{"id":"https://openalex.org/W3155556971","doi":"https://doi.org/10.3233/jifs-201829","title":"Integrating rough set theory with customer satisfaction to construct a novel approach for mining product design rules","display_name":"Integrating rough set theory with customer satisfaction to construct a novel approach for mining product design rules","publication_year":2021,"publication_date":"2021-04-16","ids":{"openalex":"https://openalex.org/W3155556971","doi":"https://doi.org/10.3233/jifs-201829","mag":"3155556971"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-201829","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-201829","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent &amp; Fuzzy Systems","raw_type":"journal-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/A5007112289","display_name":"Tianxiong Wang","orcid":"https://orcid.org/0000-0003-4020-0368"},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianxiong Wang","raw_affiliation_strings":["School of Art Design and Media, East China University of Science and Technology, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Art Design and Media, East China University of Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I143593769"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063714820","display_name":"Meiyu Zhou","orcid":"https://orcid.org/0009-0001-7239-514X"},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Meiyu Zhou","raw_affiliation_strings":["School of Art Design and Media, East China University of Science and Technology, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Art Design and Media, East China University of Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I143593769"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5063714820"],"corresponding_institution_ids":["https://openalex.org/I143593769"],"apc_list":null,"apc_paid":null,"fwci":6.7497,"has_fulltext":false,"cited_by_count":33,"citation_normalized_percentile":{"value":0.97091263,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"41","issue":"1","first_page":"331","last_page":"353"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12496","display_name":"Color perception and design","score":0.9993000030517578,"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":0.9993000030517578,"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/T11666","display_name":"Color Science and Applications","score":0.9574000239372253,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12114","display_name":"Sensory Analysis and Statistical Methods","score":0.9412999749183655,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/kansei-engineering","display_name":"Kansei engineering","score":0.8222681283950806},{"id":"https://openalex.org/keywords/rough-set","display_name":"Rough set","score":0.8074322938919067},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6502382755279541},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5763459205627441},{"id":"https://openalex.org/keywords/association-rule-learning","display_name":"Association rule learning","score":0.5735281705856323},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.563431441783905},{"id":"https://openalex.org/keywords/kansei","display_name":"Kansei","score":0.5409939885139465},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5164313912391663},{"id":"https://openalex.org/keywords/product-design","display_name":"Product design","score":0.5113431811332703},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.5088067650794983},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5063797235488892},{"id":"https://openalex.org/keywords/fuzzy-set","display_name":"Fuzzy set","score":0.4859517812728882},{"id":"https://openalex.org/keywords/customer-satisfaction","display_name":"Customer satisfaction","score":0.4766705334186554},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.43057310581207275},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4059017300605774},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35015225410461426},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2743092179298401},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.16707593202590942},{"id":"https://openalex.org/keywords/marketing","display_name":"Marketing","score":0.11989977955818176}],"concepts":[{"id":"https://openalex.org/C2780562538","wikidata":"https://www.wikidata.org/wiki/Q1075418","display_name":"Kansei engineering","level":2,"score":0.8222681283950806},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.8074322938919067},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6502382755279541},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5763459205627441},{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.5735281705856323},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.563431441783905},{"id":"https://openalex.org/C2781297728","wikidata":"https://www.wikidata.org/wiki/Q1195131","display_name":"Kansei","level":2,"score":0.5409939885139465},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5164313912391663},{"id":"https://openalex.org/C120823896","wikidata":"https://www.wikidata.org/wiki/Q1043226","display_name":"Product design","level":3,"score":0.5113431811332703},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.5088067650794983},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5063797235488892},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.4859517812728882},{"id":"https://openalex.org/C191511416","wikidata":"https://www.wikidata.org/wiki/Q999278","display_name":"Customer satisfaction","level":2,"score":0.4766705334186554},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.43057310581207275},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4059017300605774},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35015225410461426},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2743092179298401},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.16707593202590942},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.11989977955818176},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jifs-201829","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-201829","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent &amp; Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":90,"referenced_works":["https://openalex.org/W199743680","https://openalex.org/W955265301","https://openalex.org/W1585155070","https://openalex.org/W1770898509","https://openalex.org/W1965757285","https://openalex.org/W1972223166","https://openalex.org/W1973040469","https://openalex.org/W1973733364","https://openalex.org/W1977599143","https://openalex.org/W1984483758","https://openalex.org/W1984711715","https://openalex.org/W1988166728","https://openalex.org/W1999209397","https://openalex.org/W2000113052","https://openalex.org/W2001589718","https://openalex.org/W2003869977","https://openalex.org/W2007117621","https://openalex.org/W2008112332","https://openalex.org/W2008627526","https://openalex.org/W2011833972","https://openalex.org/W2014292152","https://openalex.org/W2014342438","https://openalex.org/W2014442694","https://openalex.org/W2015187650","https://openalex.org/W2022408565","https://openalex.org/W2036913038","https://openalex.org/W2036959577","https://openalex.org/W2041036882","https://openalex.org/W2048512778","https://openalex.org/W2051594262","https://openalex.org/W2055718428","https://openalex.org/W2068033140","https://openalex.org/W2073377944","https://openalex.org/W2077565335","https://openalex.org/W2080733212","https://openalex.org/W2080802424","https://openalex.org/W2081024207","https://openalex.org/W2089155985","https://openalex.org/W2098268836","https://openalex.org/W2102297485","https://openalex.org/W2104695428","https://openalex.org/W2116856683","https://openalex.org/W2122878061","https://openalex.org/W2126397993","https://openalex.org/W2128823042","https://openalex.org/W2131314315","https://openalex.org/W2138034253","https://openalex.org/W2143599027","https://openalex.org/W2156166463","https://openalex.org/W2166559705","https://openalex.org/W2182756997","https://openalex.org/W2194015003","https://openalex.org/W2235706682","https://openalex.org/W2280196970","https://openalex.org/W2316288013","https://openalex.org/W2333743022","https://openalex.org/W2359182618","https://openalex.org/W2515684830","https://openalex.org/W2550032732","https://openalex.org/W2555124530","https://openalex.org/W2560303928","https://openalex.org/W2563404506","https://openalex.org/W2576571101","https://openalex.org/W2587708284","https://openalex.org/W2725270116","https://openalex.org/W2790581077","https://openalex.org/W2792067563","https://openalex.org/W2792848070","https://openalex.org/W2902724603","https://openalex.org/W2912565176","https://openalex.org/W2944053194","https://openalex.org/W2953607237","https://openalex.org/W2953822493","https://openalex.org/W2954656134","https://openalex.org/W2968381506","https://openalex.org/W2974716119","https://openalex.org/W2979173878","https://openalex.org/W2997198052","https://openalex.org/W2998574808","https://openalex.org/W2999988434","https://openalex.org/W3003287379","https://openalex.org/W3008401153","https://openalex.org/W3008429170","https://openalex.org/W3024018979","https://openalex.org/W3144697070","https://openalex.org/W4211007335","https://openalex.org/W4255833381","https://openalex.org/W6635101376","https://openalex.org/W6695086064","https://openalex.org/W6749027773"],"related_works":["https://openalex.org/W2233343369","https://openalex.org/W2351945265","https://openalex.org/W2014292152","https://openalex.org/W2171827594","https://openalex.org/W2362403288","https://openalex.org/W2365988382","https://openalex.org/W2306194170","https://openalex.org/W4383617823","https://openalex.org/W1981504922","https://openalex.org/W4283657785"],"abstract_inverted_index":{"When":[0],"users":[1],"choose":[2],"a":[3,145],"product,":[4,123],"they":[5],"consider":[6],"the":[7,12,18,28,41,99,115,122,126,130,157,160,169,178,189,217,225,230],"emotional":[8],"experience":[9],"triggered":[10],"by":[11],"product":[13,106,162,214],"form.":[14],"In":[15,165],"view":[16],"of":[17,34,118,121,159,191,203,219],"fact":[19],"that":[20,229],"traditional":[21],"kansei":[22,176],"engineering":[23],"can":[24,233],"not":[25,39],"effectively":[26],"reflect":[27],"complex":[29,42],"and":[30,36,47,61,105,124,148,152,175,206],"changeable":[31],"psychological":[32],"factors":[33],"users,":[35],"it":[37],"has":[38],"explored":[40],"relationship":[43,101,171],"between":[44,102,172],"customer":[45,245],"satisfaction":[46,132],"perceptual":[48],"demand":[49,127],"characteristics.":[50],"To":[51],"address":[52],"this":[53,73],"problem,":[54],"some":[55],"uncertainty":[56],"techniques":[57],"including":[58],"rough":[59,82],"sets":[60,63],"fuzzy":[62,87,91,179,193],"are":[64,133],"applied":[65,112,186],"to":[66,97,113,143,155,167,187,210,240],"capture":[67],"more":[68],"accurate":[69],"emotion":[70],"knowledge.":[71],"Therefore,":[72],"research":[74],"proposes":[75],"an":[76,223],"integrated":[77],"evaluation":[78],"gird":[79],"method":[80,96,140,184,232],"(EGM),":[81],"set":[83,190],"theory":[84],"(RST),":[85],"continuous":[86],"kano":[88],"model":[89],"(CFKM),":[90],"weighted":[92,180,194],"association":[93,181,195],"rule":[94,182],"mining":[95,183],"extract":[98],"significant":[100],"user":[103,212],"needs":[104],"morphological":[107,119],"features.":[108],"The":[109,137],"EGM":[110],"is":[111,141],"analyze":[114],"attractive":[116],"factor":[117],"characteristics":[120],"then":[125],"items":[128],"with":[129],"highest":[131],"analyzed":[134],"through":[135,149],"CFKM.":[136],"semantic":[138],"difference":[139],"combined":[142],"construct":[144],"decision":[146],"table,":[147],"attribute":[150],"reduction":[151],"importance":[153],"calculation":[154],"obtain":[156,188],"weight":[158],"core":[161],"design":[163,173,218],"items.":[164],"order":[166],"explore":[168],"non-linear":[170],"elements":[174],"images,":[177],"was":[185],"frequent":[192],"rules":[196],"based":[197],"on":[198],"evidence":[199],"theory\u2019s":[200],"reliability":[201],"indices":[202],"minimum":[204],"support":[205],"confidence":[207],"so":[208],"as":[209,222],"realize":[211],"demand-driven":[213],"design.":[215],"Taking":[216],"electric":[220],"bicycle":[221],"example,":[224],"experiment":[226],"results":[227],"show":[228],"proposed":[231],"help":[234],"companies":[235],"or":[236],"designers":[237],"develop":[238],"products":[239],"generate":[241],"good":[242],"solutions":[243],"for":[244],"need.":[246]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":7}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
