{"id":"https://openalex.org/W4309675258","doi":"https://doi.org/10.1109/smc53654.2022.9945376","title":"Layered Perceptual Modeling Using Structural Equation Modeling: Exploring Structure with Genetic Algorithm","display_name":"Layered Perceptual Modeling Using Structural Equation Modeling: Exploring Structure with Genetic Algorithm","publication_year":2022,"publication_date":"2022-10-09","ids":{"openalex":"https://openalex.org/W4309675258","doi":"https://doi.org/10.1109/smc53654.2022.9945376"},"language":"en","primary_location":{"id":"doi:10.1109/smc53654.2022.9945376","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc53654.2022.9945376","pdf_url":null,"source":{"id":"https://openalex.org/S4363607746","display_name":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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":"2022 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/A5062660811","display_name":"Shuhei Watanabe","orcid":"https://orcid.org/0000-0001-6611-2812"},"institutions":[{"id":"https://openalex.org/I24193003","display_name":"Ricoh (Japan)","ror":"https://ror.org/02h4myp42","country_code":"JP","type":"company","lineage":["https://openalex.org/I24193003"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Shuhei Watanabe","raw_affiliation_strings":["Ricoh Company Ltd.,Digital Strategy Division,Kanagawa,Japan","Digital Strategy Division, Ricoh Company Ltd., Kanagawa, Japan"],"affiliations":[{"raw_affiliation_string":"Ricoh Company Ltd.,Digital Strategy Division,Kanagawa,Japan","institution_ids":["https://openalex.org/I24193003"]},{"raw_affiliation_string":"Digital Strategy Division, Ricoh Company Ltd., Kanagawa, Japan","institution_ids":["https://openalex.org/I24193003"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060692543","display_name":"Takahiko Horiuchi","orcid":"https://orcid.org/0000-0002-8197-6499"},"institutions":[{"id":"https://openalex.org/I159385669","display_name":"Chiba University","ror":"https://ror.org/01hjzeq58","country_code":"JP","type":"education","lineage":["https://openalex.org/I159385669"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takahiko Horiuchi","raw_affiliation_strings":["Chiba University,Graduate School of Engineering,Chiba,Japan","Graduate School of Engineering, Chiba University, Chiba, Japan"],"affiliations":[{"raw_affiliation_string":"Chiba University,Graduate School of Engineering,Chiba,Japan","institution_ids":["https://openalex.org/I159385669"]},{"raw_affiliation_string":"Graduate School of Engineering, Chiba University, Chiba, Japan","institution_ids":["https://openalex.org/I159385669"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5062660811"],"corresponding_institution_ids":["https://openalex.org/I24193003"],"apc_list":null,"apc_paid":null,"fwci":0.2229,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.44748079,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"574","last_page":"579"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12496","display_name":"Color perception and design","score":0.9894000291824341,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12496","display_name":"Color perception and design","score":0.9894000291824341,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10427","display_name":"Visual perception and processing mechanisms","score":0.9692999720573425,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/structural-equation-modeling","display_name":"Structural equation modeling","score":0.7935465574264526},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6035887002944946},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5241166353225708},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5198153257369995},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.5191980600357056},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3292645215988159},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1857265830039978},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.10976022481918335}],"concepts":[{"id":"https://openalex.org/C71104824","wikidata":"https://www.wikidata.org/wiki/Q1476639","display_name":"Structural equation modeling","level":2,"score":0.7935465574264526},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6035887002944946},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5241166353225708},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5198153257369995},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.5191980600357056},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3292645215988159},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1857265830039978},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.10976022481918335},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc53654.2022.9945376","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc53654.2022.9945376","pdf_url":null,"source":{"id":"https://openalex.org/S4363607746","display_name":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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":22,"referenced_works":["https://openalex.org/W1994853093","https://openalex.org/W1999371986","https://openalex.org/W2047094503","https://openalex.org/W2071356986","https://openalex.org/W2083001397","https://openalex.org/W2088615693","https://openalex.org/W2135633183","https://openalex.org/W2135655476","https://openalex.org/W2519326300","https://openalex.org/W2571061804","https://openalex.org/W2614829919","https://openalex.org/W2752234108","https://openalex.org/W2767554017","https://openalex.org/W2804272685","https://openalex.org/W2890770907","https://openalex.org/W2900283551","https://openalex.org/W2946338602","https://openalex.org/W2998376245","https://openalex.org/W3009081138","https://openalex.org/W3021730278","https://openalex.org/W3198941087","https://openalex.org/W7005934235"],"related_works":["https://openalex.org/W2024934382","https://openalex.org/W2303173273","https://openalex.org/W2513767888","https://openalex.org/W3147308590","https://openalex.org/W1528049813","https://openalex.org/W1968285868","https://openalex.org/W2364043478","https://openalex.org/W4388140417","https://openalex.org/W3153451317","https://openalex.org/W4313635805"],"abstract_inverted_index":{"To":[0],"differentiate":[1],"from":[2,154,161],"competitors,":[3],"it":[4,189],"has":[5],"become":[6],"increasingly":[7],"important":[8,195],"to":[9,48,62,66,98,120,139,193],"design":[10],"products":[11,27],"based":[12,88],"on":[13,89],"the":[14,23,50,63,73,77,80,90,93,112,121,140,179],"\u201cKansei":[15],"value,\u201d":[16],"which":[17,32],"impresses":[18],"and":[19,59,68,86,150,176],"inspires":[20],"consumers.":[21],"However,":[22],"perceptual":[24,169],"indices":[25],"of":[26,79,92,111,123,147,157,184],"are":[28],"generally":[29],"designed":[30],"qualitatively,":[31],"is":[33,82,187],"not":[34],"only":[35],"time-consuming":[36],"but":[37],"also":[38],"costly.":[39],"Therefore,":[40,95],"in":[41],"recent":[42],"years,":[43],"studies":[44],"have":[45],"been":[46],"conducted":[47],"discuss":[49],"relationship":[51,78,153],"between":[52],"some":[53,105],"perceptions":[54],"by":[55,84,115],"applying":[56,116],"multivariate":[57],"analysis":[58],"machine":[60],"learning":[61],"adjectives":[64,81],"related":[65],"perception":[67,142],"affective":[69],"response.":[70],"Nonetheless,":[71],"determining":[72],"structure":[74,114],"that":[75,171,188,197],"expresses":[76],"obtained":[83],"trial":[85],"error,":[87],"hypothesis":[91,110],"researchers.":[94],"we":[96,133,165],"aimed":[97],"investigate":[99],"a":[100,109,117,135,152,155,168],"method":[101],"for":[102,144],"mechanically":[103],"exploring":[104],"semi-optimal":[106],"structures":[107,196],"without":[108],"model":[113,137,170],"genetic":[118],"algorithm":[119],"construction":[122],"adjective":[124],"relationships":[125],"using":[126,178],"structural":[127],"equation":[128],"modeling.":[129],"In":[130],"this":[131,185],"study,":[132],"prepared":[134],"four-layered":[136],"according":[138],"human":[141],"process":[143],"eight":[145],"categories":[146],"material":[148],"samples":[149],"constructed":[151],"total":[156],"20":[158],"words":[159],"perceived":[160],"each":[162],"sample.":[163],"Consequently,":[164],"could":[166],"construct":[167,194],"can":[172,190],"be":[173,191,199],"interpreted":[174],"quantitatively":[175],"semantically":[177],"proposed":[180],"method.":[181],"The":[182],"advantage":[183],"technique":[186],"used":[192],"might":[198],"overlooked.":[200]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
