{"id":"https://openalex.org/W3113653553","doi":"https://doi.org/10.18653/v1/2020.coling-main.437","title":"Intra-/Inter-Interaction Network with Latent Interaction Modeling for Multi-turn Response Selection","display_name":"Intra-/Inter-Interaction Network with Latent Interaction Modeling for Multi-turn Response Selection","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3113653553","doi":"https://doi.org/10.18653/v1/2020.coling-main.437","mag":"3113653553"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2020.coling-main.437","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2020.coling-main.437","pdf_url":"https://www.aclweb.org/anthology/2020.coling-main.437.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 28th International Conference on Computational Linguistics","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/2020.coling-main.437.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5050035602","display_name":"Yang Deng","orcid":"https://orcid.org/0000-0002-8122-5943"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yang Deng","raw_affiliation_strings":["The Chinese University of Hong Kong"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115595118","display_name":"Wenxuan Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenxuan Zhang","raw_affiliation_strings":["The Chinese University of Hong Kong"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018582154","display_name":"Wai Lam","orcid":"https://orcid.org/0000-0001-5479-377X"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wai Lam","raw_affiliation_strings":["The Chinese University of Hong Kong"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5050035602"],"corresponding_institution_ids":["https://openalex.org/I177725633"],"apc_list":null,"apc_paid":null,"fwci":0.1326,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.56995791,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"4981","last_page":"4992"},"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/T12031","display_name":"Speech and dialogue systems","score":0.998199999332428,"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":0.9973000288009644,"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":0.9233613014221191},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7918587923049927},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6233329772949219},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6016291975975037},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.5558983683586121},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5372182726860046},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5199605226516724},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4982471466064453},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43936747312545776},{"id":"https://openalex.org/keywords/conversation","display_name":"Conversation","score":0.436064749956131},{"id":"https://openalex.org/keywords/communication","display_name":"Communication","score":0.06617945432662964}],"concepts":[{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.9233613014221191},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7918587923049927},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6233329772949219},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6016291975975037},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.5558983683586121},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5372182726860046},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5199605226516724},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4982471466064453},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43936747312545776},{"id":"https://openalex.org/C2777200299","wikidata":"https://www.wikidata.org/wiki/Q52943","display_name":"Conversation","level":2,"score":0.436064749956131},{"id":"https://openalex.org/C46312422","wikidata":"https://www.wikidata.org/wiki/Q11024","display_name":"Communication","level":1,"score":0.06617945432662964},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2020.coling-main.437","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2020.coling-main.437","pdf_url":"https://www.aclweb.org/anthology/2020.coling-main.437.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 28th International Conference on Computational Linguistics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2020.coling-main.437","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2020.coling-main.437","pdf_url":"https://www.aclweb.org/anthology/2020.coling-main.437.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 28th International Conference on Computational Linguistics","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3113653553.pdf","grobid_xml":"https://content.openalex.org/works/W3113653553.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W2153579005","https://openalex.org/W2197546379","https://openalex.org/W2339852062","https://openalex.org/W2521114121","https://openalex.org/W2561368124","https://openalex.org/W2767802162","https://openalex.org/W2786983967","https://openalex.org/W2798392716","https://openalex.org/W2798456655","https://openalex.org/W2798534672","https://openalex.org/W2822830299","https://openalex.org/W2851948290","https://openalex.org/W2891416139","https://openalex.org/W2898233200","https://openalex.org/W2908331278","https://openalex.org/W2949446780","https://openalex.org/W2952813980","https://openalex.org/W2962854379","https://openalex.org/W2963035145","https://openalex.org/W2963134326","https://openalex.org/W2963365397","https://openalex.org/W2963403868","https://openalex.org/W2963838657","https://openalex.org/W2964092386","https://openalex.org/W2964309167","https://openalex.org/W2964837208","https://openalex.org/W2965538838","https://openalex.org/W2970648534","https://openalex.org/W2983537304","https://openalex.org/W2985686011","https://openalex.org/W2988869004","https://openalex.org/W2988964532","https://openalex.org/W3012707646","https://openalex.org/W3034842667","https://openalex.org/W4294170691","https://openalex.org/W4300687842","https://openalex.org/W4385245566","https://openalex.org/W4393072862"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W1968552888","https://openalex.org/W2468279273","https://openalex.org/W2374116601","https://openalex.org/W3093134843","https://openalex.org/W1511346092","https://openalex.org/W1527532029","https://openalex.org/W2529301793","https://openalex.org/W2378167147","https://openalex.org/W3133700904"],"abstract_inverted_index":{"Multi-turn":[0],"response":[1,96,142],"selection":[2,143],"has":[3],"been":[4],"extensively":[5],"studied":[6],"and":[7,26,50,81,101,123,133],"applied":[8],"to":[9,72,115],"many":[10],"real-world":[11],"applications":[12],"in":[13,55],"recent":[14],"years.":[15],"However,":[16],"current":[17],"methods":[18,138],"typically":[19],"model":[20,74,116],"the":[21,37,78,82,89,94,102,117,121,129],"interactions":[22,76],"between":[23,77,120],"multi-turn":[24,141],"utterances":[25],"candidate":[27],"responses":[28],"with":[29,68,93],"iterative":[30],"approaches,":[31],"which":[32],"is":[33],"not":[34],"practical":[35],"as":[36,47],"turns":[38],"of":[39],"conversations":[40],"vary.":[41],"Besides,":[42],"some":[43],"latent":[44,69,110,118],"features,":[45],"such":[46],"user":[48],"intent":[49],"conversation":[51],"topic,":[52],"are":[53],"under-discovered":[54],"existing":[56,136],"works.":[57],"In":[58,84],"this":[59],"work,":[60],"we":[61,86,107],"propose":[62],"Intra-/Inter-Interaction":[63],"Network":[64],"(I":[65],"3":[66],")":[67],"interaction":[70,92,119],"modeling":[71],"comprehensively":[73],"multi-level":[75],"utterance":[79,100,104,122],"context":[80],"response.":[83,124],"specific,":[85],"first":[87],"encode":[88],"intra-and":[90],"inter-utterance":[91],"given":[95],"from":[97],"both":[98],"individual":[99],"overall":[103],"context.":[105],"Then":[106],"develop":[108],"a":[109],"multi-view":[111],"subspace":[112],"clustering":[113],"module":[114],"Experimental":[125],"results":[126],"show":[127],"that":[128],"proposed":[130],"method":[131],"substantially":[132],"consistently":[134],"outperforms":[135],"state-of-the-art":[137],"on":[139],"three":[140],"benchmark":[144],"datasets.":[145]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
