{"id":"https://openalex.org/W4241015129","doi":"https://doi.org/10.1080/18756891.2011.9727760","title":"Experimental Comparison of Iterative Versus Evolutionary Crisp and Rough Clustering","display_name":"Experimental Comparison of Iterative Versus Evolutionary Crisp and Rough Clustering","publication_year":2011,"publication_date":"2011-02-01","ids":{"openalex":"https://openalex.org/W4241015129","doi":"https://doi.org/10.1080/18756891.2011.9727760"},"language":"en","primary_location":{"id":"doi:10.1080/18756891.2011.9727760","is_oa":true,"landing_page_url":"https://doi.org/10.1080/18756891.2011.9727760","pdf_url":null,"source":{"id":"https://openalex.org/S190680769","display_name":"International Journal of Computational Intelligence Systems","issn_l":"1875-6883","issn":["1875-6883","1875-6891"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computational Intelligence Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1080/18756891.2011.9727760","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":false,"raw_author_name":"Pawan Lingras","raw_affiliation_strings":["Department of Mathematics and Computing Science , Saint Mary's University , Halifax , Nova Scotia , B3H 3C3 , Canada E-mail: pawan@cs.smu.ca","Department of Mathematics and Computing Science, Saint Mary's University, Halifax, Nova Scotia, B3H 3C3, Canada E-mail: pawan@cs.smu.ca"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Computing Science , Saint Mary's University , Halifax , Nova Scotia , B3H 3C3 , Canada E-mail: pawan@cs.smu.ca","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 E-mail: pawan@cs.smu.ca","institution_ids":["https://openalex.org/I66890659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008884152","display_name":"Manish Joshi","orcid":"https://orcid.org/0000-0001-8783-8567"},"institutions":[{"id":"https://openalex.org/I157117621","display_name":"Kavayitri Bahinabai Chaudhari North Maharashtra University","ror":"https://ror.org/04g7tnd56","country_code":"IN","type":"education","lineage":["https://openalex.org/I157117621"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Manish Joshi","raw_affiliation_strings":["Department of Computer Science , North Maharashtra University , Jalgaon , Maharashtra , 425 001 , India E-mail: joshmanish@gmail.com","Department of Computer Science, North Maharashtra University, Jalgaon, Maharashtra, 425 001, India E-mail: joshmanish@gmail.com"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science , North Maharashtra University , Jalgaon , Maharashtra , 425 001 , India E-mail: joshmanish@gmail.com","institution_ids":["https://openalex.org/I157117621"]},{"raw_affiliation_string":"Department of Computer Science, North Maharashtra University, Jalgaon, Maharashtra, 425 001, India E-mail: joshmanish@gmail.com","institution_ids":["https://openalex.org/I157117621"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2090,"currency":"USD","value_usd":2090},"apc_paid":{"value":2090,"currency":"USD","value_usd":2090},"fwci":2.3097,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.93719903,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"4","issue":"1","first_page":"12","last_page":"28"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9991000294685364,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9990000128746033,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9966999888420105,"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/cluster-analysis","display_name":"Cluster analysis","score":0.7544896602630615},{"id":"https://openalex.org/keywords/medoid","display_name":"Medoid","score":0.7485376000404358},{"id":"https://openalex.org/keywords/rough-set","display_name":"Rough set","score":0.7392741441726685},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6229036450386047},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5992600321769714},{"id":"https://openalex.org/keywords/self-organizing-map","display_name":"Self-organizing map","score":0.5783697962760925},{"id":"https://openalex.org/keywords/k-medoids","display_name":"k-medoids","score":0.5355584025382996},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4532824158668518},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.44153356552124023},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3928535282611847},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.3902071416378021},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.37783095240592957},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3460838198661804},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3327731490135193},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2901683747768402},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.19417300820350647}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7544896602630615},{"id":"https://openalex.org/C63085389","wikidata":"https://www.wikidata.org/wiki/Q4287912","display_name":"Medoid","level":3,"score":0.7485376000404358},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.7392741441726685},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6229036450386047},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5992600321769714},{"id":"https://openalex.org/C111168008","wikidata":"https://www.wikidata.org/wiki/Q1136838","display_name":"Self-organizing map","level":3,"score":0.5783697962760925},{"id":"https://openalex.org/C65932786","wikidata":"https://www.wikidata.org/wiki/Q3191282","display_name":"k-medoids","level":5,"score":0.5355584025382996},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4532824158668518},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.44153356552124023},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3928535282611847},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.3902071416378021},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.37783095240592957},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3460838198661804},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3327731490135193},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2901683747768402},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.19417300820350647},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/18756891.2011.9727760","is_oa":true,"landing_page_url":"https://doi.org/10.1080/18756891.2011.9727760","pdf_url":null,"source":{"id":"https://openalex.org/S190680769","display_name":"International Journal of Computational Intelligence Systems","issn_l":"1875-6883","issn":["1875-6883","1875-6891"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computational Intelligence Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1080/18756891.2011.9727760","is_oa":true,"landing_page_url":"https://doi.org/10.1080/18756891.2011.9727760","pdf_url":null,"source":{"id":"https://openalex.org/S190680769","display_name":"International Journal of Computational Intelligence Systems","issn_l":"1875-6883","issn":["1875-6883","1875-6891"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computational Intelligence Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W90286923","https://openalex.org/W117293815","https://openalex.org/W140942106","https://openalex.org/W1483373027","https://openalex.org/W1513494614","https://openalex.org/W1601489891","https://openalex.org/W1977556410","https://openalex.org/W1987149779","https://openalex.org/W1998778961","https://openalex.org/W2048404808","https://openalex.org/W2059354646","https://openalex.org/W2071965987","https://openalex.org/W2095561225","https://openalex.org/W2099189653","https://openalex.org/W2103535650","https://openalex.org/W2115602682","https://openalex.org/W2127821541","https://openalex.org/W2299467264","https://openalex.org/W4237251553","https://openalex.org/W4298052423"],"related_works":["https://openalex.org/W3133849001","https://openalex.org/W1481798977","https://openalex.org/W2380053301","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"],"abstract_inverted_index":{"Researchers":[0],"have":[1,29],"proposed":[2],"several":[3],"Genetic":[4,15],"Algorithm":[5],"(GA)":[6],"based":[7,13],"crisp":[8],"clustering":[9,12,35],"algorithms.":[10,84],"Rough":[11],"on":[14],"Algorithms,":[16],"Kohonen":[17],"Self-Organizing":[18],"Maps,":[19],"K-means":[20,39,79],"algorithm":[21],"are":[22],"also":[23],"reported":[24],"in":[25,60],"literature.":[26],"Recently,":[27],"researchers":[28],"combined":[30],"GAs":[31,44],"with":[32,87],"iterative":[33],"rough":[34,75,78,82],"algorithms":[36],"such":[37],"as":[38,113],"and":[40,80,97,109],"K-Medoids.":[41],"Use":[42],"of":[43,52],"makes":[45],"it":[46,57],"possible":[47],"to":[48],"specify":[49],"explicit":[50],"optimization":[51],"cluster":[53,105],"validity":[54],"measures.":[55],"However,":[56],"can":[58],"result":[59],"additional":[61],"computing":[62],"time.":[63],"In":[64],"this":[65],"paper":[66],"we":[67],"compare":[68],"results":[69],"obtained":[70],"using":[71,101],"K-means,":[72,74,76],"GA":[73,77,81],"K-medoid":[83],"We":[85],"experimented":[86],"a":[88,92,98,102],"synthetic":[89],"data":[90,95],"set,":[91,96],"real":[93],"world":[94],"standard":[99],"dataset":[100],"total":[103],"within":[104],"variation,":[106],"average":[107],"precision,":[108],"execution":[110],"time":[111],"required":[112],"the":[114],"criteria":[115],"for":[116],"comparison.":[117]},"counts_by_year":[{"year":2014,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}