{"id":"https://openalex.org/W2085336418","doi":"https://doi.org/10.1109/coginf.2009.5250720","title":"Rough K-medoids clustering using GAs","display_name":"Rough K-medoids clustering using GAs","publication_year":2009,"publication_date":"2009-06-01","ids":{"openalex":"https://openalex.org/W2085336418","doi":"https://doi.org/10.1109/coginf.2009.5250720","mag":"2085336418"},"language":"en","primary_location":{"id":"doi:10.1109/coginf.2009.5250720","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coginf.2009.5250720","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 8th IEEE International Conference on Cognitive Informatics","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/A5028107284","display_name":"Pawan Lingras","orcid":"https://orcid.org/0000-0002-2149-7242"},"institutions":[{"id":"https://openalex.org/I66890659","display_name":"Saint Mary's University","ror":"https://ror.org/010zh7098","country_code":"CA","type":"education","lineage":["https://openalex.org/I66890659"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Pawan Lingras","raw_affiliation_strings":["Department of Mathematics and Computing Science, Saint Mary's University, Halifax, NS, Canada","Department of Mathematics and Computing Science, Saint Mary's University, Halifax, Nova Scotia, B3H 3C3, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Computing Science, Saint Mary's University, Halifax, NS, Canada","institution_ids":["https://openalex.org/I66890659"]},{"raw_affiliation_string":"Department of Mathematics and Computing Science, Saint Mary's University, Halifax, Nova Scotia, B3H 3C3, Canada","institution_ids":["https://openalex.org/I66890659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5028107284"],"corresponding_institution_ids":["https://openalex.org/I66890659"],"apc_list":null,"apc_paid":null,"fwci":1.0283,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.77068244,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"315","last_page":"319"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9528999924659729,"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/medoid","display_name":"Medoid","score":0.8640571236610413},{"id":"https://openalex.org/keywords/rough-set","display_name":"Rough set","score":0.8186846971511841},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7310437560081482},{"id":"https://openalex.org/keywords/k-medoids","display_name":"k-medoids","score":0.5844221711158752},{"id":"https://openalex.org/keywords/variation","display_name":"Variation (astronomy)","score":0.5509456992149353},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.5003657341003418},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.46460288763046265},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.44573545455932617},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4303666353225708},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4134535789489746},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.33397039771080017},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.31875473260879517},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.30840420722961426},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2332199513912201}],"concepts":[{"id":"https://openalex.org/C63085389","wikidata":"https://www.wikidata.org/wiki/Q4287912","display_name":"Medoid","level":3,"score":0.8640571236610413},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.8186846971511841},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7310437560081482},{"id":"https://openalex.org/C65932786","wikidata":"https://www.wikidata.org/wiki/Q3191282","display_name":"k-medoids","level":5,"score":0.5844221711158752},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.5509456992149353},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.5003657341003418},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.46460288763046265},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.44573545455932617},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4303666353225708},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4134535789489746},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.33397039771080017},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.31875473260879517},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.30840420722961426},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2332199513912201},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C44870925","wikidata":"https://www.wikidata.org/wiki/Q37547","display_name":"Astrophysics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/coginf.2009.5250720","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coginf.2009.5250720","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 8th IEEE International Conference on Cognitive Informatics","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":25,"referenced_works":["https://openalex.org/W117293815","https://openalex.org/W140942106","https://openalex.org/W620925048","https://openalex.org/W1483373027","https://openalex.org/W1484320008","https://openalex.org/W1497256448","https://openalex.org/W1513494614","https://openalex.org/W1536006514","https://openalex.org/W1557923305","https://openalex.org/W1884786007","https://openalex.org/W1890412369","https://openalex.org/W1977556410","https://openalex.org/W1987149779","https://openalex.org/W2016487173","https://openalex.org/W2048404808","https://openalex.org/W2078975878","https://openalex.org/W2103535650","https://openalex.org/W2127218421","https://openalex.org/W2160396543","https://openalex.org/W2340020088","https://openalex.org/W4255833381","https://openalex.org/W6619527926","https://openalex.org/W6631964878","https://openalex.org/W6639403560","https://openalex.org/W6678914141"],"related_works":["https://openalex.org/W3133849001","https://openalex.org/W1481798977","https://openalex.org/W4225615903","https://openalex.org/W2088480663","https://openalex.org/W2386865990","https://openalex.org/W2967990367","https://openalex.org/W2362763349","https://openalex.org/W2389804866","https://openalex.org/W2552289628","https://openalex.org/W4388720854"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,18,37,46,73,109,123],"medoid":[4,92],"based":[5,93],"variation":[6,12,94],"of":[7,23,40,81,89,126],"rough":[8,24,29,50,61,66,74,82,103],"k-means":[9,30,51,67,83,104],"algorithm.":[10],"The":[11,76,91],"can":[13],"be":[14],"especially":[15],"useful":[16],"for":[17,45],"more":[19,98],"efficient":[20,99],"evolutionary":[21,65,102],"implementation":[22],"clustering.":[25,62],"Experimentation":[26],"with":[27,85],"the":[28,79,86,101,135],"algorithm":[31,52,68,84],"has":[32,53],"shown":[33,57],"that":[34,71],"it":[35,107,119],"provides":[36],"reasonable":[38],"set":[39],"lower":[41],"and":[42,111],"upper":[43],"bounds":[44],"given":[47],"dataset.":[48],"However,":[49],"not":[54],"been":[55],"explicitly":[56],"to":[58,121,130],"provide":[59],"optimal":[60],"Recently,":[63],"an":[64],"was":[69],"proposed":[70,95],"minimizes":[72],"within-group-error.":[75],"proposal":[77],"combined":[78],"efficiency":[80],"optimization":[87,127],"ability":[88],"GAs.":[90],"here":[96],"is":[97],"than":[100],"algorithm,":[105],"as":[106],"uses":[108],"smaller":[110],"discrete":[112],"search":[113],"space.":[114,137],"It":[115],"will":[116],"also":[117],"make":[118],"possible":[120],"test":[122],"wider":[124],"variety":[125],"criteria":[128],"due":[129],"built":[131],"in":[132],"restrictions":[133],"on":[134],"solution":[136]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}