{"id":"https://openalex.org/W7128989872","doi":"https://doi.org/10.1145/3773966.3777941","title":"Constructing Commonsense Knowledge Graph for Persona Consistency","display_name":"Constructing Commonsense Knowledge Graph for Persona Consistency","publication_year":2026,"publication_date":"2026-02-16","ids":{"openalex":"https://openalex.org/W7128989872","doi":"https://doi.org/10.1145/3773966.3777941"},"language":"en","primary_location":{"id":"doi:10.1145/3773966.3777941","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3773966.3777941","pdf_url":null,"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 Nineteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3773966.3777941","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052313571","display_name":"Lei Xia","orcid":"https://orcid.org/0000-0001-7926-1593"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lei Xia","raw_affiliation_strings":["Tongji University, 0000-0001-7926-1593, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Tongji University, 0000-0001-7926-1593, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105646008","display_name":"Y. Chen","orcid":"https://orcid.org/0000-0002-4381-486X"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuyan Chen","raw_affiliation_strings":["Cornell University, New York, NY, USA"],"affiliations":[{"raw_affiliation_string":"Cornell University, New York, NY, USA","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126132133","display_name":"Xiangqin Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiangqin Chen","raw_affiliation_strings":["The Pennsylvania State University, University Park, USA"],"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University, University Park, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101716765","display_name":"Jixiang Fan","orcid":"https://orcid.org/0009-0008-2778-3136"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jixiang Fan","raw_affiliation_strings":["Virginia Tech, Blacksburg, USA"],"affiliations":[{"raw_affiliation_string":"Virginia Tech, Blacksburg, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046762389","display_name":"Weinan Dai","orcid":"https://orcid.org/0009-0004-1201-3471"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weinan Dai","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126172560","display_name":"Xiaomei Li","orcid":null},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaomei Li","raw_affiliation_strings":["College of Design and Innovation, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"College of Design and Innovation, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124247917","display_name":"Zhixu Li","orcid":null},"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":"Zhixu Li","raw_affiliation_strings":["Suzhou Key Laboratory of Artificial Intelligence and Social Governance Technologies, International College (Suzhou Research Institute), Renmin University of China, Suzhou, China and School of Information, Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Suzhou Key Laboratory of Artificial Intelligence and Social Governance Technologies, International College (Suzhou Research Institute), Renmin University of China, Suzhou, China and School of Information, Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5052313571"],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.40722262,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"756","last_page":"766"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14074","display_name":"Persona Design and Applications","score":0.7687000036239624,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T14074","display_name":"Persona Design and Applications","score":0.7687000036239624,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T12128","display_name":"AI in Service Interactions","score":0.02459999918937683,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.020999999716877937,"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/persona","display_name":"Persona","score":0.9760000109672546},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5989000201225281},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5795999765396118},{"id":"https://openalex.org/keywords/commonsense-knowledge","display_name":"Commonsense knowledge","score":0.44290000200271606},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.43059998750686646},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.426800012588501}],"concepts":[{"id":"https://openalex.org/C313442","wikidata":"https://www.wikidata.org/wiki/Q778556","display_name":"Persona","level":2,"score":0.9760000109672546},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6894999742507935},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5989000201225281},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5795999765396118},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47870001196861267},{"id":"https://openalex.org/C30542707","wikidata":"https://www.wikidata.org/wiki/Q1603203","display_name":"Commonsense knowledge","level":3,"score":0.44290000200271606},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.43059998750686646},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.426800012588501},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.42329999804496765},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.40860000252723694},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.39239999651908875},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.335099995136261},{"id":"https://openalex.org/C2986065213","wikidata":"https://www.wikidata.org/wiki/Q743861","display_name":"Implicit knowledge","level":2,"score":0.3296999931335449},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.3287000060081482},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.2948000133037567},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2883000075817108},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.28380000591278076},{"id":"https://openalex.org/C193221554","wikidata":"https://www.wikidata.org/wiki/Q5153664","display_name":"Commonsense reasoning","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.2565000057220459}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3773966.3777941","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3773966.3777941","pdf_url":null,"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 Nineteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:vtechworks.lib.vt.edu:10919/141640","is_oa":true,"landing_page_url":"https://hdl.handle.net/10919/141640","pdf_url":null,"source":{"id":"https://openalex.org/S4306400248","display_name":"VTechWorks (Virginia Tech)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I859038795","host_organization_name":"Virginia Tech","host_organization_lineage":["https://openalex.org/I859038795"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":null,"raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1145/3773966.3777941","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3773966.3777941","pdf_url":null,"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 Nineteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2101105183","https://openalex.org/W2896457183","https://openalex.org/W2963206148","https://openalex.org/W2963640662","https://openalex.org/W2965373594","https://openalex.org/W2965718149","https://openalex.org/W2979478117","https://openalex.org/W2983160116","https://openalex.org/W3034720580","https://openalex.org/W3034999214","https://openalex.org/W3086550652","https://openalex.org/W3098641803","https://openalex.org/W3106007100","https://openalex.org/W3153128630","https://openalex.org/W4221153924","https://openalex.org/W4288624561","https://openalex.org/W4301518445","https://openalex.org/W4323659873","https://openalex.org/W4385568110","https://openalex.org/W4385732413","https://openalex.org/W4402684058"],"related_works":[],"abstract_inverted_index":{"Ensuring":[0],"consistent":[1,161],"persona":[2,37,67,84,100,113,123,133,151],"in":[3,12,150,176,182,187],"interactive":[4],"AI":[5],"systems":[6],"presents":[7],"a":[8,74,111,138,177],"significant":[9,178],"challenge,":[10],"especially":[11],"diverse":[13],"application":[14],"scenarios":[15],"ranging":[16],"from":[17],"virtual":[18],"assistants":[19],"to":[20,70,191],"customer":[21],"service":[22],"bots.":[23],"Such":[24],"capability":[25],"is":[26],"often":[27],"constrained":[28],"by":[29],"the":[30,54,58,61,66,71,98,129,132,145,153,194],"system's":[31],"understanding":[32],"of":[33,73,131,180],"direct":[34],"and":[35,49,82,121,156,185,197],"explicit":[36,120],"conflicts.":[38],"Traditional":[39],"approaches":[40],"primarily":[41],"focus":[42],"on":[43,106,171],"detecting":[44],"discrepancies":[45],"between":[46,57,86,125],"machine":[47,87,126],"responses":[48,59,88,146],"its":[50],"predefined":[51],"profile,":[52],"or":[53],"contextual":[55],"inconsistencies":[56,85],"at":[60],"semantic":[62],"level":[63],"rather":[64],"than":[65],"level.":[68],"Due":[69],"lack":[72],"comprehensive":[75],"persona-specific":[76],"Commonsense":[77],"Knowledge":[78],"Graph,":[79],"some":[80],"indirect":[81],"implicit":[83,122],"can":[89],"hardly":[90],"be":[91],"identified.":[92],"In":[93],"this":[94],"paper,":[95],"we":[96,108,136],"build":[97],"first":[99,143],"commonsense":[101,134],"knowledge":[102],"graph":[103],"(PersonaKG),":[104],"based":[105],"which":[107,142],"then":[109,157],"construct":[110],"large-scale":[112],"consistency":[114],"dialogue":[115],"dataset":[116],"(PersonaCOM)":[117],"containing":[118],"both":[119],"conflicts":[124],"responses.":[127],"With":[128],"guidance":[130],"knowledge,":[135],"propose":[137],"Recognize-Rewrite":[139],"framework":[140],"(R2)":[141],"recognizes":[144],"that":[147,167],"are":[148],"inconsistent":[149],"with":[152,173],"previous":[154],"responses,":[155],"rewrites":[158],"them":[159],"into":[160],"ones.":[162],"The":[163],"empirical":[164],"study":[165],"demonstrates":[166],"utilizing":[168],"R2":[169,195],"method":[170,196],"PersonaCOM":[172],"PersonaKG":[174],"results":[175],"improvement":[179],"12.20%":[181],"automatic":[183],"metrics":[184],"10.09%":[186],"manual":[188],"evaluation":[189],"compared":[190],"not":[192],"using":[193],"PersonaKG.":[198]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2026-02-17T00:00:00"}
