{"id":"https://openalex.org/W4213239468","doi":"https://doi.org/10.1145/3488560.3498393","title":"Improving the Applicability of Knowledge-Enhanced Dialogue Generation Systems by Using Heterogeneous Knowledge from Multiple Sources","display_name":"Improving the Applicability of Knowledge-Enhanced Dialogue Generation Systems by Using Heterogeneous Knowledge from Multiple Sources","publication_year":2022,"publication_date":"2022-02-11","ids":{"openalex":"https://openalex.org/W4213239468","doi":"https://doi.org/10.1145/3488560.3498393"},"language":"en","primary_location":{"id":"doi:10.1145/3488560.3498393","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3488560.3498393","pdf_url":null,"source":{"id":"https://openalex.org/S4363608885","display_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","issn_l":null,"issn":null,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","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/A5103185340","display_name":"Sixing Wu","orcid":"https://orcid.org/0000-0001-7278-8720"},"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":true,"raw_author_name":"Sixing Wu","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100376902","display_name":"Minghui Wang","orcid":"https://orcid.org/0000-0002-5788-894X"},"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":"Minghui Wang","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100342640","display_name":"Ying Li","orcid":"https://orcid.org/0000-0001-7589-7295"},"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":"Ying Li","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100379743","display_name":"Dawei Zhang","orcid":"https://orcid.org/0000-0002-0841-7826"},"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":"Dawei Zhang","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041563693","display_name":"Zhonghai Wu","orcid":"https://orcid.org/0000-0003-1268-836X"},"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":"Zhonghai Wu","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5103185340"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":1.9749,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.88149106,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1149","last_page":"1157"},"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9990000128746033,"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":0.9976000189781189,"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":0.8261977434158325},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7785220146179199},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.46371224522590637},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.45815742015838623},{"id":"https://openalex.org/keywords/knowledge-extraction","display_name":"Knowledge extraction","score":0.42479759454727173},{"id":"https://openalex.org/keywords/knowledge-management","display_name":"Knowledge management","score":0.39714038372039795},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3087077736854553}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8261977434158325},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7785220146179199},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.46371224522590637},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.45815742015838623},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.42479759454727173},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.39714038372039795},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3087077736854553},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3488560.3498393","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3488560.3498393","pdf_url":null,"source":{"id":"https://openalex.org/S4363608885","display_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","issn_l":null,"issn":null,"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W2094728533","https://openalex.org/W2098985784","https://openalex.org/W2101105183","https://openalex.org/W2561529111","https://openalex.org/W2804552794","https://openalex.org/W2950902819","https://openalex.org/W2952420867","https://openalex.org/W2963521540","https://openalex.org/W2970260827","https://openalex.org/W2970579055","https://openalex.org/W2971199636","https://openalex.org/W2997094605","https://openalex.org/W2997300509","https://openalex.org/W2998083599","https://openalex.org/W3034556525","https://openalex.org/W3034569646","https://openalex.org/W3034606970","https://openalex.org/W3034758256","https://openalex.org/W3035356453","https://openalex.org/W3093956460","https://openalex.org/W3101212722","https://openalex.org/W3118010541","https://openalex.org/W3212092284","https://openalex.org/W4206908526","https://openalex.org/W4213052788","https://openalex.org/W4290742115"],"related_works":["https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W2352448290","https://openalex.org/W2380820513","https://openalex.org/W2913146933","https://openalex.org/W2372385138","https://openalex.org/W4296359239","https://openalex.org/W2101155126","https://openalex.org/W2043093291","https://openalex.org/W2363545964"],"abstract_inverted_index":{"Traditional":[0],"conversational":[1],"systems":[2],"can":[3,90,120],"only":[4,40],"access":[5],"the":[6,10,37,57,66,122,161],"given":[7],"query":[8],"during":[9],"response":[11],"generation,":[12],"leading":[13],"to":[14,22,76,106],"meaningless":[15],"responses.":[16],"To":[17,64],"this":[18],"end,":[19],"researchers":[20],"proposed":[21],"enhance":[23],"dialogue":[24],"generation":[25],"by":[26,95],"integrating":[27],"external":[28],"knowledge.":[29,63],"Although":[30],"such":[31],"methods":[32,47],"have":[33],"achieved":[34],"remarkable":[35],"gains,":[36],"use":[38,77,91],"of":[39,56,61,68,124,164],"single-source":[41,62],"knowledge":[42,59,79,94,98,109,151],"often":[43],"makes":[44],"existing":[45],"knowledge-enhanced":[46,69],"degenerate":[48],"into":[49],"traditional":[50],"models":[51,127],"in":[52],"real":[53],"scenarios":[54],"because":[55],"insufficient":[58],"coverage":[60],"improve":[65],"applicability":[67],"methods,":[70],"we":[71,134],"propose":[72,85],"two":[73],"novel":[74],"frameworks":[75],"heterogeneous":[78,93],"from":[80,137],"multiple":[81,108],"sources.":[82],"We":[83],"first":[84],"an":[86],"MHKD-Seq2Seq":[87],"framework,":[88],"which":[89,148],"different":[92],"identifying":[96],"abstract-level":[97],"behaviors;":[99],"meanwhile,":[100],"a":[101,113,143],"Diffuse-Aggregate":[102],"scheme":[103],"is":[104],"used":[105],"process":[107],"simultaneously":[110],"and":[111,141,155],"produce":[112],"unified":[114],"result.":[115],"The":[116],"next":[117],"framework":[118],"MHKD-ARPLM":[119],"leverage":[121],"advantages":[123],"pretrained":[125],"language":[126],"with":[128],"Knowledge":[129],"Linearization":[130],"techniques.":[131],"In":[132],"experiments,":[133],"collected":[135],"dialogues":[136],"previously":[138],"open-released":[139],"datasets":[140],"built":[142],"multi-source":[144],"knowledge-aligned":[145],"dataset":[146],"TriKE-Weibo,":[147],"involves":[149],"three":[150],"sources:":[152],"commonsense,":[153],"texts,":[154],"infobox":[156],"tables.":[157],"Extensive":[158],"evaluations":[159],"demonstrate":[160],"performance":[162],"leadership":[163],"our":[165],"approaches":[166],"against":[167],"competitive":[168],"baseline":[169],"models.":[170]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}