{"id":"https://openalex.org/W7143754668","doi":"https://doi.org/10.20736/0002002107","title":"Evaluating Group Fairness and Relevance in Conversational Search: An Alternative Formulation","display_name":"Evaluating Group Fairness and Relevance in Conversational Search: An Alternative Formulation","publication_year":null,"publication_date":null,"ids":{"openalex":"https://openalex.org/W7143754668","doi":"https://doi.org/10.20736/0002002107"},"language":"en","primary_location":{"id":"pmh:oai:irdb.nii.ac.jp:03100:0006839270","is_oa":true,"landing_page_url":"https://repository.nii.ac.jp/records/2002107","pdf_url":"https://repository.nii.ac.jp/record/2002107/files/03-EVIA2025-EVIA-SakaiT.pdf","source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"},"type":"conference-paper","indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://repository.nii.ac.jp/record/2002107/files/03-EVIA2025-EVIA-SakaiT.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5131154020","display_name":"Tetsuya Sakai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tetsuya Sakai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091105421","display_name":"Sijie Tao","orcid":"https://orcid.org/0000-0002-6751-5303"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sijie Tao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5131426416","display_name":"Young-In Song","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Young-In Song","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"none","last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.30559998750686646,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.30559998750686646,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T13274","display_name":"Expert finding and Q&A systems","score":0.22750000655651093,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.13009999692440033,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/relevance","display_name":"Relevance (law)","score":0.8690000176429749},{"id":"https://openalex.org/keywords/conversation","display_name":"Conversation","score":0.7526000142097473},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7185999751091003},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5871999859809875},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.508899986743927},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.5034000277519226}],"concepts":[{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.8690000176429749},{"id":"https://openalex.org/C2777200299","wikidata":"https://www.wikidata.org/wiki/Q52943","display_name":"Conversation","level":2,"score":0.7526000142097473},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7185999751091003},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6104000210762024},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5871999859809875},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.508899986743927},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5034000277519226},{"id":"https://openalex.org/C2781311116","wikidata":"https://www.wikidata.org/wiki/Q83306","display_name":"Group (periodic table)","level":2,"score":0.47110000252723694},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3675000071525574},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3458999991416931},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3343000113964081},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.32249999046325684},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.29910001158714294},{"id":"https://openalex.org/C3017738328","wikidata":"https://www.wikidata.org/wiki/Q613366","display_name":"User group","level":2,"score":0.28790000081062317},{"id":"https://openalex.org/C2985126265","wikidata":"https://www.wikidata.org/wiki/Q1637368","display_name":"Task group","level":2,"score":0.27309998869895935},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2621000111103058},{"id":"https://openalex.org/C2780829048","wikidata":"https://www.wikidata.org/wiki/Q1624720","display_name":"Conversation analysis","level":3,"score":0.2549999952316284}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:irdb.nii.ac.jp:03100:0006839270","is_oa":true,"landing_page_url":"https://repository.nii.ac.jp/records/2002107","pdf_url":"https://repository.nii.ac.jp/record/2002107/files/03-EVIA2025-EVIA-SakaiT.pdf","source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"}],"best_oa_location":{"id":"pmh:oai:irdb.nii.ac.jp:03100:0006839270","is_oa":true,"landing_page_url":"https://repository.nii.ac.jp/records/2002107","pdf_url":"https://repository.nii.ac.jp/record/2002107/files/03-EVIA2025-EVIA-SakaiT.pdf","source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7143754668.pdf","grobid_xml":"https://content.openalex.org/works/W7143754668.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"Conversational":[1],"Search":[2],"(CS)":[3],"subtask":[4],"of":[5,59,73,83,90,114,131],"the":[6,22,25,38,45,56,60,71,95,98,104,121,129,138],"NTCIR-18":[7],"FairWeb-2":[8,139],"task":[9,72],"used":[10],"Sakai's":[11],"GFRC":[12,36],"(Group":[13,62],"Fairness":[14,29,63,108],"and":[15,27,37,64,106],"Relevance":[16,26,105],"for":[17,20,67,87,111],"Conversations)":[18],"measure":[19,39],"evaluating":[21,74],"participating":[23],"systems.As":[24],"Group":[28,107],"components":[30],"were":[31],"not":[32],"directly":[33,54],"integrated":[34],"in":[35],"lacked":[40],"a":[41,81,88,124],"clear":[42],"user":[43,85],"model,":[44],"present":[46],"pilot":[47],"study":[48],"discusses":[49],"an":[50],"alternative":[51],"called":[52],"GFRC2.By":[53],"transferring":[55],"general":[57],"idea":[58],"GFR":[61],"Relevance)":[65],"framework":[66],"web":[68],"search":[69],"to":[70,119],"generated":[75],"conversations,":[76],"we":[77],"formulate":[78],"GFRC2":[79,133],"as":[80],"form":[82],"expected":[84],"experience":[86],"population":[89],"users":[91,115],"who":[92,116],"go":[93],"through":[94],"words":[96],"within":[97],"conversation.This":[99],"also":[100],"lets":[101],"us":[102],"visualise":[103],"component":[109],"scores":[110],"each":[112],"cluster":[113],"are":[117],"assumed":[118],"abandon":[120],"conversation":[122],"at":[123],"particular":[125],"relevant":[126],"nugget.We":[127],"demonstrate":[128],"steps":[130],"computing":[132],"using":[134],"real":[135],"runs":[136],"from":[137],"CS":[140],"subtask.":[141]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-04-01T00:00:00"}
