{"id":"https://openalex.org/W7118009983","doi":"https://doi.org/10.1109/tfuzz.2025.3650110","title":"Parameter-Free Dual-Granularity Weighted Multiview Fuzzy $c$-Means Clustering","display_name":"Parameter-Free Dual-Granularity Weighted Multiview Fuzzy $c$-Means Clustering","publication_year":2026,"publication_date":"2026-01-02","ids":{"openalex":"https://openalex.org/W7118009983","doi":"https://doi.org/10.1109/tfuzz.2025.3650110"},"language":null,"primary_location":{"id":"doi:10.1109/tfuzz.2025.3650110","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2025.3650110","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on 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/A5121446277","display_name":"Zhe Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210109434","display_name":"Xinyu University","ror":"https://ror.org/021xwcd05","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210109434"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhe Liu","raw_affiliation_strings":["College of Mathematics and Computer, Xinyu University, Xinyu, China"],"raw_orcid":"https://orcid.org/0000-0002-8580-9655","affiliations":[{"raw_affiliation_string":"College of Mathematics and Computer, Xinyu University, Xinyu, China","institution_ids":["https://openalex.org/I4210109434"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121431149","display_name":"Jiahao Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahao Shi","raw_affiliation_strings":["College of Computer Science and Technology, Harbin Engineering University, Harbin, China"],"raw_orcid":"https://orcid.org/0009-0004-1469-0628","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Harbin Engineering University, Harbin, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073999917","display_name":"Sukumar Letchmunan","orcid":"https://orcid.org/0000-0002-3521-7141"},"institutions":[{"id":"https://openalex.org/I139322472","display_name":"Universiti Sains Malaysia","ror":"https://ror.org/02rgb2k63","country_code":"MY","type":"education","lineage":["https://openalex.org/I139322472"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Sukumar Letchmunan","raw_affiliation_strings":["School of Computer Sciences, Universiti Sains Malaysia, Penang, Malaysia"],"raw_orcid":"https://orcid.org/0000-0002-3521-7141","affiliations":[{"raw_affiliation_string":"School of Computer Sciences, Universiti Sains Malaysia, Penang, Malaysia","institution_ids":["https://openalex.org/I139322472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121773188","display_name":"Yulong Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210109434","display_name":"Xinyu University","ror":"https://ror.org/021xwcd05","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210109434"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yulong Huang","raw_affiliation_strings":["College of Mathematics and Computer, Xinyu University, Xinyu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mathematics and Computer, Xinyu University, Xinyu, China","institution_ids":["https://openalex.org/I4210109434"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051710693","display_name":"Muhammet Deveci","orcid":"https://orcid.org/0000-0002-3712-976X"},"institutions":[{"id":"https://openalex.org/I157637111","display_name":"Naval Academy","ror":"https://ror.org/05syseh24","country_code":"TR","type":"education","lineage":["https://openalex.org/I157637111"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Muhammet Deveci","raw_affiliation_strings":["Department of Industrial Engineering, Turkish Naval Academy, National Defence University, Tuzla, T&#x00FC;rkiye"],"raw_orcid":"https://orcid.org/0000-0002-3712-976X","affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, Turkish Naval Academy, National Defence University, Tuzla, T&#x00FC;rkiye","institution_ids":["https://openalex.org/I157637111"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0318819,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"34","issue":"3","first_page":"870","last_page":"880"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9348000288009644,"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"}},"topics":[{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9348000288009644,"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/T10057","display_name":"Face and Expression Recognition","score":0.02160000056028366,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11550","display_name":"Text and Document Classification Technologies","score":0.002899999963119626,"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/interpretability","display_name":"Interpretability","score":0.7505000233650208},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7301999926567078},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.7218999862670898},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6484000086784363},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.5321999788284302},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5181000232696533},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.44209998846054077},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.41260001063346863},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4097999930381775}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.7505000233650208},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7301999926567078},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.7218999862670898},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6534000039100647},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6484000086784363},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5465999841690063},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.5321999788284302},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5181000232696533},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44290000200271606},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.44209998846054077},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.41260001063346863},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4097999930381775},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.40869998931884766},{"id":"https://openalex.org/C111442797","wikidata":"https://www.wikidata.org/wiki/Q7291446","display_name":"Rand index","level":3,"score":0.37470000982284546},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.3709000051021576},{"id":"https://openalex.org/C27964816","wikidata":"https://www.wikidata.org/wiki/Q5164359","display_name":"Constrained clustering","level":5,"score":0.3260999917984009},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32519999146461487},{"id":"https://openalex.org/C63085389","wikidata":"https://www.wikidata.org/wiki/Q4287912","display_name":"Medoid","level":3,"score":0.3188999891281128},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.31349998712539673},{"id":"https://openalex.org/C2639959","wikidata":"https://www.wikidata.org/wiki/Q1344778","display_name":"Distance measures","level":2,"score":0.31299999356269836},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.30410000681877136},{"id":"https://openalex.org/C129782007","wikidata":"https://www.wikidata.org/wiki/Q162886","display_name":"Euclidean geometry","level":2,"score":0.29829999804496765},{"id":"https://openalex.org/C70136482","wikidata":"https://www.wikidata.org/wiki/Q13583781","display_name":"A-weighting","level":3,"score":0.28769999742507935},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.274399995803833},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.2705000042915344},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2687999904155731},{"id":"https://openalex.org/C139502532","wikidata":"https://www.wikidata.org/wiki/Q1122090","display_name":"Computational intelligence","level":2,"score":0.2662999927997589},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.25769999623298645}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tfuzz.2025.3650110","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2025.3650110","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on 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":45,"referenced_works":["https://openalex.org/W2108154570","https://openalex.org/W2108502868","https://openalex.org/W2136753665","https://openalex.org/W2141429283","https://openalex.org/W2159091719","https://openalex.org/W2210977594","https://openalex.org/W2441795274","https://openalex.org/W2586686153","https://openalex.org/W2590019597","https://openalex.org/W2751768089","https://openalex.org/W2766258899","https://openalex.org/W2790896944","https://openalex.org/W2887768066","https://openalex.org/W3016050434","https://openalex.org/W3036015371","https://openalex.org/W3045894993","https://openalex.org/W3131778097","https://openalex.org/W3167023447","https://openalex.org/W3201737266","https://openalex.org/W4213418104","https://openalex.org/W4220654722","https://openalex.org/W4299300164","https://openalex.org/W4310225030","https://openalex.org/W4310494058","https://openalex.org/W4313410482","https://openalex.org/W4377235415","https://openalex.org/W4388580674","https://openalex.org/W4389076299","https://openalex.org/W4389937721","https://openalex.org/W4391653295","https://openalex.org/W4394015595","https://openalex.org/W4394711308","https://openalex.org/W4400112754","https://openalex.org/W4401485050","https://openalex.org/W4402448414","https://openalex.org/W4402676361","https://openalex.org/W4403390515","https://openalex.org/W4403976971","https://openalex.org/W4404509882","https://openalex.org/W4406079958","https://openalex.org/W4407794168","https://openalex.org/W4408398387","https://openalex.org/W4409347423","https://openalex.org/W4410141156","https://openalex.org/W4412453446"],"related_works":[],"abstract_inverted_index":{"It":[0],"remains":[1],"a":[2,26,40,150],"challenge":[3],"in":[4],"multi-view":[5,30,157],"clustering":[6,32],"to":[7,38,72,143],"effectively":[8,128],"integrate":[9],"heterogeneous":[10],"views":[11,73,134],"while":[12,137],"reducing":[13],"the":[14,45,130,138,146],"impact":[15],"of":[16,133],"noise":[17],"and":[18,47,52,74,76,88,103,135,153,162],"redundancy.":[19],"To":[20],"tackle":[21],"this":[22],"issue,":[23],"we":[24],"propose":[25],"parameter-free":[27],"dual-granularity":[28,126],"weighted":[29],"fuzzy$c$-means":[31],"framework.":[33],"The":[34],"basic":[35],"idea":[36],"is":[37],"introduce":[39],"product-to-one":[41],"constraint":[42],"at":[43],"both":[44,86],"view":[46],"attribute":[48],"levels,":[49],"enabling":[50],"adaptive":[51],"balanced":[53],"weight":[54],"assignment":[55],"without":[56],"introducing":[57],"extra":[58],"parameters.":[59],"Two":[60],"weighting":[61,127],"strategies":[62],"are":[63,94],"developed:":[64],"(i)":[65],"vector-form":[66],"weighting,":[67,79],"which":[68,80],"assigns":[69],"global":[70],"importance":[71,132],"attributes,":[75,136],"(ii)":[77],"matrix-form":[78],"further":[81],"captures":[82],"cluster-specific":[83],"relevance.":[84],"Moreover,":[85],"Euclidean":[87],"non-Euclidean":[89,139],"(exponential":[90],"transformation)":[91],"distance":[92,140],"measures":[93],"incorporated,":[95],"yielding":[96],"four":[97],"algorithmic":[98],"variants:":[99],"PDW-MFC-V,":[100],"PDW-MFC-M,":[101],"PDW-MAFC-V,":[102],"PDW-MAFC-M.":[104],"Extensive":[105],"experiments":[106],"on":[107],"nine":[108],"real-world":[109],"datasets":[110],"show":[111],"that":[112,125],"our":[113],"algorithms":[114,118],"outperform":[115],"thirteen":[116],"related":[117],"across":[119,165],"multiple":[120],"metrics.":[121],"These":[122],"results":[123],"confirm":[124],"models":[129],"relative":[131],"improves":[141],"robustness":[142],"noise.":[144],"Overall,":[145],"proposed":[147],"framework":[148],"offers":[149],"flexible,":[151],"parameter-free,":[152],"robust":[154],"solution":[155],"for":[156],"clustering,":[158],"providing":[159],"fine-grained":[160],"interpretability":[161],"stable":[163],"performance":[164],"diverse":[166],"datasets.":[167]},"counts_by_year":[],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2026-01-02T00:00:00"}
