{"id":"https://openalex.org/W2508101854","doi":"https://doi.org/10.18653/v1/p16-1194","title":"Hidden Softmax Sequence Model for Dialogue Structure Analysis","display_name":"Hidden Softmax Sequence Model for Dialogue Structure Analysis","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2508101854","doi":"https://doi.org/10.18653/v1/p16-1194","mag":"2508101854"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p16-1194","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p16-1194","pdf_url":"https://www.aclweb.org/anthology/P16-1194.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 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P16-1194.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047512906","display_name":"Zhiyang He","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyang He","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100674776","display_name":"Xien Liu","orcid":"https://orcid.org/0000-0002-4947-0631"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Xien Liu","raw_affiliation_strings":["Tsinghua-iFlytek Joint Laboratory for Speech Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua-iFlytek Joint Laboratory for Speech Technology, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100828802","display_name":"Ping Lv","orcid":"https://orcid.org/0000-0001-6095-3397"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ping Lv","raw_affiliation_strings":["Tsinghua-iFlytek Joint Laboratory for Speech Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua-iFlytek Joint Laboratory for Speech Technology, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101235840","display_name":"Ji Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ji Wu","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100674776"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7139,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.88996815,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"2063","last_page":"2072"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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":0.9998000264167786,"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":0.996399998664856,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9914000034332275,"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/softmax-function","display_name":"Softmax function","score":0.9762617945671082},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.776801586151123},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.7361657619476318},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.7244166135787964},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6870056986808777},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.6507939100265503},{"id":"https://openalex.org/keywords/restricted-boltzmann-machine","display_name":"Restricted Boltzmann machine","score":0.5675942301750183},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5634886622428894},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.4680848717689514},{"id":"https://openalex.org/keywords/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.4668850004673004},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.34830498695373535},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07278275489807129}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.9762617945671082},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.776801586151123},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.7361657619476318},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.7244166135787964},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6870056986808777},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.6507939100265503},{"id":"https://openalex.org/C199354608","wikidata":"https://www.wikidata.org/wiki/Q7316287","display_name":"Restricted Boltzmann machine","level":3,"score":0.5675942301750183},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5634886622428894},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.4680848717689514},{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.4668850004673004},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.34830498695373535},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07278275489807129},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","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/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p16-1194","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p16-1194","pdf_url":"https://www.aclweb.org/anthology/P16-1194.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 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/p16-1194","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p16-1194","pdf_url":"https://www.aclweb.org/anthology/P16-1194.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 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2508101854.pdf","grobid_xml":"https://content.openalex.org/works/W2508101854.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W35388109","https://openalex.org/W1513873506","https://openalex.org/W1516111018","https://openalex.org/W1516554472","https://openalex.org/W1654173042","https://openalex.org/W1853745982","https://openalex.org/W1985514943","https://openalex.org/W2042096436","https://openalex.org/W2044120473","https://openalex.org/W2089285937","https://openalex.org/W2096192494","https://openalex.org/W2100002341","https://openalex.org/W2102409316","https://openalex.org/W2116064496","https://openalex.org/W2116825644","https://openalex.org/W2118370253","https://openalex.org/W2144100511","https://openalex.org/W2146447174","https://openalex.org/W2169218343","https://openalex.org/W2170323078","https://openalex.org/W2251949648","https://openalex.org/W2294861638","https://openalex.org/W2567948266","https://openalex.org/W2949952668","https://openalex.org/W4237840503","https://openalex.org/W4239181501","https://openalex.org/W4293503257"],"related_works":["https://openalex.org/W2888805565","https://openalex.org/W4312773271","https://openalex.org/W4315588616","https://openalex.org/W2769501189","https://openalex.org/W2962686197","https://openalex.org/W2207653751","https://openalex.org/W4293863151","https://openalex.org/W3159709618","https://openalex.org/W2611137333","https://openalex.org/W3209162324"],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,54],"new":[3],"unsupervised":[4],"learning":[5],"model,":[6],"hidden":[7,29,78],"softmax":[8,36,79],"sequence":[9],"model":[10,21,72,112],"(HSSM),":[11],"based":[12],"on":[13],"Boltzmann":[14],"machine":[15],"for":[16,101],"dialogue":[17,33,67,94],"structure":[18],"analysis.":[19],"The":[20],"employs":[22],"three":[23],"types":[24],"of":[25,42,91],"units":[26,37,45,80],"in":[27],"the":[28,59,65,71,83,106,110],"layer":[30],"to":[31,81],"discovery":[32],"latent":[34,40,48,86],"structures:":[35],"which":[38,46],"represent":[39,47],"states":[41],"utterances;":[43],"binary":[44,55],"topics":[49],"specified":[50],"by":[51],"dialogues;":[52],"and":[53,97,105],"unit":[56],"that":[57,109],"represents":[58],"global":[60],"general":[61],"topic":[62],"shared":[63],"across":[64],"whole":[66],"corpus.":[68],"In":[69],"addition,":[70],"contains":[73],"extra":[74],"connections":[75],"between":[76,85],"adjacent":[77],"formulate":[82],"dependency":[84],"states.":[87],"Two":[88],"different":[89],"kinds":[90],"real":[92],"world":[93],"corpora,":[95],"Twitter-Post":[96],"AirTicketBooking,":[98],"are":[99],"utilized":[100],"extensive":[102],"comparing":[103],"experiments,":[104],"results":[107],"illustrate":[108],"proposed":[111],"outperforms":[113],"sate-ofthe-art":[114],"popular":[115],"approaches.":[116]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}