{"id":"https://openalex.org/W3193603894","doi":"https://doi.org/10.1145/3462207","title":"Response Ranking with Multi-types of Deep Interactive Representations in Retrieval-based Dialogues","display_name":"Response Ranking with Multi-types of Deep Interactive Representations in Retrieval-based Dialogues","publication_year":2021,"publication_date":"2021-08-17","ids":{"openalex":"https://openalex.org/W3193603894","doi":"https://doi.org/10.1145/3462207","mag":"3193603894"},"language":"en","primary_location":{"id":"doi:10.1145/3462207","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3462207","pdf_url":null,"source":{"id":"https://openalex.org/S4394735545","display_name":"ACM Transactions on Information Systems","issn_l":"1046-8188","issn":["1046-8188","1558-2868"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Information Systems","raw_type":"journal-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/A5013828154","display_name":"Ruijian Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210161752","display_name":"Beijing Haidian Hospital","ror":"https://ror.org/058x5eq06","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210161752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruijian Xu","raw_affiliation_strings":["Peking University, Haidian, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University, Haidian, Beijing, China","institution_ids":["https://openalex.org/I4210161752"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073065834","display_name":"Chongyang Tao","orcid":"https://orcid.org/0000-0002-4162-2119"},"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":"Chongyang Tao","raw_affiliation_strings":["Wangxuan Institute of Computer Technology, Peking University, Haidian, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wangxuan Institute of Computer Technology, Peking University, Haidian, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013569210","display_name":"Jiazhan Feng","orcid":"https://orcid.org/0000-0002-5832-6199"},"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":"Jiazhan Feng","raw_affiliation_strings":["Wangxuan Institute of Computer Technology, Peking University, Haidian, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wangxuan Institute of Computer Technology, Peking University, Haidian, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101796417","display_name":"Wei Wu","orcid":"https://orcid.org/0000-0001-6572-8471"},"institutions":[{"id":"https://openalex.org/I4210161752","display_name":"Beijing Haidian Hospital","ror":"https://ror.org/058x5eq06","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210161752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Wu","raw_affiliation_strings":["Microsoft Corporation, Haidian, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Haidian, Beijing, China","institution_ids":["https://openalex.org/I4210161752"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100716372","display_name":"Rui Yan","orcid":"https://orcid.org/0000-0002-3356-6823"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Yan","raw_affiliation_strings":["Gaoling School of Artificial Intelligence, Renmin University of China, Haidian, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Gaoling School of Artificial Intelligence, Renmin University of China, Haidian, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037132097","display_name":"Dongyan Zhao","orcid":"https://orcid.org/0000-0002-0396-6703"},"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":"Dongyan Zhao","raw_affiliation_strings":["Wangxuan Institute of Computer Technology, Peking University, Haidian, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wangxuan Institute of Computer Technology, Peking University, Haidian, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8189,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.77925262,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"39","issue":"4","first_page":"1","last_page":"28"},"is_retracted":false,"is_paratext":false,"is_xpac":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/T12031","display_name":"Speech and dialogue systems","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/T10181","display_name":"Natural Language Processing Techniques","score":0.9984999895095825,"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/computer-science","display_name":"Computer science","score":0.8575913906097412},{"id":"https://openalex.org/keywords/utterance","display_name":"Utterance","score":0.7469769716262817},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6551520228385925},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6318035125732422},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6170690059661865},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5896854400634766},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5501287579536438},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5479516983032227},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5290226936340332},{"id":"https://openalex.org/keywords/meaning","display_name":"Meaning (existential)","score":0.4812457263469696},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.44950661063194275},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.4396061599254608},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.353374183177948},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.16065698862075806},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07957214117050171}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8575913906097412},{"id":"https://openalex.org/C2775852435","wikidata":"https://www.wikidata.org/wiki/Q258403","display_name":"Utterance","level":2,"score":0.7469769716262817},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6551520228385925},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6318035125732422},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6170690059661865},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5896854400634766},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5501287579536438},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5479516983032227},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5290226936340332},{"id":"https://openalex.org/C2780876879","wikidata":"https://www.wikidata.org/wiki/Q3054749","display_name":"Meaning (existential)","level":2,"score":0.4812457263469696},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.44950661063194275},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.4396061599254608},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.353374183177948},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.16065698862075806},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07957214117050171},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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:10.1145/3462207","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3462207","pdf_url":null,"source":{"id":"https://openalex.org/S4394735545","display_name":"ACM Transactions on Information Systems","issn_l":"1046-8188","issn":["1046-8188","1558-2868"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Information Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6399999856948853,"display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G367289946","display_name":null,"funder_award_id":"61876196","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1614298861","https://openalex.org/W1924770834","https://openalex.org/W1975244201","https://openalex.org/W1978394996","https://openalex.org/W2064675550","https://openalex.org/W2157331557","https://openalex.org/W2197546379","https://openalex.org/W2339852062","https://openalex.org/W2561368124","https://openalex.org/W2608787653","https://openalex.org/W2798456655","https://openalex.org/W2891416139","https://openalex.org/W2892181857","https://openalex.org/W2899423466","https://openalex.org/W2908331278","https://openalex.org/W2938224087","https://openalex.org/W2952813980","https://openalex.org/W2962854379","https://openalex.org/W2963167310","https://openalex.org/W2963341956","https://openalex.org/W2963446712","https://openalex.org/W2963527228","https://openalex.org/W2963542836","https://openalex.org/W2963715136","https://openalex.org/W2963825865","https://openalex.org/W2963963856","https://openalex.org/W2964092386","https://openalex.org/W2964110616","https://openalex.org/W2964309167","https://openalex.org/W2970648534","https://openalex.org/W2985686011","https://openalex.org/W2997308257","https://openalex.org/W3094612274","https://openalex.org/W3097517997","https://openalex.org/W3099023595","https://openalex.org/W4230273322","https://openalex.org/W4236521339","https://openalex.org/W4237823148","https://openalex.org/W4247780151"],"related_works":["https://openalex.org/W2468279273","https://openalex.org/W2529301793","https://openalex.org/W2384121599","https://openalex.org/W2038083449","https://openalex.org/W2562096895","https://openalex.org/W2333799855","https://openalex.org/W2354198838","https://openalex.org/W3177678247","https://openalex.org/W1999617572","https://openalex.org/W1989130879"],"abstract_inverted_index":{"Building":[0],"an":[1,127],"intelligent":[2],"dialogue":[3,67,101,131,265],"system":[4],"with":[5,102],"the":[6,24,58,61,71,74,77,100,106,110,113,135,138,142,200,204,215,229,240,256],"ability":[7],"to":[8,14,126,171],"select":[9],"a":[10,15,27,47,51,119,152,219],"proper":[11],"response":[12,78,114,177,261],"according":[13],"multi-turn":[16,260],"context":[17,59,75,111,143],"is":[18,30],"challenging":[19],"in":[20,66,81,91,118,263],"three":[21,235],"aspects:":[22],"(1)":[23],"meaning":[25],"of":[26,130,137,167,184,206,226],"context\u2013response":[28,230],"pair":[29],"built":[31],"upon":[32],"language":[33],"units":[34],"from":[35],"multiple":[36,82,165,224],"granularities":[37],"(e.g.,":[38,46,55],"words,":[39],"phrases,":[40],"and":[41,53,60,69,76,105,112,133,144,189,195,211,217,250],"sub-sentences,":[42],"etc.);":[43],"(2)":[44],"local":[45],"small":[48],"window":[49],"around":[50],"word)":[52],"long-range":[54,212],"words":[56],"across":[57],"response)":[62],"dependencies":[63,213],"may":[64,124],"exist":[65],"data;":[68],"(3)":[70],"relationship":[72],"between":[73,109,141,228],"candidate":[79,115],"lies":[80],"relevant":[83],"semantic":[84,89,139],"clues":[85,90],"or":[86],"relatively":[87],"implicit":[88],"some":[92],"real":[93],"cases.":[94],"However,":[95],"existing":[96],"approaches":[97],"usually":[98],"encode":[99],"mono-type":[103],"representation":[104,153,216],"interaction":[107],"processes":[108],"are":[116],"executed":[117],"rather":[120],"shallow":[121],"manner,":[122],"which":[123],"lead":[125],"inadequate":[128],"understanding":[129],"content":[132],"hinder":[134],"recognition":[136],"relevance":[140],"response.":[145],"To":[146],"tackle":[147],"these":[148],"challenges,":[149],"we":[150,180],"propose":[151],"[":[154,158],"K":[155],"]":[156,160],"-interaction":[157],"L":[159],"-matching":[161],"framework":[162],"that":[163,239],"explores":[164],"types":[166,183],"deep":[168],"interactive":[169],"representations":[170,185],"build":[172],"context-response":[173,247],"matching":[174,248],"models":[175,249],"for":[176,186,259],"selection.":[178],"Particularly,":[179],"construct":[181],"different":[182],"utterance\u2013response":[187],"pairs":[188],"deepen":[190],"them":[191],"via":[192],"alternate":[193],"encoding":[194],"interaction.":[196],"By":[197],"this":[198],"means,":[199],"model":[201,242,258],"can":[202],"handle":[203],"relation":[205],"neighboring":[207],"elements,":[208],"phrasal":[209],"pattern,":[210],"during":[214],"make":[218],"more":[220],"accurate":[221],"prediction":[222],"through":[223],"layers":[225],"interactions":[227],"pair.":[231],"Experiment":[232],"results":[233,254],"on":[234],"public":[236],"benchmarks":[237],"indicate":[238],"proposed":[241],"significantly":[243],"outperforms":[244],"previous":[245],"conventional":[246],"achieve":[251],"slightly":[252],"better":[253],"than":[255],"BERT":[257],"selection":[262],"retrieval-based":[264],"systems.":[266]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}