{"id":"https://openalex.org/W2980135714","doi":"https://doi.org/10.1109/fuzz-ieee.2019.8858849","title":"Quantification and Visualization for Difference of Fuzzy Clustering Results","display_name":"Quantification and Visualization for Difference of Fuzzy Clustering Results","publication_year":2019,"publication_date":"2019-06-01","ids":{"openalex":"https://openalex.org/W2980135714","doi":"https://doi.org/10.1109/fuzz-ieee.2019.8858849","mag":"2980135714"},"language":"en","primary_location":{"id":"doi:10.1109/fuzz-ieee.2019.8858849","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2019.8858849","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","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/A5046294812","display_name":"Mika Sato\u2010Ilic","orcid":"https://orcid.org/0000-0003-1266-1853"},"institutions":[{"id":"https://openalex.org/I146399215","display_name":"University of Tsukuba","ror":"https://ror.org/02956yf07","country_code":"JP","type":"education","lineage":["https://openalex.org/I146399215"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Mika Sato-Ilic","raw_affiliation_strings":["Faculty of Engineering, Information and Systems University of Tsukuba, Tsukuba, Japan"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, Information and Systems University of Tsukuba, Tsukuba, Japan","institution_ids":["https://openalex.org/I146399215"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5046294812"],"corresponding_institution_ids":["https://openalex.org/I146399215"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.12376807,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"2019","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9976999759674072,"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":0.9976999759674072,"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/T11106","display_name":"Data Management and Algorithms","score":0.9822999835014343,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10050","display_name":"Multi-Criteria Decision Making","score":0.9711999893188477,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.823259711265564},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.6762696504592896},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6626745462417603},{"id":"https://openalex.org/keywords/comparability","display_name":"Comparability","score":0.6557531356811523},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5609956979751587},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5581513047218323},{"id":"https://openalex.org/keywords/flame-clustering","display_name":"FLAME clustering","score":0.45669275522232056},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.4392070174217224},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4347511827945709},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42191603779792786},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.35450947284698486},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33839136362075806}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.823259711265564},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.6762696504592896},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6626745462417603},{"id":"https://openalex.org/C197947376","wikidata":"https://www.wikidata.org/wiki/Q5155608","display_name":"Comparability","level":2,"score":0.6557531356811523},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5609956979751587},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5581513047218323},{"id":"https://openalex.org/C44859942","wikidata":"https://www.wikidata.org/wiki/Q5426511","display_name":"FLAME clustering","level":5,"score":0.45669275522232056},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.4392070174217224},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4347511827945709},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42191603779792786},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.35450947284698486},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33839136362075806},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/fuzz-ieee.2019.8858849","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2019.8858849","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","raw_type":"proceedings-article"},{"id":"mag:3087361375","is_oa":false,"landing_page_url":"https://jglobal.jst.go.jp/en/detail?JGLOBAL_ID=201902239054801033","pdf_url":null,"source":{"id":"https://openalex.org/S4306512817","display_name":"IEEE Conference Proceedings","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":null,"is_accepted":false,"is_published":null,"raw_source_name":"IEEE Conference Proceedings","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.47999998927116394}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1507216665","https://openalex.org/W1535837486","https://openalex.org/W1969043006","https://openalex.org/W1999597013","https://openalex.org/W2055576996","https://openalex.org/W2061681393","https://openalex.org/W2088784163","https://openalex.org/W2113076747","https://openalex.org/W2133467637","https://openalex.org/W2612765195","https://openalex.org/W2763635920","https://openalex.org/W2795998755","https://openalex.org/W4246354968","https://openalex.org/W6632043775","https://openalex.org/W6664635345"],"related_works":["https://openalex.org/W2182561586","https://openalex.org/W2884893917","https://openalex.org/W2027443997","https://openalex.org/W2129417512","https://openalex.org/W2364555098","https://openalex.org/W2608738689","https://openalex.org/W2125631209","https://openalex.org/W3129335559","https://openalex.org/W2012262742","https://openalex.org/W2359500286"],"abstract_inverted_index":{"This":[0],"paper":[1,153],"proposes":[2],"a":[3,82,106,111],"method":[4,150],"to":[5,15,37,84,135,174],"obtain":[6,52,121],"the":[7,23,31,41,63,86,122,137,140,144,155,158,162,166,170,181,187,200],"quantitative":[8],"difference":[9,138,159,182],"of":[10,25,33,35,69,100,114,139,157,165,183,199],"fuzzy":[11,26],"clustering":[12,27,123,141,184],"results":[13,54,142,185],"and":[14,102,104,118,179],"visualize":[16,180],"it":[17],"in":[18,95,151],"lower":[19],"dimensional":[20],"space.":[21],"Since":[22],"result":[24,124],"is":[28,81,108],"shown":[29,194],"as":[30],"degree":[32],"belongingness":[34],"objects":[36,101],"exploratory":[38],"obtained":[39,42,67,167],"clusters,":[40],"clusters":[43,70,168],"do":[44],"not":[45],"have":[46],"\"explicit":[47],"order\".":[48],"Therefore,":[49],"if":[50,90,119],"we":[51,60,91,120,131],"multiple":[53,56,93,112],"from":[55,76],"datasets":[57,94,172],"individually,":[58],"then":[59,130],"cannot":[61],"compare":[62,85],"results,":[64],"since":[65],"each":[66,72,77,97,126],"\"order\"":[68],"for":[71,110,195],"dataset":[73,98,107],"may":[74],"differ":[75],"other.":[78],"However,":[79],"there":[80],"need":[83],"results.":[87],"For":[88],"example,":[89],"observe":[92],"which":[96],"consists":[99],"variables":[103],"such":[105],"observed":[109],"number":[113],"subjects":[115,145,176,188],"(or":[116,128,146,177,189],"times),":[117],"at":[125],"subject":[127],"time),":[129],"usually":[132],"would":[133],"like":[134],"know":[136],"over":[143,169,186],"times).":[147,190],"The":[148],"proposed":[149,201],"this":[152],"enables":[154],"capturing":[156],"based":[160],"on":[161],"mathematical":[163],"comparability":[164],"different":[171,175],"corresponding":[173],"times)":[178],"Numerical":[191],"examples":[192],"are":[193],"an":[196],"improved":[197],"understanding":[198],"method.":[202]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}