalex.org/W2147152072","https://openalex.org/W2157881433","https://openalex.org/W2250539671","https://openalex.org/W2318991869","https://openalex.org/W2470673105","https://openalex.org/W2515144511","https://openalex.org/W2517194566","https://openalex.org/W2604675517","https://openalex.org/W2734389934","https://openalex.org/W2739996966","https://openalex.org/W2911379778","https://openalex.org/W2949448715","https://openalex.org/W2962946486","https://openalex.org/W2963912736","https://openalex.org/W2963921497","https://openalex.org/W2964046515","https://openalex.org/W3011614468","https://openalex.org/W3080994088","https://openalex.org/W3156333129","https://openalex.org/W4248524623","https://openalex.org/W6600882167","https://openalex.org/W6607802380","https://openalex.org/W6640212811","https://openalex.org/W6674330103","https://openalex.org/W6678885109","https://openalex.org/W6685974025","https://openalex.org/W6713582272","https://openalex.org/W6727249380","https://openalex.org/W6729752019","https://openalex.org/W6739365718","https://openalex.org/W6767075311","https://openalex.org/W6774690220"],"related_works":["https://openalex.org/W3009238340","https://openalex.org/W4315777907","https://openalex.org/W3197060662","https://openalex.org/W4221136938","https://openalex.org/W4213225422","https://openalex.org/W2908875379","https://openalex.org/W4206762304","https://openalex.org/W4297725807","https://openalex.org/W3158586592","https://openalex.org/W4206984194"],"abstract_inverted_index":{"With":[0],"the":[1,22,40,97,111,116,129],"booming":[2],"of":[3,21,42,62,70,103,128,131],"deep":[4,77,143],"learning,":[5],"massive":[6],"attention":[7,31],"has":[8],"been":[9],"paid":[10],"to":[11,115],"developing":[12],"neural":[13,74,112],"models":[14],"for":[15,66,76,85,95,110],"multilabel":[16],"text":[17],"categorization":[18],"(MLTC).":[19],"Most":[20],"works":[23],"concentrate":[24],"on":[25,119],"disclosing":[26],"word-label":[27],"relationship,":[28],"while":[29],"less":[30],"is":[32],"taken":[33],"in":[34,57,138],"exploiting":[35],"global":[36],"clues,":[37],"particularly":[38],"with":[39,140],"relationship":[41,130],"document-label.":[43],"To":[44],"address":[45],"this":[46,58],"limitation,":[47],"we":[48],"propose":[49],"an":[50,92],"effective":[51],"collaborative":[52],"representation":[53],"learning":[54,107],"(CRL)":[55],"model":[56],"article.":[59],"CRL":[60,123],"consists":[61],"a":[63,73],"factorization":[64],"component":[65,75],"generating":[67],"shallow":[68],"representations":[69],"documents":[71],"and":[72,79,105,133],"text-encoding":[78],"classification.":[80],"We":[81],"have":[82],"developed":[83],"strategies":[84],"jointly":[86],"training":[87],"those":[88],"two":[89],"components,":[90],"including":[91],"alternating-least-squares-based":[93],"approach":[94],"factorizing":[96],"pointwise":[98],"mutual":[99],"information":[100],"(PMI)":[101],"matrix":[102],"label-document":[104],"multitask":[106],"(MTL)":[108],"strategy":[109],"component.":[113],"According":[114],"experimental":[117],"results":[118],"six":[120],"data":[121],"sets,":[122],"can":[124],"explicitly":[125],"take":[126],"advantage":[127],"document-label":[132],"achieve":[134],"competitive":[135],"classification":[136],"performance":[137],"comparison":[139],"some":[141],"state-of-the-art":[142],"methods.":[144]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":5}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
