{"id":"https://openalex.org/W2990592922","doi":"https://doi.org/10.1109/smc.2019.8914542","title":"A Deep Learning Model with Data Enrichment for Intent Detection and Slot Filling","display_name":"A Deep Learning Model with Data Enrichment for Intent Detection and Slot Filling","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2990592922","doi":"https://doi.org/10.1109/smc.2019.8914542","mag":"2990592922"},"language":"en","primary_location":{"id":"doi:10.1109/smc.2019.8914542","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc.2019.8914542","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)","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/A5037566627","display_name":"S\u0142awomir Dadas","orcid":"https://orcid.org/0000-0002-9177-6685"},"institutions":[{"id":"https://openalex.org/I4210139285","display_name":"National Information Processing Institute","ror":"https://ror.org/040fc1e14","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210139285"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Slawomir Dadas","raw_affiliation_strings":["National Information Processing Institute, Warsaw, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Information Processing Institute, Warsaw, Poland","institution_ids":["https://openalex.org/I4210139285"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020570496","display_name":"Jaros\u0142aw Protasiewicz","orcid":"https://orcid.org/0000-0002-9204-921X"},"institutions":[{"id":"https://openalex.org/I4210139285","display_name":"National Information Processing Institute","ror":"https://ror.org/040fc1e14","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210139285"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Jaroslaw Protasiewicz","raw_affiliation_strings":["National Information Processing Institute, Warsaw, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Information Processing Institute, Warsaw, Poland","institution_ids":["https://openalex.org/I4210139285"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003799782","display_name":"Witold Pedrycz","orcid":"https://orcid.org/0000-0002-9335-9930"},"institutions":[{"id":"https://openalex.org/I4210139285","display_name":"National Information Processing Institute","ror":"https://ror.org/040fc1e14","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210139285"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Witold Pedrycz","raw_affiliation_strings":["National Information Processing Institute, Warsaw, Poland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Information Processing Institute, Warsaw, Poland","institution_ids":["https://openalex.org/I4210139285"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.723,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.79411922,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3012","last_page":"3018"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9976999759674072,"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":0.9976999759674072,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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":0.8513921499252319},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.7135534286499023},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6788666844367981},{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.6516770124435425},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6493654251098633},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.6360458731651306},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.616170346736908},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5198850631713867},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4649431109428406},{"id":"https://openalex.org/keywords/novelty-detection","display_name":"Novelty detection","score":0.44979429244995117},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43514376878738403},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.41856810450553894},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41770613193511963}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8513921499252319},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.7135534286499023},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6788666844367981},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.6516770124435425},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6493654251098633},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.6360458731651306},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.616170346736908},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5198850631713867},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4649431109428406},{"id":"https://openalex.org/C2778924833","wikidata":"https://www.wikidata.org/wiki/Q7064603","display_name":"Novelty detection","level":3,"score":0.44979429244995117},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43514376878738403},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.41856810450553894},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41770613193511963},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C27206212","wikidata":"https://www.wikidata.org/wiki/Q34178","display_name":"Theology","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},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc.2019.8914542","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc.2019.8914542","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1503259811","https://openalex.org/W1522301498","https://openalex.org/W1971034924","https://openalex.org/W2064675550","https://openalex.org/W2079735306","https://openalex.org/W2091671846","https://openalex.org/W2094472029","https://openalex.org/W2110230617","https://openalex.org/W2120699290","https://openalex.org/W2137871902","https://openalex.org/W2155524666","https://openalex.org/W2155858122","https://openalex.org/W2166293310","https://openalex.org/W2201092681","https://openalex.org/W2227316993","https://openalex.org/W2250539671","https://openalex.org/W2473329891","https://openalex.org/W2522720655","https://openalex.org/W2963974889","https://openalex.org/W2964117975","https://openalex.org/W2964121744","https://openalex.org/W2964232431","https://openalex.org/W6630217047","https://openalex.org/W6631190155","https://openalex.org/W6676328030","https://openalex.org/W6684017090","https://openalex.org/W6687630728","https://openalex.org/W6689346831","https://openalex.org/W6696511012"],"related_works":["https://openalex.org/W2064636555","https://openalex.org/W2585503716","https://openalex.org/W1939982668","https://openalex.org/W2105014086","https://openalex.org/W2076090200","https://openalex.org/W3025682415","https://openalex.org/W2081173909","https://openalex.org/W4389009659","https://openalex.org/W4312933423","https://openalex.org/W2604316291"],"abstract_inverted_index":{"A":[0],"model":[1,159,203],"for":[2,45,117,126,135,155,199],"accurately":[3],"solving":[4],"the":[5,60,72,98,107,111,118,136,179,223],"tasks":[6],"of":[7,17,40,66,71,81,138,142,160,181,209,215],"intent":[8,161],"detection":[9,162],"and":[10,25,90,163,175,222],"slot":[11,164],"filling":[12],"requires":[13],"a":[14,38,42,56,64,76,82,139,148,158,186,196,200,206,213],"substantial":[15],"amount":[16,180],"user":[18,145],"queries":[19,146],"annotated":[20,144],"manually,":[21],"which":[22],"is":[23,123,153],"time-consuming":[24],"costly.":[26],"In":[27],"this":[28,34,132],"study,":[29],"in":[30,194],"order":[31],"to":[32,59,172,184],"circumvent":[33],"problem,":[35],"we":[36,74],"propose":[37],"method":[39,133],"expanding":[41,195],"training":[43,61,150,197,210,224],"set":[44,65,141,151,198,214],"handling":[46],"these":[47],"two":[48],"tasks.":[49],"The":[50,94],"data":[51,182,225],"are":[52],"augmented":[53],"by":[54,177],"applying":[55],"random":[57,92,207],"mutation":[58,208],"samples,":[62,211],"following":[63,212],"heuristic":[67,216],"rules.":[68],"For":[69],"validation":[70],"method,":[73],"construct":[75],"compound":[77],"neural":[78],"architecture":[79],"composed":[80],"long":[83],"short-term":[84],"memory":[85],"layer,":[86],"an":[87],"attention":[88],"mechanism,":[89],"conditional":[91],"fields.":[93],"experiments":[95],"conducted":[96],"on":[97,110,205],"Automatic":[99],"Terminal":[100],"Information":[101],"Service":[102],"(ATIS)":[103],"dataset":[104],"demonstrate":[105],"that":[106,131,152,218],"models":[108],"trained":[109],"expanded":[112],"datasets":[113],"improve":[114],"their":[115],"F-score":[116],"slot-filling":[119],"task.":[120],"This":[121],"improvement":[122],"particularly":[124],"significant":[125],"small":[127,140],"datasets.":[128],"We":[129],"believe":[130],"allows":[134],"expansion":[137],"previously":[143],"into":[147],"large":[149],"sufficient":[154],"correctly":[156],"constructing":[157],"filling.":[165],"Therefore,":[166],"our":[167],"approach":[168],"can":[169],"be":[170],"used":[171],"save":[173],"time":[174],"money":[176],"reducing":[178],"required":[183],"train":[185],"natural":[187],"language":[188],"understanding":[189],"model.":[190],"Its":[191],"novelty":[192],"consists":[193],"deep":[201],"learning":[202],"based":[204],"rules":[217],"utilise":[219],"external":[220],"lexicons":[221],"itself.":[226]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}