{"id":"https://openalex.org/W3115855682","doi":"https://doi.org/10.1109/icct50939.2020.9295901","title":"POS Scaling Attention Model for Joint Slot Filling and Intent Classification","display_name":"POS Scaling Attention Model for Joint Slot Filling and Intent Classification","publication_year":2020,"publication_date":"2020-10-28","ids":{"openalex":"https://openalex.org/W3115855682","doi":"https://doi.org/10.1109/icct50939.2020.9295901","mag":"3115855682"},"language":"en","primary_location":{"id":"doi:10.1109/icct50939.2020.9295901","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icct50939.2020.9295901","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 20th International Conference on Communication Technology (ICCT)","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/A5025852048","display_name":"Wei\u2010An Chao","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Chao","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100719457","display_name":"Ke Yu","orcid":"https://orcid.org/0000-0002-1158-1483"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Ke","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051552380","display_name":"Xiaofei Wu","orcid":"https://orcid.org/0000-0002-4797-1256"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wu Xiaofei","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5025852048"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.17806021,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1483","last_page":"1487"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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":0.9998999834060669,"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/T12031","display_name":"Speech and dialogue systems","score":0.9994999766349792,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9961000084877014,"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":0.8132627010345459},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.7350573539733887},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.7343950867652893},{"id":"https://openalex.org/keywords/hierarchy","display_name":"Hierarchy","score":0.6650735139846802},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6488342881202698},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5654008984565735},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.5524201393127441},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5196781754493713},{"id":"https://openalex.org/keywords/noun","display_name":"Noun","score":0.5011568069458008},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4690319299697876},{"id":"https://openalex.org/keywords/natural-language-understanding","display_name":"Natural language understanding","score":0.4465550482273102},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4314311742782593},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.38453176617622375},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.3680857717990875}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8132627010345459},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.7350573539733887},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.7343950867652893},{"id":"https://openalex.org/C31170391","wikidata":"https://www.wikidata.org/wiki/Q188619","display_name":"Hierarchy","level":2,"score":0.6650735139846802},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6488342881202698},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5654008984565735},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.5524201393127441},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5196781754493713},{"id":"https://openalex.org/C121934690","wikidata":"https://www.wikidata.org/wiki/Q1084","display_name":"Noun","level":2,"score":0.5011568069458008},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4690319299697876},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.4465550482273102},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4314311742782593},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.38453176617622375},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.3680857717990875},{"id":"https://openalex.org/C34447519","wikidata":"https://www.wikidata.org/wiki/Q179522","display_name":"Market economy","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/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icct50939.2020.9295901","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icct50939.2020.9295901","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 20th International Conference on Communication Technology (ICCT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.699999988079071,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"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":37,"referenced_works":["https://openalex.org/W47495561","https://openalex.org/W112633934","https://openalex.org/W179875071","https://openalex.org/W1535753778","https://openalex.org/W2063624183","https://openalex.org/W2105594594","https://openalex.org/W2133564696","https://openalex.org/W2147527908","https://openalex.org/W2147880316","https://openalex.org/W2399175133","https://openalex.org/W2405622356","https://openalex.org/W2470673105","https://openalex.org/W2609512471","https://openalex.org/W2803392141","https://openalex.org/W2804945011","https://openalex.org/W2891533927","https://openalex.org/W2892248135","https://openalex.org/W2905730339","https://openalex.org/W2917128112","https://openalex.org/W2920898473","https://openalex.org/W2949325756","https://openalex.org/W2951527505","https://openalex.org/W2963033987","https://openalex.org/W2963066655","https://openalex.org/W2963974889","https://openalex.org/W2964308564","https://openalex.org/W2964829511","https://openalex.org/W2970450228","https://openalex.org/W2972380590","https://openalex.org/W6604603068","https://openalex.org/W6607333740","https://openalex.org/W6631924126","https://openalex.org/W6679434410","https://openalex.org/W6682137061","https://openalex.org/W6713452507","https://openalex.org/W6757078890","https://openalex.org/W6759393636"],"related_works":["https://openalex.org/W4288263119","https://openalex.org/W3015724364","https://openalex.org/W2967994095","https://openalex.org/W4285240985","https://openalex.org/W2900126711","https://openalex.org/W4286930972","https://openalex.org/W3202115945","https://openalex.org/W2542958340","https://openalex.org/W4389520438","https://openalex.org/W1991374750"],"abstract_inverted_index":{"Intention":[0],"recognition":[1],"is":[2,32,85],"a":[3,38,116],"subtask":[4],"of":[5,76,109],"the":[6,17,24,28,35,48,71,107,127,158,169],"natural":[7],"language":[8],"understanding":[9],"in":[10,63,97],"human-machine":[11],"dialogue":[12],"system.":[13],"To":[14],"understand":[15],"what":[16],"user":[18,101],"says,":[19],"we":[20,88,114],"need":[21],"to":[22,33,106],"determine":[23],"intention":[25,40],"expressed":[26],"by":[27],"user.":[29],"Intent":[30],"classification":[31,56],"classify":[34],"sentence":[36],"into":[37],"predefined":[39],"category.":[41],"Considering":[42],"that":[43,141],"slot":[44,52,77,133],"and":[45,54,74,79,92,103,129,135,154,161],"intent":[46,55,80,136],"have":[47],"strong":[49],"correlation,":[50],"joint":[51,67,132],"filling":[53,78,134],"with":[57,168],"attention":[58,119],"mechanism":[59],"are":[60],"actively":[61],"explored":[62],"recent":[64],"years.":[65],"Most":[66],"methods":[68],"focus":[69,125],"on":[70,126,157],"interactive":[72],"mode":[73],"hierarchy":[75],"classification.":[81,137],"However,":[82],"part-of-speech":[83,117],"(POS)":[84],"ignored.":[86],"As":[87],"all":[89],"know,":[90],"nouns":[91,104,130],"verbs":[93,99,128],"occupy":[94],"important":[95],"positions":[96],"sentence,":[98],"represent":[100],"behavior,":[102],"correspond":[105],"object":[108],"operation.":[110],"In":[111,165],"this":[112],"paper,":[113],"propose":[115],"scaling":[118],"module":[120],"which":[121],"makes":[122],"our":[123,142,172],"model":[124,144,173],"for":[131],"The":[138],"experiments":[139],"show":[140],"proposed":[143],"significantly":[145],"improves":[146],"sentence-level":[147],"semantic":[148],"frame":[149],"accuracy,":[150],"reaching":[151],"85.8":[152],"percent":[153,156],"76.8":[155],"benchmark":[159],"ATIS":[160],"Snips":[162],"datasets":[163],"respectively.":[164],"addition,":[166],"compared":[167],"baseline":[170],"methods,":[171],"has":[174],"better":[175],"convergence":[176],"speed.":[177]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}