{"id":"https://openalex.org/W4367047001","doi":"https://doi.org/10.1145/3543507.3583265","title":"Learning Denoised and Interpretable Session Representation for Conversational Search","display_name":"Learning Denoised and Interpretable Session Representation for Conversational Search","publication_year":2023,"publication_date":"2023-04-26","ids":{"openalex":"https://openalex.org/W4367047001","doi":"https://doi.org/10.1145/3543507.3583265"},"language":"en","primary_location":{"id":"doi:10.1145/3543507.3583265","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3543507.3583265","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2023","raw_type":"proceedings-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/A5074229248","display_name":"Kelong Mao","orcid":"https://orcid.org/0000-0002-5648-568X"},"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":true,"raw_author_name":"Kelong Mao","raw_affiliation_strings":["Renmin University of China, China"],"raw_orcid":"https://orcid.org/0000-0002-5648-568X","affiliations":[{"raw_affiliation_string":"Renmin University of China, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010274969","display_name":"Hongjin Qian","orcid":"https://orcid.org/0000-0003-4011-5673"},"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":"Hongjin Qian","raw_affiliation_strings":["Renmin University of China, China"],"raw_orcid":"https://orcid.org/0000-0003-4011-5673","affiliations":[{"raw_affiliation_string":"Renmin University of China, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048033573","display_name":"Fengran Mo","orcid":"https://orcid.org/0000-0002-0838-6994"},"institutions":[{"id":"https://openalex.org/I70931966","display_name":"Universit\u00e9 de Montr\u00e9al","ror":"https://ror.org/0161xgx34","country_code":"CA","type":"education","lineage":["https://openalex.org/I70931966"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Fengran Mo","raw_affiliation_strings":["Universit\u00e9 de Montr\u00e9al, Canada"],"raw_orcid":"https://orcid.org/0000-0002-0838-6994","affiliations":[{"raw_affiliation_string":"Universit\u00e9 de Montr\u00e9al, Canada","institution_ids":["https://openalex.org/I70931966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010558184","display_name":"Zhicheng Dou","orcid":"https://orcid.org/0000-0002-9781-948X"},"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":"Zhicheng Dou","raw_affiliation_strings":["Renmin University of China, China"],"raw_orcid":"https://orcid.org/0000-0002-9781-948X","affiliations":[{"raw_affiliation_string":"Renmin University of China, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056033969","display_name":"Bang Liu","orcid":"https://orcid.org/0000-0002-9483-8984"},"institutions":[{"id":"https://openalex.org/I70931966","display_name":"Universit\u00e9 de Montr\u00e9al","ror":"https://ror.org/0161xgx34","country_code":"CA","type":"education","lineage":["https://openalex.org/I70931966"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Bang Liu","raw_affiliation_strings":["RALI &amp; Mila, Universit\u00e9 de Montr\u00e9al, Canada"],"raw_orcid":"https://orcid.org/0000-0002-9483-8984","affiliations":[{"raw_affiliation_string":"RALI &amp; Mila, Universit\u00e9 de Montr\u00e9al, Canada","institution_ids":["https://openalex.org/I70931966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046312002","display_name":"Xiaohua Cheng","orcid":"https://orcid.org/0000-0002-3533-5279"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohua Cheng","raw_affiliation_strings":["Huawei Poisson Lab, China"],"raw_orcid":"https://orcid.org/0000-0002-3533-5279","affiliations":[{"raw_affiliation_string":"Huawei Poisson Lab, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000839824","display_name":"Zhao Cao","orcid":"https://orcid.org/0000-0002-4214-7858"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhao Cao","raw_affiliation_strings":["Huawei Poisson Lab, China"],"raw_orcid":"https://orcid.org/0000-0002-4214-7858","affiliations":[{"raw_affiliation_string":"Huawei Poisson Lab, China","institution_ids":["https://openalex.org/I2250955327"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5074229248"],"corresponding_institution_ids":["https://openalex.org/I78988378"],"apc_list":null,"apc_paid":null,"fwci":2.6772,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.917634,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3193","last_page":"3202"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9993000030517578,"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":0.9993000030517578,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9987999796867371,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/interpretability","display_name":"Interpretability","score":0.8254750370979309},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.822688102722168},{"id":"https://openalex.org/keywords/session","display_name":"Session (web analytics)","score":0.7362799048423767},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5250071287155151},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4845644533634186},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4788525104522705},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43090352416038513},{"id":"https://openalex.org/keywords/search-engine","display_name":"Search engine","score":0.4268847405910492},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.41353705525398254},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3746546506881714},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.0861363410949707}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8254750370979309},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.822688102722168},{"id":"https://openalex.org/C2779182362","wikidata":"https://www.wikidata.org/wiki/Q17126187","display_name":"Session (web analytics)","level":2,"score":0.7362799048423767},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5250071287155151},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4845644533634186},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4788525104522705},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43090352416038513},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.4268847405910492},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.41353705525398254},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3746546506881714},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0861363410949707},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3543507.3583265","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3543507.3583265","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2023","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.7799999713897705,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W2798482016","https://openalex.org/W2889742741","https://openalex.org/W2970996870","https://openalex.org/W2981852735","https://openalex.org/W2995200518","https://openalex.org/W2998702515","https://openalex.org/W3012014212","https://openalex.org/W3027639267","https://openalex.org/W3034912391","https://openalex.org/W3035169992","https://openalex.org/W3100907046","https://openalex.org/W3103251620","https://openalex.org/W3154280800","https://openalex.org/W3154898636","https://openalex.org/W3172119680","https://openalex.org/W3198536471","https://openalex.org/W3214455632","https://openalex.org/W4226059645","https://openalex.org/W4252076394","https://openalex.org/W4284663260","https://openalex.org/W4284664419","https://openalex.org/W4284685693","https://openalex.org/W4287643741","https://openalex.org/W4288089799","https://openalex.org/W4289674561","https://openalex.org/W4385573600"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W2888392564","https://openalex.org/W4310278675","https://openalex.org/W4388422664","https://openalex.org/W4390569940","https://openalex.org/W4361193272","https://openalex.org/W2963326959","https://openalex.org/W4388685194","https://openalex.org/W4312407344","https://openalex.org/W2894289927"],"abstract_inverted_index":{"Conversational":[0,101],"search":[1,19,24,31,57,71,138],"supports":[2],"multi-turn":[3],"user-system":[4],"interactions":[5],"to":[6,62,124],"solve":[7],"complex":[8,23,69],"information":[9],"needs.":[10],"Compared":[11],"with":[12,109],"the":[13,49,74,86,89,93,106,148],"traditional":[14],"single-turn":[15],"ad-hoc":[16,51],"search,":[17],"conversational":[18,30,43,56,70,137,158],"faces":[20],"a":[21,29,68,98],"more":[22,154],"intent":[25],"understanding":[26],"problem":[27],"because":[28],"session":[32,130],"is":[33],"much":[34],"longer":[35],"and":[36,120,127,143,156],"contains":[37],"many":[38],"noisy":[39],"tokens.":[40],"However,":[41],"existing":[42],"dense":[44],"retrieval":[45],"solutions":[46],"simply":[47],"fine-tune":[48],"pre-trained":[50],"query":[52,122],"encoder":[53],"on":[54,117,134],"limited":[55],"data,":[58],"which":[59,104],"are":[60],"hard":[61],"achieve":[63],"satisfactory":[64],"performance":[65,150],"in":[66,140],"such":[67],"scenario.":[72],"Meanwhile,":[73],"learned":[75],"latent":[76],"representation":[77],"also":[78],"lacks":[79],"interpretability":[80],"that":[81],"people":[82],"cannot":[83],"perceive":[84],"how":[85],"model":[87,108],"understands":[88],"session.":[90],"To":[91],"tackle":[92],"above":[94],"drawbacks,":[95],"we":[96],"propose":[97],"sparse":[99],"Lexical-based":[100],"REtriever":[102],"(LeCoRE),":[103],"extends":[105],"SPLADE":[107],"two":[110],"well-matched":[111],"multi-level":[112],"denoising":[113],"methods":[114],"uniformly":[115],"based":[116],"knowledge":[118],"distillation":[119],"external":[121],"rewrites":[123],"generate":[125],"denoised":[126],"interpretable":[128,157],"lexical":[129],"representation.":[131],"Extensive":[132],"experiments":[133],"four":[135],"public":[136],"datasets":[139],"both":[141],"normal":[142],"zero-shot":[144],"evaluation":[145],"settings":[146],"demonstrate":[147],"strong":[149],"of":[151],"LeCoRE":[152],"towards":[153],"effective":[155],"search.":[159]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5}],"updated_date":"2026-05-10T08:33:47.465468","created_date":"2025-10-10T00:00:00"}
