{"id":"https://openalex.org/W4410244118","doi":"https://doi.org/10.32604/cmc.2025.065127","title":"Multi-View Picture Fuzzy Clustering: A Novel Method for Partitioning Multi-View Relational Data","display_name":"Multi-View Picture Fuzzy Clustering: A Novel Method for Partitioning Multi-View Relational Data","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4410244118","doi":"https://doi.org/10.32604/cmc.2025.065127"},"language":"en","primary_location":{"id":"doi:10.32604/cmc.2025.065127","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.065127","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials &amp; Continua","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.32604/cmc.2025.065127","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076762390","display_name":"Pham Huy Thong","orcid":"https://orcid.org/0000-0001-6502-4466"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Pham Huy Thong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093469320","display_name":"Hoang Thi Canh","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hoang Thi Canh","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087946767","display_name":"Luong Thi Hong Lan","orcid":"https://orcid.org/0000-0002-4083-2253"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luong Thi Hong Lan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070329277","display_name":"Nguyen Tien Huy","orcid":"https://orcid.org/0000-0002-9543-9440"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nguyen Tuan Huy","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5073341529","display_name":"Nguy\u1ec5n Long Giang","orcid":"https://orcid.org/0000-0001-6184-1469"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nguyen Long Giang","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5076762390"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.8843,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.90782481,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"83","issue":"3","first_page":"5461","last_page":"5485"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.8442000150680542,"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":0.8442000150680542,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.7210999727249146,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6852601766586304},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6225845813751221},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.6033331155776978},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5841467380523682},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.579858660697937},{"id":"https://openalex.org/keywords/relational-database","display_name":"Relational database","score":0.44042107462882996},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4351489245891571}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6852601766586304},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6225845813751221},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.6033331155776978},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5841467380523682},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.579858660697937},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.44042107462882996},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4351489245891571}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.32604/cmc.2025.065127","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.065127","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials &amp; Continua","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.32604/cmc.2025.065127","is_oa":true,"landing_page_url":"https://doi.org/10.32604/cmc.2025.065127","pdf_url":null,"source":{"id":"https://openalex.org/S4210191605","display_name":"Computers, materials & continua/Computers, materials & continua (Print)","issn_l":"1546-2218","issn":["1546-2218","1546-2226"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers, Materials &amp; Continua","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W347478911","https://openalex.org/W1937059634","https://openalex.org/W1980564456","https://openalex.org/W2017846705","https://openalex.org/W2100235303","https://openalex.org/W2132885717","https://openalex.org/W2460369835","https://openalex.org/W2518171709","https://openalex.org/W2808465901","https://openalex.org/W2921065608","https://openalex.org/W2964070360","https://openalex.org/W2981206386","https://openalex.org/W3081926674","https://openalex.org/W3087947698","https://openalex.org/W3176694003","https://openalex.org/W4200191747","https://openalex.org/W4225473713","https://openalex.org/W4226080957","https://openalex.org/W4287891019","https://openalex.org/W4367016851","https://openalex.org/W4377235415","https://openalex.org/W4390819631","https://openalex.org/W4400726743","https://openalex.org/W4402639496","https://openalex.org/W4403976971"],"related_works":["https://openalex.org/W2945382830","https://openalex.org/W4224807364","https://openalex.org/W2596632494","https://openalex.org/W2535986621","https://openalex.org/W1980197432","https://openalex.org/W2382432689","https://openalex.org/W2000612978","https://openalex.org/W4388110928","https://openalex.org/W1483228865","https://openalex.org/W4292434959"],"abstract_inverted_index":{"Multi-view":[0,79],"clustering":[1,27,56,74,163,176,223],"is":[2],"a":[3,52,64,112,179,184],"critical":[4],"research":[5],"area":[6],"in":[7,37,162,244],"computer":[8],"science":[9],"aimed":[10],"at":[11],"effectively":[12],"extracting":[13],"meaningful":[14],"patterns":[15],"from":[16],"complex,":[17],"high-dimensional":[18],"data":[19,120,133,219],"that":[20,58],"single-view":[21],"methods":[22],"cannot":[23],"capture.":[24],"Traditional":[25],"fuzzy":[26,55,61,88,123],"techniques,":[28],"such":[29,213],"as":[30,214],"Fuzzy":[31,81],"C-Means":[32],"(FCM),":[33],"face":[34],"significant":[35,160],"challenges":[36],"handling":[38,148],"uncertainty":[39,96],"and":[40,76,106,118,135,145,150,165,190,204,221,242],"the":[41,86,92,129,171,198,231],"dependencies":[42],"between":[43,132],"different":[44],"views.":[45,139],"To":[46],"overcome":[47],"these":[48],"limitations,":[49],"we":[50],"introduce":[51],"new":[53],"multi-view":[54,69,217,235],"approach":[57,208],"integrates":[59],"picture":[60,87],"sets":[62],"with":[63],"dual-anchor":[65,126],"graph":[66],"method":[67,232],"for":[68,111,197,233],"data,":[70],"aiming":[71,237],"to":[72,94,211,238],"enhance":[73,239],"accuracy":[75,164],"robustness,":[77],"termed":[78],"Picture":[80],"Clustering":[82],"(MPFC).":[83],"In":[84],"particular,":[85],"set":[89],"theory":[90],"extends":[91],"capability":[93],"represent":[95],"by":[97],"modeling":[98],"three":[99],"membership":[100,102],"levels:":[101],"degrees,":[103,105],"neutral":[104],"refusal":[107],"degrees.":[108],"This":[109,140],"allows":[110],"more":[113],"flexible":[114],"representation":[115],"of":[116,181,188,195],"uncertain":[117],"conflicting":[119],"than":[121],"traditional":[122,168],"models.":[124],"Meanwhile,":[125],"graphs":[127],"exploit":[128],"similarity":[130],"relationships":[131],"points":[134],"integrate":[136],"information":[137],"across":[138],"combination":[141],"improves":[142],"stability,":[143],"scalability,":[144,241],"robustness":[146,203],"when":[147],"noisy":[149],"heterogeneous":[151],"data.":[152],"Experimental":[153],"results":[154],"on":[155,178,229],"several":[156],"benchmark":[157],"datasets":[158],"demonstrate":[159],"improvements":[161],"efficiency,":[166],"outperforming":[167],"methods.":[169],"Specifically,":[170],"MPFC":[172],"algorithm":[173],"demonstrates":[174],"outstanding":[175],"performance":[177,243],"variety":[180],"datasets,":[182],"attaining":[183],"Purity":[185],"(PUR)":[186],"score":[187,194],"0.6440":[189],"an":[191],"Accuracy":[192],"(ACC)":[193],"0.6213":[196],"3Sources":[199],"dataset,":[200],"underscoring":[201],"its":[202],"efficiency.":[205],"The":[206],"proposed":[207],"significantly":[209],"contributes":[210],"fields":[212],"pattern":[215],"recognition,":[216],"relational":[218],"analysis,":[220],"large-scale":[222],"problems.":[224],"Future":[225],"work":[226],"will":[227],"focus":[228],"extending":[230],"semi-supervised":[234],"clustering,":[236],"adaptability,":[240],"real-world":[245],"applications.":[246]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
