{"id":"https://openalex.org/W4375944604","doi":"https://doi.org/10.3233/jifs-231699","title":"A hybrid model for text classification using part-of-speech features","display_name":"A hybrid model for text classification using part-of-speech features","publication_year":2023,"publication_date":"2023-05-09","ids":{"openalex":"https://openalex.org/W4375944604","doi":"https://doi.org/10.3233/jifs-231699"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-231699","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-231699","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & 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/A5040833989","display_name":"Wang Zou","orcid":"https://orcid.org/0000-0001-7421-9302"},"institutions":[{"id":"https://openalex.org/I4210126203","display_name":"Hubei University of Automotive Technology","ror":"https://ror.org/039m95m06","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210126203"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wang Zou","raw_affiliation_strings":["School of Electrical and Information Engineering, Hubei University of Automotive Technology, Shiyan, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Hubei University of Automotive Technology, Shiyan, China","institution_ids":["https://openalex.org/I4210126203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079010381","display_name":"Wubo Zhang","orcid":"https://orcid.org/0000-0001-8368-0491"},"institutions":[{"id":"https://openalex.org/I4210126203","display_name":"Hubei University of Automotive Technology","ror":"https://ror.org/039m95m06","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210126203"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wubo Zhang","raw_affiliation_strings":["School of Electrical and Information Engineering, Hubei University of Automotive Technology, Shiyan, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Hubei University of Automotive Technology, Shiyan, China","institution_ids":["https://openalex.org/I4210126203"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102655547","display_name":"Zhuofeng Tian","orcid":null},"institutions":[{"id":"https://openalex.org/I43922553","display_name":"Wuhan University of Science and Technology","ror":"https://ror.org/00e4hrk88","country_code":"CN","type":"education","lineage":["https://openalex.org/I43922553"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuofeng Tian","raw_affiliation_strings":["School of Grammar and Economics, Wuhan University of Science and Technology, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Grammar and Economics, Wuhan University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I43922553"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039147646","display_name":"Wenhuan Wu","orcid":"https://orcid.org/0000-0002-0918-4737"},"institutions":[{"id":"https://openalex.org/I4210126203","display_name":"Hubei University of Automotive Technology","ror":"https://ror.org/039m95m06","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210126203"]},{"id":"https://openalex.org/I4210131919","display_name":"Xi'an University of Technology","ror":"https://ror.org/038avdt50","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210131919"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenhuan Wu","raw_affiliation_strings":["School of Computer Science and Engineering, Xi\u2019an University of Technology, Xi\u2019an, China","School of Electrical and Information Engineering, Hubei University of Automotive Technology, Shiyan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Xi\u2019an University of Technology, Xi\u2019an, China","institution_ids":["https://openalex.org/I4210131919"]},{"raw_affiliation_string":"School of Electrical and Information Engineering, Hubei University of Automotive Technology, Shiyan, China","institution_ids":["https://openalex.org/I4210126203"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5040833989"],"corresponding_institution_ids":["https://openalex.org/I4210126203"],"apc_list":null,"apc_paid":null,"fwci":0.6983,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.74419786,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"45","issue":"1","first_page":"1235","last_page":"1249"},"is_retracted":true,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9943000078201294,"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":0.9925000071525574,"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/softmax-function","display_name":"Softmax function","score":0.9573560953140259},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8012822866439819},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6853476166725159},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.574180006980896},{"id":"https://openalex.org/keywords/stacking","display_name":"Stacking","score":0.4910926818847656},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.490448921918869},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.44460999965667725},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4430045187473297},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4269470274448395},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41188547015190125},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.39090946316719055}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.9573560953140259},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8012822866439819},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6853476166725159},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.574180006980896},{"id":"https://openalex.org/C33347731","wikidata":"https://www.wikidata.org/wiki/Q285210","display_name":"Stacking","level":2,"score":0.4910926818847656},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.490448921918869},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.44460999965667725},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4430045187473297},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4269470274448395},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41188547015190125},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.39090946316719055},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C46141821","wikidata":"https://www.wikidata.org/wiki/Q209402","display_name":"Nuclear magnetic resonance","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jifs-231699","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-231699","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5400000214576721}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W292284645","https://openalex.org/W1968969471","https://openalex.org/W2001237910","https://openalex.org/W2014545475","https://openalex.org/W2031998113","https://openalex.org/W2052684427","https://openalex.org/W2064794832","https://openalex.org/W2079735306","https://openalex.org/W2150874198","https://openalex.org/W2153207916","https://openalex.org/W2158994553","https://openalex.org/W2183366530","https://openalex.org/W2319453305","https://openalex.org/W2765854388","https://openalex.org/W2914767245","https://openalex.org/W2937423263","https://openalex.org/W2962970834","https://openalex.org/W2963477629","https://openalex.org/W2974335209","https://openalex.org/W2989409993","https://openalex.org/W3021743785","https://openalex.org/W3040078053","https://openalex.org/W3040573443","https://openalex.org/W3089856149","https://openalex.org/W3105625590","https://openalex.org/W3210728438","https://openalex.org/W4212883601"],"related_works":["https://openalex.org/W3107204728","https://openalex.org/W4287591324","https://openalex.org/W4226420367","https://openalex.org/W2980176872","https://openalex.org/W2962876041","https://openalex.org/W3090555870","https://openalex.org/W3108503355","https://openalex.org/W2249953602","https://openalex.org/W2947839263","https://openalex.org/W3120400911"],"abstract_inverted_index":{"In":[0,68,87,109],"the":[1,9,15,30,69,74,88,93,96,106,110,116,126,155,163,166,174],"field":[2],"of":[3,11,73,84,92,115,165],"text":[4,22,61,70,85,107,111],"classification,":[5,40],"current":[6],"research":[7],"ignores":[8],"role":[10],"part-of-speech":[12,64,77],"features,":[13,65],"and":[14,45,52,130,142,158],"multi-channel":[16,97],"model":[17,59,102,168],"that":[18,162],"can":[19,48,103],"learn":[20,105],"richer":[21],"information":[23],"compared":[24,172],"to":[25,37,124,173],"a":[26,57,80],"single":[27],"model.":[28],"Moreover,":[29],"method":[31],"based":[32],"on":[33,154],"neural":[34,100],"network":[35,101],"models":[36],"achieve":[38],"final":[39,112],"using":[41,63,95],"fully":[42,104,127,144],"connected":[43,128,145],"layer":[44,47,129,146,148],"Softmax":[46,131,147],"be":[49],"further":[50],"improved":[51,171],"optimized.":[53],"This":[54],"paper":[55,119],"proposes":[56],"hybrid":[58],"for":[60],"classification":[62,113],"namely":[66],"PAGNN-Stacking1.":[67],"representation":[71,83],"stage":[72,91,114],"model,":[75,94,117],"introducing":[76],"features":[78],"facilitates":[79],"more":[81],"accurate":[82],"information.":[86,108],"feature":[89],"extraction":[90],"attention":[98],"gated":[99],"this":[118],"innovatively":[120],"adopts":[121],"Stacking":[122],"algorithm":[123],"improve":[125],"layer,":[132],"which":[133],"fuses":[134],"five":[135],"machine":[136],"learning":[137],"algorithms":[138],"as":[139,149],"base":[140],"classifier":[141],"uses":[143],"meta":[150],"classifier.":[151],"The":[152],"experiments":[153],"IMDB,":[156],"SST-2,":[157],"AG_News":[159],"datasets":[160],"show":[161],"accuracy":[164],"PAGNN-Stacking":[167],"is":[169],"significantly":[170],"benchmark":[175],"models.":[176]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-01-30T23:17:42.513302","created_date":"2025-10-10T00:00:00"}