{"id":"https://openalex.org/W2978440502","doi":"https://doi.org/10.1109/ijcnn.2019.8852271","title":"Text Classification Using Gated and Transposed Attention Networks","display_name":"Text Classification Using Gated and Transposed Attention Networks","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2978440502","doi":"https://doi.org/10.1109/ijcnn.2019.8852271","mag":"2978440502"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8852271","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852271","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-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/A5101747967","display_name":"Kang He","orcid":"https://orcid.org/0000-0003-0148-699X"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Kang He","raw_affiliation_strings":["School of Computer Science and Software Engineering, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Software Engineering, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101272808","display_name":"Min Zhu","orcid":"https://orcid.org/0009-0001-7398-9230"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Zhu","raw_affiliation_strings":["School of Computer Science and Software Engineering, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Software Engineering, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101747967"],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":0.28,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.66123236,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"32","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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/T10028","display_name":"Topic Modeling","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/T11550","display_name":"Text and Document Classification Technologies","score":0.9987000226974487,"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":0.9977999925613403,"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":0.6610201597213745},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42103028297424316},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3332270681858063}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6610201597213745},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42103028297424316},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3332270681858063}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2019.8852271","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852271","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1544827683","https://openalex.org/W1832693441","https://openalex.org/W2070246124","https://openalex.org/W2105591985","https://openalex.org/W2113378307","https://openalex.org/W2133564696","https://openalex.org/W2147527908","https://openalex.org/W2158139315","https://openalex.org/W2170240176","https://openalex.org/W2250539671","https://openalex.org/W2250966211","https://openalex.org/W2251939518","https://openalex.org/W2265846598","https://openalex.org/W2470673105","https://openalex.org/W2511794618","https://openalex.org/W2556888587","https://openalex.org/W2740721704","https://openalex.org/W2949615363","https://openalex.org/W2951527505","https://openalex.org/W2962853356","https://openalex.org/W2963012544","https://openalex.org/W2963403868","https://openalex.org/W2963921497","https://openalex.org/W2964046515","https://openalex.org/W2964121744","https://openalex.org/W2964308564","https://openalex.org/W4285719527","https://openalex.org/W4385245566","https://openalex.org/W6631190155","https://openalex.org/W6632455782","https://openalex.org/W6638834111","https://openalex.org/W6679434410","https://openalex.org/W6682137061","https://openalex.org/W6683557909","https://openalex.org/W6685053522","https://openalex.org/W6691459498","https://openalex.org/W6693505360","https://openalex.org/W6725962192","https://openalex.org/W6729752019","https://openalex.org/W6732491067","https://openalex.org/W6739901393","https://openalex.org/W6749915262"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W4391913857","https://openalex.org/W2350741829","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Text":[0,43],"classification":[1,44,108],"models":[2,45],"based":[3,37,46,75],"on":[4,38,47,76,103,128,135,152],"recurrent":[5,40],"neural":[6,41,49],"networks":[7],"have":[8],"poor":[9],"parallel":[10,30],"processing":[11],"ability,":[12],"as":[13,56],"they":[14,57],"need":[15],"to":[16,34,52,88],"be":[17],"trained":[18],"word":[19],"by":[20,60],"word.":[21],"The":[22,110],"model":[23,116],"proposed":[24],"in":[25,118],"this":[26,68,119,141],"paper":[27,120,142],"has":[28],"increased":[29],"computing":[31],"capability":[32],"compared":[33],"the":[35,39,61,64,85,115,122,125,136,145,153],"one":[36],"networks.":[42],"convolution":[48],"network":[50,74,86],"struggle":[51],"obtain":[53],"contextual":[54],"information":[55],"are":[58,100],"limited":[59],"size":[62],"of":[63,124,147],"convolutional":[65],"kernel.":[66],"In":[67,139],"paper,":[69],"we":[70],"propose":[71],"an":[72],"attention":[73],"a":[77],"gated":[78],"control":[79,149],"and":[80,91,131,150],"transposed":[81],"structure,":[82],"which":[83],"makes":[84],"able":[87],"understand":[89],"context":[90],"more":[92],"efficiently":[93],"extract":[94],"important":[95],"features":[96],"from":[97],"text.":[98],"Experiments":[99],"carried":[101],"out":[102],"six":[104],"commonly":[105],"used":[106],"text":[107],"datasets.":[109],"experimental":[111],"results":[112],"show":[113],"that":[114],"presented":[117],"achieves":[121],"state":[123],"art":[126],"performance":[127],"four":[129],"datasets":[130],"is":[132],"very":[133],"competitive":[134],"other":[137],"two.":[138],"addition,":[140],"also":[143],"explores":[144],"effects":[146],"gate":[148],"transposition":[151],"whole":[154],"model.":[155]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
