{"id":"https://openalex.org/W4400643956","doi":"https://doi.org/10.1109/tfuzz.2024.3427801","title":"A Fuzzy Multigranularity Convolutional Neural Network With Double Attention Mechanisms for Measuring Semantic Textual Similarity","display_name":"A Fuzzy Multigranularity Convolutional Neural Network With Double Attention Mechanisms for Measuring Semantic Textual Similarity","publication_year":2024,"publication_date":"2024-07-15","ids":{"openalex":"https://openalex.org/W4400643956","doi":"https://doi.org/10.1109/tfuzz.2024.3427801"},"language":"en","primary_location":{"id":"doi:10.1109/tfuzz.2024.3427801","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2024.3427801","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"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 Fuzzy Systems","raw_type":"journal-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/A5005495416","display_name":"Butian Zhao","orcid":"https://orcid.org/0000-0001-9278-6685"},"institutions":[{"id":"https://openalex.org/I17747738","display_name":"Beijing University of Chinese Medicine","ror":"https://ror.org/05damtm70","country_code":"CN","type":"education","lineage":["https://openalex.org/I17747738"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Butian Zhao","raw_affiliation_strings":["School of Management, Beijing University of Chinese Medicine, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9278-6685","affiliations":[{"raw_affiliation_string":"School of Management, Beijing University of Chinese Medicine, Beijing, China","institution_ids":["https://openalex.org/I17747738"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008891083","display_name":"Runtong Zhang","orcid":"https://orcid.org/0000-0003-0246-5058"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Runtong Zhang","raw_affiliation_strings":["School of Economics and Management, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0246-5058","affiliations":[{"raw_affiliation_string":"School of Economics and Management, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091453895","display_name":"Kaiyuan Bai","orcid":"https://orcid.org/0000-0002-2344-3627"},"institutions":[{"id":"https://openalex.org/I4210136246","display_name":"China Telecom (China)","ror":"https://ror.org/03jgnzt20","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210136246"]},{"id":"https://openalex.org/I4387153335","display_name":"China Telecom","ror":"https://ror.org/05p67dv18","country_code":null,"type":"company","lineage":["https://openalex.org/I4387153335"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaiyuan Bai","raw_affiliation_strings":["China Telecom Research Institute, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-2344-3627","affiliations":[{"raw_affiliation_string":"China Telecom Research Institute, Beijing, China","institution_ids":["https://openalex.org/I4210136246","https://openalex.org/I4387153335"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2006,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.81670959,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"32","issue":"10","first_page":"5762","last_page":"5776"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9574000239372253,"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":0.9574000239372253,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9320999979972839,"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/granularity","display_name":"Granularity","score":0.7862398624420166},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7686628103256226},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7024180293083191},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.6293542385101318},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.620478093624115},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5706986784934998},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5085209608078003},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44223445653915405},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4112963080406189},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40835580229759216},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.37962520122528076},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3262789845466614},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.14621716737747192}],"concepts":[{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.7862398624420166},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7686628103256226},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7024180293083191},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.6293542385101318},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.620478093624115},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5706986784934998},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5085209608078003},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44223445653915405},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4112963080406189},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40835580229759216},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.37962520122528076},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3262789845466614},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.14621716737747192},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tfuzz.2024.3427801","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2024.3427801","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"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 Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.47999998927116394}],"awards":[{"id":"https://openalex.org/G723782673","display_name":null,"funder_award_id":"62173025","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":53,"referenced_works":["https://openalex.org/W333500581","https://openalex.org/W384920120","https://openalex.org/W1980776243","https://openalex.org/W1984968544","https://openalex.org/W1996054841","https://openalex.org/W2044770310","https://openalex.org/W2064675550","https://openalex.org/W2105482032","https://openalex.org/W2110485445","https://openalex.org/W2112796928","https://openalex.org/W2118004980","https://openalex.org/W2147152072","https://openalex.org/W2165612380","https://openalex.org/W2168022112","https://openalex.org/W2171590421","https://openalex.org/W2211192759","https://openalex.org/W2251427843","https://openalex.org/W2254842198","https://openalex.org/W2290034161","https://openalex.org/W2469060249","https://openalex.org/W2508865106","https://openalex.org/W2587019100","https://openalex.org/W2593833795","https://openalex.org/W2597485909","https://openalex.org/W2739351760","https://openalex.org/W2900874631","https://openalex.org/W2922382144","https://openalex.org/W2963149412","https://openalex.org/W2964082993","https://openalex.org/W3009234749","https://openalex.org/W3009849671","https://openalex.org/W3010763821","https://openalex.org/W3025337893","https://openalex.org/W3104033643","https://openalex.org/W3135685413","https://openalex.org/W3201204403","https://openalex.org/W4225639074","https://openalex.org/W4226127704","https://openalex.org/W4231510805","https://openalex.org/W4285149215","https://openalex.org/W4289752563","https://openalex.org/W4307817449","https://openalex.org/W4308310740","https://openalex.org/W4321763616","https://openalex.org/W4390946929","https://openalex.org/W6605913859","https://openalex.org/W6639619044","https://openalex.org/W6682137061","https://openalex.org/W6730179637","https://openalex.org/W6733081445","https://openalex.org/W6743583902","https://openalex.org/W6755207826","https://openalex.org/W6764398373"],"related_works":["https://openalex.org/W2931688134","https://openalex.org/W2377919138","https://openalex.org/W2378857091","https://openalex.org/W2999756192","https://openalex.org/W103652678","https://openalex.org/W4226090359","https://openalex.org/W2114797768","https://openalex.org/W2380654781","https://openalex.org/W2176214140","https://openalex.org/W2516873349"],"abstract_inverted_index":{"Semantic":[0],"textual":[1],"similarity":[2],"(STS)":[3],"is":[4,232],"a":[5,64,102,132,233],"fundamental":[6],"task":[7],"in":[8,107,242],"the":[9,33,47,79,88,96,139,147,217,225,243],"field":[10],"of":[11,36,49,81,141,219,222],"natural":[12],"language":[13],"processing":[14],"(NLP).":[15],"Recent":[16],"advances":[17],"demonstrate":[18],"that":[19,230],"deep-learning-based":[20],"approaches":[21],"can":[22,160],"achieve":[23],"excitingly":[24],"accurate":[25,172],"STS":[26,75,181,199],"measurement.":[27],"However,":[28],"existing":[29],"studies":[30],"cannot":[31],"capture":[32],"spatial":[34,89,114],"location":[35,115],"important":[37],"information":[38,116],"by":[39,185,190,204],"attention":[40,90],"mechanisms,":[41],"fail":[42],"to":[43,54,73,100,137,164,167,237],"model":[44],"sentences":[45,120],"from":[46,121],"perspective":[48],"overall":[50],"sentences,":[51],"and":[52,92,126,154,157,173,194,202,207],"neglect":[53],"deal":[55],"with":[56,78,95,170,178],"semantic":[57,82,143,210],"fuzziness.":[58,83],"In":[59],"this":[60],"article,":[61],"we":[62],"propose":[63],"novel":[65],"double":[66],"attentive":[67,98],"fuzzy":[68,133,142,148,151,165,239],"convolutional":[69,104],"neural":[70,105],"network":[71,106],"(DAFCNN)":[72],"measure":[74],"more":[76,171],"accurately":[77],"consideration":[80],"This":[84],"article":[85],"first":[86],"introduces":[87],"module":[91,135,221],"combines":[93],"it":[94],"improved":[97],"convolutions":[99],"create":[101],"multigranularity":[103],"DAFCNN,":[108],"which":[109],"not":[110],"only":[111],"extracts":[112],"critical":[113],"but":[117],"also":[118,228],"models":[119],"multiple":[122],"perspectives":[123],"at":[124],"word":[125],"sentence":[127,162],"levels.":[128],"Second,":[129],"DAFCNN":[130,183],"pioneers":[131],"learning":[134],"(FLM)":[136],"fulfill":[138],"extraction":[140],"features.":[144],"By":[145],"using":[146],"membership":[149],"function,":[150],"aggregation":[152],"operator,":[153],"trainable":[155],"parameters":[156],"weights,":[158],"FLM":[159,231],"map":[161],"representations":[163,169],"space":[166],"constitute":[168],"rich":[174],"semantics.":[175],"Third,":[176],"compared":[177],"various":[179],"state-of-the-art":[180],"models,":[182],"decreases":[184],"14.57%":[186],"mean-square":[187],"error,":[188],"increases":[189,203],"4.61%":[191],"Pearson's":[192],"\u03b3":[193],"8.57%":[195],"Spearman's":[196],"\u03c1":[197],"on":[198,209],"score":[200],"datasets,":[201],"3.39%":[205],"accuracy":[206],"2.41%F1-score":[208],"classification":[211],"dataset.":[212],"The":[213],"ablation":[214],"experiment":[215],"demonstrates":[216],"effectiveness":[218],"each":[220],"DAFCNN.":[223],"Finally,":[224],"experimental":[226],"results":[227],"indicate":[229],"promising":[234],"new":[235],"attempt":[236],"incorporate":[238],"set":[240],"theory":[241],"NLP":[244],"field.":[245]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}