{"id":"https://openalex.org/W2000141452","doi":"https://doi.org/10.1109/iccais.2014.7020552","title":"An improved kernel-induced possibilistic fuzzy c-means clustering algorithm based on dispersion control","display_name":"An improved kernel-induced possibilistic fuzzy c-means clustering algorithm based on dispersion control","publication_year":2014,"publication_date":"2014-12-01","ids":{"openalex":"https://openalex.org/W2000141452","doi":"https://doi.org/10.1109/iccais.2014.7020552","mag":"2000141452"},"language":"en","primary_location":{"id":"doi:10.1109/iccais.2014.7020552","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccais.2014.7020552","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2014 International Conference on Control, Automation and Information Sciences (ICCAIS 2014)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5003627780","display_name":"Jeonghwan Gwak","orcid":"https://orcid.org/0000-0002-6237-0141"},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jeonghwan Gwak","raw_affiliation_strings":["School of Information and Communications, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea","School of Information and Communications, Gwangju Institute of Science and Technology, 123 Cheomdan-gwagiro, Buk-gu, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communications, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea","institution_ids":["https://openalex.org/I39534123"]},{"raw_affiliation_string":"School of Information and Communications, Gwangju Institute of Science and Technology, 123 Cheomdan-gwagiro, Buk-gu, Republic of Korea","institution_ids":["https://openalex.org/I39534123"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056743652","display_name":"Moongu Jeon","orcid":"https://orcid.org/0000-0002-2775-7789"},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Moongu Jeon","raw_affiliation_strings":["School of Information and Communications, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea","School of Information and Communications, Gwangju Institute of Science and Technology, 123 Cheomdan-gwagiro, Buk-gu, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communications, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea","institution_ids":["https://openalex.org/I39534123"]},{"raw_affiliation_string":"School of Information and Communications, Gwangju Institute of Science and Technology, 123 Cheomdan-gwagiro, Buk-gu, Republic of Korea","institution_ids":["https://openalex.org/I39534123"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I39534123"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"170","last_page":"175"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9980000257492065,"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":0.9980000257492065,"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":0.988099992275238,"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/T13717","display_name":"Advanced Algorithms and Applications","score":0.9790999889373779,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6777592301368713},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6104326248168945},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5948911905288696},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.575465202331543},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.5354148745536804},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4436042010784149},{"id":"https://openalex.org/keywords/flame-clustering","display_name":"FLAME clustering","score":0.43415507674217224},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37951067090034485},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37857598066329956},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.34652554988861084},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.2325667440891266},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.07912763953208923}],"concepts":[{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6777592301368713},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6104326248168945},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5948911905288696},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.575465202331543},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.5354148745536804},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4436042010784149},{"id":"https://openalex.org/C44859942","wikidata":"https://www.wikidata.org/wiki/Q5426511","display_name":"FLAME clustering","level":5,"score":0.43415507674217224},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37951067090034485},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37857598066329956},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.34652554988861084},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.2325667440891266},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.07912763953208923}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccais.2014.7020552","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccais.2014.7020552","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2014 International Conference on Control, Automation and Information Sciences (ICCAIS 2014)","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":29,"referenced_works":["https://openalex.org/W1570448133","https://openalex.org/W1616377031","https://openalex.org/W1793466594","https://openalex.org/W1841961408","https://openalex.org/W1888898201","https://openalex.org/W1972969203","https://openalex.org/W1979372206","https://openalex.org/W1979711990","https://openalex.org/W1987098293","https://openalex.org/W1988122146","https://openalex.org/W1992419399","https://openalex.org/W2004616416","https://openalex.org/W2108859253","https://openalex.org/W2113076747","https://openalex.org/W2120688485","https://openalex.org/W2125464731","https://openalex.org/W2125687218","https://openalex.org/W2127218421","https://openalex.org/W2127971792","https://openalex.org/W2143926826","https://openalex.org/W2148603752","https://openalex.org/W2164201421","https://openalex.org/W2164381747","https://openalex.org/W2167428023","https://openalex.org/W2171855237","https://openalex.org/W2295256067","https://openalex.org/W6636554799","https://openalex.org/W6678914141","https://openalex.org/W6681686298"],"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":{"Presented":[0],"is":[1,107,132],"a":[2,74,136],"fuzzy":[3,16,28,58,95],"clustering":[4,42,96,157],"algorithm":[5,150],"based":[6,111],"on":[7,112],"adaptive":[8],"kernel":[9,64,89],"methods.":[10],"To":[11],"utilize":[12],"benefits":[13],"of":[14,48,88,121],"combining":[15],"c-means":[17,21,29,59],"(FCM)":[18],"and":[19,35,102],"possibilistic":[20,27,57],"(PCM)":[22],"models,":[23,91],"we":[24,52],"adopt":[25],"the":[26,63,66,80,119,125,128,147],"(PFCM)":[30],"model":[31],"that":[32,108,127,146],"produces":[33],"memberships":[34],"possibilities":[36],"simultaneously":[37],"for":[38],"each":[39,140],"cluster":[40],"while":[41],"unlabeled":[43],"data.":[44],"As":[45],"an":[46,54],"extension":[47],"kernel-induced":[49,56,114],"PFCM":[50,103],"(KPFCM),":[51],"propose":[53],"improved":[55],"(IKPFCM)":[60],"algorithm.":[61],"With":[62],"methods,":[65],"input":[67],"space":[68,77],"can":[69],"be":[70],"implicitly":[71],"mapped":[72],"into":[73],"high-dimensional":[75],"feature":[76,87],"in":[78,135],"which":[79],"nonlinear":[81],"patterns":[82],"appear":[83],"linear.":[84],"The":[85,142],"main":[86],"induced":[90],"compared":[92],"to":[93],"other":[94],"models":[97],"such":[98],"as":[99],"FCM,":[100],"PCM":[101],"using":[104],"Euclidean":[105],"distance,":[106],"they":[109],"are":[110],"Gaussian":[113,129],"non-Euclidean":[115],"distance.":[116],"For":[117],"ameliorating":[118],"performance":[120,158],"KPFCM,":[122],"IKPFCM":[123,149],"uses":[124],"approach":[126],"width":[130],"parameter":[131],"selected":[133],"randomly":[134],"suitable":[137],"range":[138],"at":[139],"iteration.":[141],"experimental":[143],"results":[144],"show":[145],"proposed":[148],"achieved":[151],"significantly":[152],"better":[153],"or":[154],"sometimes":[155],"similar":[156],"than":[159],"its":[160],"competitors":[161],"considered.":[162]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
