{"id":"https://openalex.org/W3023027202","doi":"https://doi.org/10.1145/3366423.3380268","title":"Open Intent Extraction from Natural Language Interactions","display_name":"Open Intent Extraction from Natural Language Interactions","publication_year":2020,"publication_date":"2020-04-20","ids":{"openalex":"https://openalex.org/W3023027202","doi":"https://doi.org/10.1145/3366423.3380268","mag":"3023027202"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3366423.3380268","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5080114650","display_name":"Nikhita Vedula","orcid":"https://orcid.org/0000-0003-4857-5308"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"funder","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nikhita Vedula","raw_affiliation_strings":["The Ohio State University"],"affiliations":[{"raw_affiliation_string":"The Ohio State University","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016933602","display_name":"Nedim Lipka","orcid":"https://orcid.org/0000-0002-3779-7784"},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"funder","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nedim Lipka","raw_affiliation_strings":["Adobe"],"affiliations":[{"raw_affiliation_string":"Adobe","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005531495","display_name":"Pranav Maneriker","orcid":"https://orcid.org/0000-0003-1333-4424"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"funder","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pranav Maneriker","raw_affiliation_strings":["The Ohio State University"],"affiliations":[{"raw_affiliation_string":"The Ohio State University","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100755351","display_name":"Srinivasan Parthasarathy","orcid":"https://orcid.org/0000-0002-6062-6449"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"funder","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Srinivasan Parthasarathy","raw_affiliation_strings":["The Ohio State University"],"affiliations":[{"raw_affiliation_string":"The Ohio State University","institution_ids":["https://openalex.org/I52357470"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.11,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.859501,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":95},"biblio":{"volume":"198","issue":null,"first_page":"2009","last_page":"2020"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"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":1.0,"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":0.9995,"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":0.9964,"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/utterance","display_name":"Utterance","score":0.7609089},{"id":"https://openalex.org/keywords/sequence-labeling","display_name":"Sequence labeling","score":0.73394173},{"id":"https://openalex.org/keywords/open-domain","display_name":"Open domain","score":0.6163161},{"id":"https://openalex.org/keywords/natural-language-understanding","display_name":"Natural language understanding","score":0.60218793},{"id":"https://openalex.org/keywords/spoken-language","display_name":"Spoken Language","score":0.46070233}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.838052},{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.7609089},{"id":"https://openalex.org/C35639132","wikidata":"https://www.wikidata.org/wiki/Q7452468","display_name":"Sequence labeling","level":3,"score":0.73394173},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6438451},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.64348245},{"id":"https://openalex.org/C173853756","wikidata":"https://www.wikidata.org/wiki/Q86915","display_name":"Dialog box","level":2,"score":0.64110684},{"id":"https://openalex.org/C2993776861","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Open domain","level":3,"score":0.6163161},{"id":"https://openalex.org/C2779439875","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Natural language understanding","level":3,"score":0.60218793},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5994771},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.57773525},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5739322},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5506239},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.542802},{"id":"https://openalex.org/C2776230583","wikidata":"https://www.wikidata.org/wiki/Q1322198","display_name":"Spoken language","level":2,"score":0.46070233},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.43322635},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.3790926},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.16862515},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3366423.3380268","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality education","id":"https://metadata.un.org/sdg/4","score":0.77}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":61,"referenced_works":["https://openalex.org/W1972595521","https://openalex.org/W1987971958","https://openalex.org/W2036282699","https://openalex.org/W2047237057","https://openalex.org/W2064675550","https://openalex.org/W2077302143","https://openalex.org/W2094472029","https://openalex.org/W2095705004","https://openalex.org/W2123442489","https://openalex.org/W2124033848","https://openalex.org/W2137871902","https://openalex.org/W2141732516","https://openalex.org/W2142384583","https://openalex.org/W2143612262","https://openalex.org/W2147880316","https://openalex.org/W2150295085","https://openalex.org/W2156387975","https://openalex.org/W2162833336","https://openalex.org/W2163844356","https://openalex.org/W2170240176","https://openalex.org/W2250539671","https://openalex.org/W2251687660","https://openalex.org/W2251913848","https://openalex.org/W2252180690","https://openalex.org/W2253491900","https://openalex.org/W2473007590","https://openalex.org/W2473329891","https://openalex.org/W2522720655","https://openalex.org/W2575101493","https://openalex.org/W2740765036","https://openalex.org/W2741306347","https://openalex.org/W2742039423","https://openalex.org/W2742129161","https://openalex.org/W2752813202","https://openalex.org/W2774470364","https://openalex.org/W2798965707","https://openalex.org/W2803392141","https://openalex.org/W2803609229","https://openalex.org/W2804945011","https://openalex.org/W2805853672","https://openalex.org/W2892081520","https://openalex.org/W2901336235","https://openalex.org/W2914702779","https://openalex.org/W2933022734","https://openalex.org/W2954108589","https://openalex.org/W2962715022","https://openalex.org/W2962788148","https://openalex.org/W2962854379","https://openalex.org/W2962910139","https://openalex.org/W2963033987","https://openalex.org/W2963207607","https://openalex.org/W2963403868","https://openalex.org/W2963560594","https://openalex.org/W2963826681","https://openalex.org/W2963834453","https://openalex.org/W2963888305","https://openalex.org/W2963951015","https://openalex.org/W2963974889","https://openalex.org/W2964232431","https://openalex.org/W4285719527","https://openalex.org/W4312846666"],"related_works":["https://openalex.org/W4309395021","https://openalex.org/W4307481286","https://openalex.org/W3215363805","https://openalex.org/W3192727970","https://openalex.org/W3091989500","https://openalex.org/W3023027202","https://openalex.org/W2991310128","https://openalex.org/W2951097643","https://openalex.org/W2391533720","https://openalex.org/W204133468"],"abstract_inverted_index":{"Accurately":[0],"discovering":[1,70],"user":[2,39],"intents":[3,120,206],"from":[4,46,77],"their":[5],"written":[6],"or":[7,72],"spoken":[8],"language":[9,16],"plays":[10],"a":[11,28,32,42,47,61,90,100,110,115,122,134],"critical":[12],"role":[13],"in":[14,121,201],"natural":[15],"understanding":[17],"and":[18,59,153,164],"automated":[19],"dialog":[20],"response.":[21],"Most":[22],"existing":[23],"research":[24],"models":[25],"this":[26,55],"as":[27,99],"classification":[29],"task":[30,103],"with":[31,207],"single":[33,43],"intent":[34,44,66,75,129,170],"label":[35],"per":[36,215],"utterance,":[37],"grouping":[38],"utterances":[40,176],"into":[41],"type":[45],"set":[48],"of":[49,64,114,173,199],"categories":[50],"known":[51],"beforehand.":[52],"Going":[53],"beyond":[54],"formulation,":[56],"we":[57,162],"define":[58],"investigate":[60],"new":[62],"problem":[63,98],"open":[65,169],"discovery.":[67],"It":[68,108],"involves":[69],"one":[71],"more":[73],"generic":[74],"types":[76],"text":[78],"utterances,":[79],"that":[80,183],"may":[81],"not":[82],"have":[83],"been":[84],"encountered":[85],"during":[86],"training.":[87],"We":[88,132,145,194],"propose":[89],"novel":[91],"domain-agnostic":[92],"approach,":[93],"OPINE,":[94],"which":[95],"formulates":[96],"the":[97,197],"sequence":[101],"tagging":[102],"under":[104],"an":[105,168],"open-world":[106],"setting.":[107],"employs":[109],"CRF":[111],"on":[112],"top":[113],"bidirectional":[116],"LSTM":[117],"to":[118,126,138,150,166],"extract":[119],"consistent":[123],"format,":[124],"subject":[125],"constraints":[127],"among":[128],"tag":[130],"labels.":[131],"apply":[133],"multi-head":[135],"self-attention":[136],"mechanism":[137],"effectively":[139],"learn":[140],"dependencies":[141],"between":[142],"distant":[143],"words.":[144],"further":[146],"use":[147],"adversarial":[148],"training":[149,213],"improve":[151],"performance":[152],"robustly":[154],"adapt":[155],"our":[156,184],"model":[157],"across":[158],"varying":[159],"domains.":[160,179],"Finally,":[161],"curate":[163],"plan":[165],"release":[167],"annotated":[171],"dataset":[172],"25K":[174],"real-life":[175],"spanning":[177],"diverse":[178,204],"Extensive":[180],"experiments":[181],"show":[182],"approach":[185],"outperforms":[186],"state-of-the-art":[187],"baselines":[188],"by":[189],"5-15%":[190],"F1":[191],"score":[192],"points.":[193],"also":[195,210],"demonstrate":[196],"efficacy":[198],"OPINE":[200],"recognizing":[202],"multiple,":[203],"domain":[205],"limited":[208],"(can":[209],"be":[211],"zero)":[212],"examples":[214],"unique":[216],"domain.":[217]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W3023027202","counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":5}],"updated_date":"2025-04-23T09:36:08.760251","created_date":"2020-05-13"}