{"id":"https://openalex.org/W4406611335","doi":"https://doi.org/10.1109/smc54092.2024.10831836","title":"MFFLEN: Multi-Label Text Classification Based on Multi-Feature Fusion and Label Embedding","display_name":"MFFLEN: Multi-Label Text Classification Based on Multi-Feature Fusion and Label Embedding","publication_year":2024,"publication_date":"2024-10-06","ids":{"openalex":"https://openalex.org/W4406611335","doi":"https://doi.org/10.1109/smc54092.2024.10831836"},"language":"en","primary_location":{"id":"doi:10.1109/smc54092.2024.10831836","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc54092.2024.10831836","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5111319776","display_name":"Qiliang Gu","orcid":null},"institutions":[{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]},{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiliang Gu","raw_affiliation_strings":["Ministry of Education, Shandong Computer Science Center, Qilu University of Technology (Shandong Academy of Sciences),Key Laboratory of Computing Power Network and Information Security,Jinan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ministry of Education, Shandong Computer Science Center, Qilu University of Technology (Shandong Academy of Sciences),Key Laboratory of Computing Power Network and Information Security,Jinan,China","institution_ids":["https://openalex.org/I152269853","https://openalex.org/I4210142748"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087911800","display_name":"Shuo Zhao","orcid":"https://orcid.org/0000-0003-0537-8531"},"institutions":[{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]},{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuo Zhao","raw_affiliation_strings":["Ministry of Education, Shandong Computer Science Center, Qilu University of Technology (Shandong Academy of Sciences),Key Laboratory of Computing Power Network and Information Security,Jinan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ministry of Education, Shandong Computer Science Center, Qilu University of Technology (Shandong Academy of Sciences),Key Laboratory of Computing Power Network and Information Security,Jinan,China","institution_ids":["https://openalex.org/I152269853","https://openalex.org/I4210142748"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103091680","display_name":"Jianqiang Zhang","orcid":"https://orcid.org/0000-0003-0912-2082"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianqiang Zhang","raw_affiliation_strings":["Shandong Branch of China Mobile Communication Group Design Institute Co.,Jinan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong Branch of China Mobile Communication Group Design Institute Co.,Jinan,China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102703948","display_name":"Gongpeng Song","orcid":null},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gongpeng Song","raw_affiliation_strings":["Shandong Branch of China Mobile Communication Group Design Institute Co.,Jinan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong Branch of China Mobile Communication Group Design Institute Co.,Jinan,China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016391596","display_name":"Qin Lu","orcid":"https://orcid.org/0000-0002-9092-2476"},"institutions":[{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]},{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qin Lu","raw_affiliation_strings":["Ministry of Education, Shandong Computer Science Center, Qilu University of Technology (Shandong Academy of Sciences),Key Laboratory of Computing Power Network and Information Security,Jinan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ministry of Education, Shandong Computer Science Center, Qilu University of Technology (Shandong Academy of Sciences),Key Laboratory of Computing Power Network and Information Security,Jinan,China","institution_ids":["https://openalex.org/I152269853","https://openalex.org/I4210142748"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28867621,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3097","last_page":"3103"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9634000062942505,"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":0.9634000062942505,"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/multi-label-classification","display_name":"Multi-label classification","score":0.8831077218055725},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7484749555587769},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6415197253227234},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5765812993049622},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5532219409942627},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.504592776298523},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4938662648200989}],"concepts":[{"id":"https://openalex.org/C2776482837","wikidata":"https://www.wikidata.org/wiki/Q3553958","display_name":"Multi-label classification","level":2,"score":0.8831077218055725},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7484749555587769},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6415197253227234},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5765812993049622},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5532219409942627},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.504592776298523},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4938662648200989},{"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":1,"locations":[{"id":"doi:10.1109/smc54092.2024.10831836","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc54092.2024.10831836","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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":20,"referenced_works":["https://openalex.org/W2119466907","https://openalex.org/W2740721704","https://openalex.org/W2890026792","https://openalex.org/W2964142373","https://openalex.org/W2977487347","https://openalex.org/W2997050424","https://openalex.org/W3076947077","https://openalex.org/W3121217868","https://openalex.org/W3127362468","https://openalex.org/W3130747775","https://openalex.org/W4200260392","https://openalex.org/W4225787342","https://openalex.org/W4283366853","https://openalex.org/W4289313402","https://openalex.org/W4295296320","https://openalex.org/W4308112365","https://openalex.org/W4320517096","https://openalex.org/W4385245566","https://openalex.org/W6767075311","https://openalex.org/W6844794680"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W2037549926","https://openalex.org/W2345479200","https://openalex.org/W2183306018","https://openalex.org/W2849310602","https://openalex.org/W3006008237","https://openalex.org/W4404781601","https://openalex.org/W2419146053","https://openalex.org/W4388890789","https://openalex.org/W3045290893"],"abstract_inverted_index":{"To":[0],"address":[1],"the":[2,15,39,74,82,88,94,101,105,108,111,122,159,195,209],"challenges":[3],"associated":[4],"with":[5,81],"insufficiently":[6],"extracting":[7,31],"and":[8,20,22,56,107,132,181,200,203,205,215],"utilizing":[9],"features":[10,131,167,178],"at":[11],"different":[12,175],"levels,":[13],"overlooking":[14],"connection":[16,103],"between":[17,104],"label":[18,65,76],"meanings":[19],"text,":[21,83],"facing":[23],"problems":[24],"of":[25,41,73,93,97,177],"over-compression":[26],"or":[27],"information":[28,33],"loss":[29],"when":[30],"global":[32],"using":[34,188],"recurrent":[35],"neural":[36],"networks":[37],"in":[38],"field":[40],"multi-label":[42,182],"text":[43,106,183],"categorization,":[44],"this":[45],"paper":[46],"introduces":[47],"an":[48,133],"innovative":[49],"model":[50,96,123,197],"known":[51],"as":[52],"MFFLEN":[53,196],"(MultiFeature":[54],"Fusion":[55],"Label":[57],"Embedding":[58],"Neural":[59],"Network).":[60],"First,":[61],"a":[62,125,189],"back-translated":[63,70],"enhanced":[64],"set":[66],"is":[67,84,147,221],"constructed":[68],"by":[69],"splicing":[71],"enhancement":[72],"original":[75],"set.":[77],"This":[78],"set,":[79],"together":[80],"then":[85,156],"input":[86],"into":[87,158],"embedding":[89,134],"layer,":[90],"which":[91,154,220],"consists":[92],"pre-trained":[95],"bert-baseChinese,":[98],"thus":[99],"establishing":[100],"initial":[102],"labels":[109],"within":[110],"same":[112],"vector":[113],"space.":[114],"Then,":[115],"to":[116,128,136,149,162],"comprehensively":[117],"extract":[118,129,137,150,164],"multi-level":[119],"semantic":[120],"features,":[121,153],"uses":[124],"convolutional":[126],"layer":[127,135,146,161],"local":[130],"sentence-level":[138],"features.":[139],"A":[140],"bidirectional":[141],"attention":[142,160],"embedded":[143],"GRU":[144],"(BAE-GRU)":[145],"used":[148],"hybrid":[151,165],"finegrained":[152],"are":[155,179,186],"fed":[157],"further":[163],"labeled":[166],"based":[168],"on":[169,208],"labeling":[170],"information.":[171],"Finally,":[172],"these":[173],"three":[174],"types":[176],"fused":[180],"classification":[184],"results":[185],"obtained":[187],"classifier.":[190],"The":[191],"experiments":[192],"proved":[193],"that":[194],"achieved":[198],"73.82%":[199],"88.44%":[201],"macro-F1":[202],"88.00%":[204],"88.86%":[206],"micro-F1":[207],"two":[210],"datasets":[211],"CAIL":[212,216],"2018":[213,217],"Small":[214],"Split,":[218],"respectively,":[219],"better":[222],"than":[223],"other":[224],"baseline":[225],"models.":[226]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
