{"id":"https://openalex.org/W7125932945","doi":"https://doi.org/10.1109/smc58881.2025.11343370","title":"A method to visualize evaluation factors affect satisfaction in surveys of the service industry using XAI: evaluation for cram school service as an example","display_name":"A method to visualize evaluation factors affect satisfaction in surveys of the service industry using XAI: evaluation for cram school service as an example","publication_year":2025,"publication_date":"2025-10-05","ids":{"openalex":"https://openalex.org/W7125932945","doi":"https://doi.org/10.1109/smc58881.2025.11343370"},"language":null,"primary_location":{"id":"doi:10.1109/smc58881.2025.11343370","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343370","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5124120724","display_name":"Masao Nakahara","orcid":null},"institutions":[{"id":"https://openalex.org/I8488066","display_name":"Chiba Institute of Technology","ror":"https://ror.org/00qwnam72","country_code":"JP","type":"education","lineage":["https://openalex.org/I8488066"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Masao Nakahara","raw_affiliation_strings":["Chiba Institute of Technology,Faculty of Advanced Engineering,Department of Advanced Media,Chiba,Japan,275-0016"],"affiliations":[{"raw_affiliation_string":"Chiba Institute of Technology,Faculty of Advanced Engineering,Department of Advanced Media,Chiba,Japan,275-0016","institution_ids":["https://openalex.org/I8488066"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124099083","display_name":"Fumiaki Saitoh","orcid":null},"institutions":[{"id":"https://openalex.org/I131231118","display_name":"Aoyama Gakuin University","ror":"https://ror.org/002rw7y37","country_code":"JP","type":"education","lineage":["https://openalex.org/I131231118"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Fumiaki Saitoh","raw_affiliation_strings":["Aoyama Gakuin University,College of Science and Engineering,Department of Industrial and Systems Engineering,Sagamihara City, Kanagawa,Japan"],"affiliations":[{"raw_affiliation_string":"Aoyama Gakuin University,College of Science and Engineering,Department of Industrial and Systems Engineering,Sagamihara City, Kanagawa,Japan","institution_ids":["https://openalex.org/I131231118"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5124120724"],"corresponding_institution_ids":["https://openalex.org/I8488066"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.76667028,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"692","last_page":"695"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.15719999372959137,"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/T11122","display_name":"Online Learning and Analytics","score":0.15719999372959137,"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/T12128","display_name":"AI in Service Interactions","score":0.07530000060796738,"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/T12884","display_name":"Educational Assessment and Pedagogy","score":0.04520000144839287,"subfield":{"id":"https://openalex.org/subfields/3304","display_name":"Education"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.7440999746322632},{"id":"https://openalex.org/keywords/affect","display_name":"Affect (linguistics)","score":0.7095000147819519},{"id":"https://openalex.org/keywords/grasp","display_name":"GRASP","score":0.6358000040054321},{"id":"https://openalex.org/keywords/chart","display_name":"Chart","score":0.4731999933719635},{"id":"https://openalex.org/keywords/customer-satisfaction","display_name":"Customer satisfaction","score":0.451200008392334},{"id":"https://openalex.org/keywords/service","display_name":"Service (business)","score":0.40950000286102295},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.38100001215934753},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.38100001215934753}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.7440999746322632},{"id":"https://openalex.org/C2776035688","wikidata":"https://www.wikidata.org/wiki/Q1606558","display_name":"Affect (linguistics)","level":2,"score":0.7095000147819519},{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.6358000040054321},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5577999949455261},{"id":"https://openalex.org/C190812933","wikidata":"https://www.wikidata.org/wiki/Q28923","display_name":"Chart","level":2,"score":0.4731999933719635},{"id":"https://openalex.org/C191511416","wikidata":"https://www.wikidata.org/wiki/Q999278","display_name":"Customer satisfaction","level":2,"score":0.451200008392334},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.40950000286102295},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.38100001215934753},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.38100001215934753},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3610999882221222},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.33649998903274536},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.32499998807907104},{"id":"https://openalex.org/C43246008","wikidata":"https://www.wikidata.org/wiki/Q55638","display_name":"Tertiary sector of the economy","level":2,"score":0.31859999895095825},{"id":"https://openalex.org/C527412718","wikidata":"https://www.wikidata.org/wiki/Q855395","display_name":"Interpretation (philosophy)","level":2,"score":0.29109999537467957},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C539667460","wikidata":"https://www.wikidata.org/wiki/Q2414942","display_name":"Management science","level":1,"score":0.2815999984741211},{"id":"https://openalex.org/C27209215","wikidata":"https://www.wikidata.org/wiki/Q1192777","display_name":"Radar chart","level":2,"score":0.28130000829696655},{"id":"https://openalex.org/C140781008","wikidata":"https://www.wikidata.org/wiki/Q1221081","display_name":"Service quality","level":3,"score":0.27410000562667847},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.27230000495910645},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.26919999718666077},{"id":"https://openalex.org/C56995899","wikidata":"https://www.wikidata.org/wiki/Q1126687","display_name":"Focus group","level":2,"score":0.2630000114440918}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc58881.2025.11343370","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343370","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5932394862174988}],"awards":[],"funders":[{"id":"https://openalex.org/F4320327550","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W2282821441","https://openalex.org/W3167451058","https://openalex.org/W3176714582"],"related_works":[],"abstract_inverted_index":{"In":[0],"this":[1],"study,":[2],"we":[3],"focus":[4],"on":[5,46,74,135],"explainable":[6],"artificial":[7],"intelligence":[8],"(XAI),":[9],"which":[10,95],"improves":[11],"the":[12,29,49,55,64,75,121,139,143],"interpretability":[13],"of":[14,51,54,67,77,107,138,145],"learning":[15],"models":[16],"that":[17,31,141],"tend":[18],"to":[19,27,40,82,93,103,117,130],"become":[20],"black":[21],"boxes,":[22],"and":[23,102,147],"propose":[24],"a":[25,38,60,70],"method":[26,39],"visualize":[28,41],"factors":[30,140],"affect":[32,142],"customer":[33],"satisfaction.":[34],"We":[35,110],"have":[36],"developed":[37],"trends":[42,85],"across":[43],"features":[44],"based":[45,73,134],"t-SNE":[47,68],"using":[48],"contribution":[50,76],"LIME,":[52,94],"one":[53],"most":[56],"representative":[57],"XAIs,":[58],"as":[59],"variable.":[61],"By":[62],"expanding":[63],"output":[65],"results":[66],"into":[69],"bubble":[71],"chart":[72],"variables,":[78],"it":[79,116,127],"becomes":[80],"possible":[81],"grasp":[83],"overall":[84,108],"regarding":[86],"satisfaction":[87],"at":[88],"cram":[89,123,132],"schools,":[90],"in":[91],"contrast":[92],"provides":[96],"an":[97,105,136],"interpretation":[98],"for":[99],"each":[100],"sample,":[101],"support":[104],"understanding":[106,137],"needs.":[109],"confirmed":[111],"its":[112],"effectiveness":[113],"by":[114],"applying":[115],"survey":[118],"data":[119],"from":[120],"Japanese":[122],"school":[124],"industry,":[125],"where":[126],"is":[128],"desirable":[129],"operate":[131],"schools":[133],"needs":[144],"students":[146],"parents.":[148]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-01-29T00:00:00"}