{"id":"https://openalex.org/W3014670421","doi":"https://doi.org/10.1109/access.2020.2985098","title":"Semi-Supervised Multi-Granularity CNNs for Text Classification: An Application in Human-Car Interaction","display_name":"Semi-Supervised Multi-Granularity CNNs for Text Classification: An Application in Human-Car Interaction","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3014670421","doi":"https://doi.org/10.1109/access.2020.2985098","mag":"3014670421"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.2985098","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2985098","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09055236.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09055236.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Fen Zhao","orcid":"https://orcid.org/0000-0003-4485-6313"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fen Zhao","raw_affiliation_strings":["School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0003-4485-6313","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057946457","display_name":"Yinguo Li","orcid":"https://orcid.org/0000-0002-6580-7345"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yinguo Li","raw_affiliation_strings":["School of Automation, Chongqing University of Posts and Telecommunications, Chongqing, China","School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-6580-7345","affiliations":[{"raw_affiliation_string":"School of Automation, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]},{"raw_affiliation_string":"School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084139251","display_name":"Ling Bai","orcid":"https://orcid.org/0000-0002-2135-5404"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]},{"id":"https://openalex.org/I98251732","display_name":"McMaster University","ror":"https://ror.org/02fa3aq29","country_code":"CA","type":"education","lineage":["https://openalex.org/I98251732"]}],"countries":["CA","CN"],"is_corresponding":false,"raw_author_name":"Ling Bai","raw_affiliation_strings":["Department of Electrical and Computer Engineering, McMaster University, Hamilton, Canada","School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-2135-5404","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, McMaster University, Hamilton, Canada","institution_ids":["https://openalex.org/I98251732"]},{"raw_affiliation_string":"School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066170793","display_name":"Zhen Tian","orcid":"https://orcid.org/0000-0002-2677-9388"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]},{"id":"https://openalex.org/I98251732","display_name":"McMaster University","ror":"https://ror.org/02fa3aq29","country_code":"CA","type":"education","lineage":["https://openalex.org/I98251732"]}],"countries":["CA","CN"],"is_corresponding":false,"raw_author_name":"Zhen Tian","raw_affiliation_strings":["Department of Electrical and Computer Engineering, McMaster University, Hamilton, Canada","School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-2677-9388","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, McMaster University, Hamilton, Canada","institution_ids":["https://openalex.org/I98251732"]},{"raw_affiliation_string":"School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101465154","display_name":"Xinheng Wang","orcid":"https://orcid.org/0000-0002-0030-1036"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinheng Wang","raw_affiliation_strings":["School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-0030-1036","affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.5215,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.71891431,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"8","issue":null,"first_page":"68000","last_page":"68012"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9983999729156494,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9983999729156494,"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/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9979000091552734,"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":0.8337476253509521},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7874526977539062},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.7852268815040588},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6492911577224731},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6261360049247742},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5979117155075073},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5578387379646301},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5195508599281311},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.49929332733154297},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47133588790893555},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46574342250823975},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.454971581697464},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43419817090034485},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4203207492828369},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4114701747894287}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8337476253509521},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7874526977539062},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.7852268815040588},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6492911577224731},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6261360049247742},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5979117155075073},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5578387379646301},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5195508599281311},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.49929332733154297},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47133588790893555},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46574342250823975},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.454971581697464},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43419817090034485},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4203207492828369},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4114701747894287},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.2985098","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2985098","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09055236.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:654195ce74ce47169652534b34296d65","is_oa":true,"landing_page_url":"https://doaj.org/article/654195ce74ce47169652534b34296d65","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 68000-68012 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.2985098","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2985098","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09055236.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals","score":0.5299999713897705}],"awards":[{"id":"https://openalex.org/G1387382502","display_name":null,"funder_award_id":"BYJS201916","funder_id":"https://openalex.org/F4320322687","funder_display_name":"Chongqing University of Posts and Telecommunications"}],"funders":[{"id":"https://openalex.org/F4320321135","display_name":"Chongqing University","ror":"https://ror.org/023rhb549"},{"id":"https://openalex.org/F4320322687","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3014670421.pdf","grobid_xml":"https://content.openalex.org/works/W3014670421.grobid-xml"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W1493036841","https://openalex.org/W1528361845","https://openalex.org/W1616262590","https://openalex.org/W1966949944","https://openalex.org/W1978874999","https://openalex.org/W2056624866","https://openalex.org/W2063217105","https://openalex.org/W2077997370","https://openalex.org/W2079359777","https://openalex.org/W2090575847","https://openalex.org/W2126281772","https://openalex.org/W2155090596","https://openalex.org/W2579161546","https://openalex.org/W2749367327","https://openalex.org/W2753800142","https://openalex.org/W2767501428","https://openalex.org/W2789686642","https://openalex.org/W2799528505","https://openalex.org/W2808190017","https://openalex.org/W2808485586","https://openalex.org/W2901643192","https://openalex.org/W2902516827","https://openalex.org/W2913894912","https://openalex.org/W2923269990","https://openalex.org/W2951701153","https://openalex.org/W2963740926","https://openalex.org/W2963921497","https://openalex.org/W2964673274","https://openalex.org/W2965349765","https://openalex.org/W2976295868","https://openalex.org/W3102431071","https://openalex.org/W4234016251","https://openalex.org/W4248956172","https://openalex.org/W6638591638","https://openalex.org/W6638834111","https://openalex.org/W6682716468","https://openalex.org/W6760541073"],"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/W2059697060","https://openalex.org/W4382701072","https://openalex.org/W4256502920","https://openalex.org/W2491314273"],"abstract_inverted_index":{"With":[0],"the":[1,43,62,92,97,111,120,127,143,161,176,182],"rapid":[2],"growth":[3],"of":[4,45,64,91,107,145,160],"advanced":[5],"driving":[6],"assistance":[7],"technology,":[8],"how":[9],"to":[10,27,141],"implement":[11],"human-car":[12,87],"interaction":[13],"humanely":[14],"and":[15,50,57,68,96,117,197,203],"personally":[16],"becomes":[17],"increasingly":[18],"important.":[19],"Existing":[20],"methods":[21],"typically":[22],"rely":[23],"on":[24,199],"hand-crafted":[25],"data":[26,47,66,115,146,180],"conduct":[28],"training,":[29],"which":[30,89],"cannot":[31],"fully":[32,150],"extract":[33,151],"information":[34,152],"hidden":[35,153],"in":[36,86,154],"text.":[37],"In":[38],"this":[39],"paper,":[40],"we":[41,71],"tackle":[42],"problem":[44,144],"label":[46,65],"acquisition":[48,67],"difficulties":[49],"inadequate":[51],"feature":[52,69],"extraction":[53],"via":[54],"semi-supervised":[55,75],"learning":[56,173],"multi-granularity":[58,76,98],"learning.":[59],"To":[60],"fulfill":[61],"goal":[63],"extraction,":[70],"present":[72],"a":[73],"novel":[74],"convolutional":[77],"neural":[78],"networks":[79],"(CNNs)-based":[80],"(SSMGCNNs-based)":[81],"model":[82,168],"for":[83],"an":[84,134],"application":[85],"interaction,":[88],"consists":[90],"two-view-embedding":[93],"(TVE)":[94],"module":[95,104],"CNNs":[99],"(MGCNNs)":[100],"module.":[101],"The":[102],"TVE":[103],"learns":[105],"embeddings":[106],"text":[108,155],"regions":[109,130],"from":[110],"unlabeled":[112],"user":[113],"command":[114,179],"set":[116],"then":[118],"integrate":[119],"learned":[121,128],"tv-embeddings":[122],"into":[123,137],"MGCNNs,":[124],"so":[125],"that":[126],"tv-embedded":[129],"are":[131],"used":[132],"as":[133],"additional":[135],"input":[136],"MGCNNs'":[138],"convolution":[139,158,163],"layer":[140],"solve":[142],"annotation.":[147],"MGCNNs":[148],"can":[149],"by":[156],"multiple":[157],"kernels":[159],"same":[162],"layer.":[164],"We":[165],"compared":[166,187],"our":[167,190],"with":[169,188],"some":[170],"state-of-the-art":[171],"machine":[172],"models.":[174],"On":[175],"car":[177],"operation":[178],"set,":[181],"simulation":[183],"results":[184],"demonstrated":[185],"that,":[186],"CNNs,":[189],"method":[191],"respectively":[192],"improved":[193],"5.13%,":[194],"5.64%,":[195],"3.60%":[196],"5.34%":[198],"precision,":[200],"recall,":[201],"F-1":[202],"training":[204],"loss.":[205]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}