{"id":"https://openalex.org/W2109808610","doi":"https://doi.org/10.1109/fuzzy.2005.1452371","title":"Relational Gustafson Kessel Clustering Using Medoids and Triangulation","display_name":"Relational Gustafson Kessel Clustering Using Medoids and Triangulation","publication_year":2005,"publication_date":"2005-07-27","ids":{"openalex":"https://openalex.org/W2109808610","doi":"https://doi.org/10.1109/fuzzy.2005.1452371","mag":"2109808610"},"language":"en","primary_location":{"id":"doi:10.1109/fuzzy.2005.1452371","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzzy.2005.1452371","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 14th IEEE International Conference on Fuzzy Systems, 2005. FUZZ '05.","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/A5002518694","display_name":"Thomas A. Runkler","orcid":"https://orcid.org/0000-0002-5465-198X"},"institutions":[{"id":"https://openalex.org/I1325886976","display_name":"Siemens (Germany)","ror":"https://ror.org/059mq0909","country_code":"DE","type":"company","lineage":["https://openalex.org/I1325886976"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"T.A. Runkler","raw_affiliation_strings":["Neural Computation Department, Information and Communications, Siemens AG, Munich, Germany","Dept. of Neural Comput., Siemens AG, Munich"],"affiliations":[{"raw_affiliation_string":"Neural Computation Department, Information and Communications, Siemens AG, Munich, Germany","institution_ids":["https://openalex.org/I1325886976"]},{"raw_affiliation_string":"Dept. of Neural Comput., Siemens AG, Munich","institution_ids":["https://openalex.org/I1325886976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5002518694"],"corresponding_institution_ids":["https://openalex.org/I1325886976"],"apc_list":null,"apc_paid":null,"fwci":0.8775,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.80816015,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"73","last_page":"78"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9900000095367432,"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":0.9900000095367432,"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":0.9854000210762024,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9819999933242798,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/cluster-analysis","display_name":"Cluster analysis","score":0.6766319870948792},{"id":"https://openalex.org/keywords/relational-database","display_name":"Relational database","score":0.608426570892334},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.5955612063407898},{"id":"https://openalex.org/keywords/triangulation","display_name":"Triangulation","score":0.5234068036079407},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47910192608833313},{"id":"https://openalex.org/keywords/k-medoids","display_name":"k-medoids","score":0.46671029925346375},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4379279613494873},{"id":"https://openalex.org/keywords/flame-clustering","display_name":"FLAME clustering","score":0.4228174090385437},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41190487146377563},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.4112960696220398},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4040473997592926},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3455778956413269},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.19953349232673645},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.06440550088882446}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6766319870948792},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.608426570892334},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.5955612063407898},{"id":"https://openalex.org/C135981907","wikidata":"https://www.wikidata.org/wiki/Q188056","display_name":"Triangulation","level":2,"score":0.5234068036079407},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47910192608833313},{"id":"https://openalex.org/C65932786","wikidata":"https://www.wikidata.org/wiki/Q3191282","display_name":"k-medoids","level":5,"score":0.46671029925346375},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4379279613494873},{"id":"https://openalex.org/C44859942","wikidata":"https://www.wikidata.org/wiki/Q5426511","display_name":"FLAME clustering","level":5,"score":0.4228174090385437},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41190487146377563},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.4112960696220398},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4040473997592926},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3455778956413269},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.19953349232673645},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.06440550088882446}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fuzzy.2005.1452371","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzzy.2005.1452371","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 14th IEEE International Conference on Fuzzy Systems, 2005. FUZZ '05.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1982249777","https://openalex.org/W2061708588","https://openalex.org/W2090582154","https://openalex.org/W2091341295","https://openalex.org/W2095973690","https://openalex.org/W2099836385","https://openalex.org/W2113076747","https://openalex.org/W2119411328","https://openalex.org/W2125078521","https://openalex.org/W2134312057","https://openalex.org/W2136753665","https://openalex.org/W2171223863"],"related_works":["https://openalex.org/W3129335559","https://openalex.org/W2157383128","https://openalex.org/W2399084168","https://openalex.org/W4292964559","https://openalex.org/W2363077075","https://openalex.org/W3087769312","https://openalex.org/W2747006034","https://openalex.org/W2609785842","https://openalex.org/W1513651805","https://openalex.org/W4388658494"],"abstract_inverted_index":{"This":[0],"paper":[1],"deals":[2],"with":[3,17],"clustering":[4,22],"relational":[5,21,26,30,40,66,92],"data":[6,16,93],"that":[7],"can":[8],"be":[9],"(at":[10],"least":[11],"approximately)":[12],"represented":[13],"by":[14],"object":[15],"ellipsoidal":[18],"clusters.":[19],"Conventional":[20],"models":[23],"such":[24],"as":[25],"fuzzy":[27,31],"c-means":[28],"or":[29],"c-medoids":[32],"produce":[33],"bad":[34],"results":[35,87],"for":[36,88],"this":[37,51],"family":[38,90],"of":[39,91],"data,":[41,67],"because":[42],"they":[43],"do":[44],"not":[45],"consider":[46],"the":[47,60,68,72,89],"cluster":[48,61],"shape.":[49],"In":[50],"paper,":[52],"we":[53],"develop":[54],"a":[55],"Gustafson":[56],"Kessel":[57],"model":[58],"where":[59],"centers":[62],"are":[63,75],"medoids.":[64],"For":[65],"scatter":[69],"matrices":[70],"and":[71],"matrix":[73],"distances":[74],"locally":[76],"computed":[77],"using":[78],"triangulation.":[79],"The":[80],"resulting":[81],"RGKMdd":[82],"algorithm":[83],"produces":[84],"very":[85],"good":[86],"specified":[94],"above":[95]},"counts_by_year":[{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}