{"id":"https://openalex.org/W2889636191","doi":"https://doi.org/10.18653/v1/d18-1072","title":"Auto-Dialabel: Labeling Dialogue Data with Unsupervised Learning","display_name":"Auto-Dialabel: Labeling Dialogue Data with Unsupervised Learning","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2889636191","doi":"https://doi.org/10.18653/v1/d18-1072","mag":"2889636191"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d18-1072","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1072","pdf_url":"https://www.aclweb.org/anthology/D18-1072.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/D18-1072.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100709711","display_name":"Shi Chen","orcid":"https://orcid.org/0000-0002-3524-3577"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Shi","raw_affiliation_strings":["MOE Key Lab of Computational Linguistics, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MOE Key Lab of Computational Linguistics, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100340184","display_name":"Qi Chen","orcid":"https://orcid.org/0000-0002-7430-1645"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Chen","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079222154","display_name":"Lei Sha","orcid":"https://orcid.org/0000-0001-5914-7590"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Sha","raw_affiliation_strings":["MOE Key Lab of Computational Linguistics, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MOE Key Lab of Computational Linguistics, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058353424","display_name":"Sujian Li","orcid":"https://orcid.org/0000-0001-7493-0786"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sujian Li","raw_affiliation_strings":["MOE Key Lab of Computational Linguistics, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MOE Key Lab of Computational Linguistics, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101441137","display_name":"Xu Sun","orcid":"https://orcid.org/0000-0001-8241-9320"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Sun","raw_affiliation_strings":["MOE Key Lab of Computational Linguistics, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MOE Key Lab of Computational Linguistics, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025565222","display_name":"Houfeng Wang","orcid":"https://orcid.org/0000-0001-7130-1589"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Houfeng Wang","raw_affiliation_strings":["MOE Key Lab of Computational Linguistics, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MOE Key Lab of Computational Linguistics, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101985940","display_name":"Lintao Zhang","orcid":"https://orcid.org/0009-0005-7527-8183"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lintao Zhang","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5845,"has_fulltext":true,"cited_by_count":41,"citation_normalized_percentile":{"value":0.88151029,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"684","last_page":"689"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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/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":0.9988999962806702,"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/leverage","display_name":"Leverage (statistics)","score":0.8248782157897949},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8072031736373901},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.7832232713699341},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6862172484397888},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.6077800393104553},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5458753705024719},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5098270773887634},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48558682203292847},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.4802672863006592},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.47429922223091125},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4572571814060211},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43709948658943176},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3657595217227936},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.16381493210792542},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10349041223526001}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.8248782157897949},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8072031736373901},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7832232713699341},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6862172484397888},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.6077800393104553},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5458753705024719},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5098270773887634},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48558682203292847},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.4802672863006592},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47429922223091125},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4572571814060211},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43709948658943176},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3657595217227936},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.16381493210792542},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10349041223526001},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","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:10.18653/v1/d18-1072","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1072","pdf_url":"https://www.aclweb.org/anthology/D18-1072.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/d18-1072","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d18-1072","pdf_url":"https://www.aclweb.org/anthology/D18-1072.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G118205048","display_name":null,"funder_award_id":"2017YFB1002101","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2204133011","display_name":"\u6c49\u8bed\u591a\u5c42\u6b21\u8bed\u7bc7\u5206\u6790\u7406\u8bba\u65b9\u6cd5\u7814\u7a76\u4e0e\u5e94\u7528","funder_award_id":"61333018","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8356743227","display_name":null,"funder_award_id":"2017YFB1002101","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2889636191.pdf","grobid_xml":"https://content.openalex.org/works/W2889636191.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W1518951372","https://openalex.org/W1521626219","https://openalex.org/W1591706642","https://openalex.org/W1714665356","https://openalex.org/W1773652845","https://openalex.org/W1969152782","https://openalex.org/W2077302143","https://openalex.org/W2130942839","https://openalex.org/W2131876387","https://openalex.org/W2157331557","https://openalex.org/W2250539671","https://openalex.org/W2251235149","https://openalex.org/W2604698497","https://openalex.org/W2963491014","https://openalex.org/W2963797754","https://openalex.org/W2963963856"],"related_works":["https://openalex.org/W2997921738","https://openalex.org/W2965146396","https://openalex.org/W2770818364","https://openalex.org/W3210196349","https://openalex.org/W4214728004","https://openalex.org/W2950181282","https://openalex.org/W2963261224","https://openalex.org/W2798287483","https://openalex.org/W2913410650","https://openalex.org/W165115930"],"abstract_inverted_index":{"The":[0],"lack":[1],"of":[2,7,59],"labeled":[3],"data":[4],"is":[5,26],"one":[6],"the":[8,47],"main":[9],"challenges":[10],"when":[11],"building":[12],"a":[13,57,70,92],"task-oriented":[14],"dialogue":[15,18,48],"system.":[16],"Existing":[17],"datasets":[19],"usually":[20],"rely":[21],"on":[22],"human":[23,88],"labeling,":[24],"which":[25],"expensive,":[27],"limited":[28],"in":[29,32],"size,":[30],"and":[31,50,68,77,101,104],"low":[33],"coverage.":[34],"In":[35,52],"this":[36,53],"paper,":[37],"we":[38,55],"instead":[39],"propose":[40],"our":[41,84],"framework":[42,85],"auto-dialabel":[43],"to":[44,91],"automatically":[45],"cluster":[46],"intents":[49],"slots.":[51],"framework,":[54],"collect":[56],"set":[58],"context":[60],"features,":[61],"leverage":[62],"an":[63],"autoencoder":[64],"for":[65,75],"feature":[66],"assembly,":[67],"adapt":[69],"dynamic":[71],"hierarchical":[72],"clustering":[73,98],"method":[74],"intent":[76,97],"slot":[78,106],"labeling.":[79],"Experimental":[80],"results":[81],"show":[82],"that":[83],"can":[86],"promote":[87],"labeling":[89,107],"cost":[90],"great":[93],"extent,":[94],"achieve":[95],"good":[96],"accuracy":[99],"(84.1%),":[100],"provide":[102],"reasonable":[103],"instructive":[105],"results.":[108]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}