{"id":"https://openalex.org/W3161085427","doi":"https://doi.org/10.1145/3447654.3447657","title":"The Systematic Review of K-Means Clustering Algorithm","display_name":"The Systematic Review of K-Means Clustering Algorithm","publication_year":2020,"publication_date":"2020-12-18","ids":{"openalex":"https://openalex.org/W3161085427","doi":"https://doi.org/10.1145/3447654.3447657","mag":"3161085427"},"language":"en","primary_location":{"id":"doi:10.1145/3447654.3447657","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447654.3447657","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 The 9th International Conference on Networks, Communication and Computing","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/A5012181761","display_name":"Ardavan Ashabi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210147344","display_name":"Malaysia University of Science and Technology","ror":"https://ror.org/04frcff47","country_code":"MY","type":"education","lineage":["https://openalex.org/I4210147344"]},{"id":"https://openalex.org/I4576418","display_name":"University of Technology Malaysia","ror":"https://ror.org/026w31v75","country_code":"MY","type":"education","lineage":["https://openalex.org/I4576418"]}],"countries":["MY"],"is_corresponding":true,"raw_author_name":"Ardavan Ashabi","raw_affiliation_strings":["University of Technology Malaysia, MALAYSIA"],"affiliations":[{"raw_affiliation_string":"University of Technology Malaysia, MALAYSIA","institution_ids":["https://openalex.org/I4210147344","https://openalex.org/I4576418"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053297300","display_name":"Shamsul Sahibuddin","orcid":null},"institutions":[{"id":"https://openalex.org/I4576418","display_name":"University of Technology Malaysia","ror":"https://ror.org/026w31v75","country_code":"MY","type":"education","lineage":["https://openalex.org/I4576418"]},{"id":"https://openalex.org/I207206903","display_name":"Universiti Tun Abdul Razak","ror":"https://ror.org/01m91v580","country_code":"MY","type":"education","lineage":["https://openalex.org/I207206903"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Shamsul Bin Sahibuddin","raw_affiliation_strings":["Razak Faculty of Technology and Informatics University of Technology Malaysia Kuala Lumpur MALAYSIA, Malaysia"],"affiliations":[{"raw_affiliation_string":"Razak Faculty of Technology and Informatics University of Technology Malaysia Kuala Lumpur MALAYSIA, Malaysia","institution_ids":["https://openalex.org/I207206903","https://openalex.org/I4576418"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077391518","display_name":"Mehdi Salkhordeh Haghighi","orcid":"https://orcid.org/0000-0001-8435-9253"},"institutions":[{"id":"https://openalex.org/I3132928613","display_name":"Sadjad University of Technology","ror":"https://ror.org/04b9hej41","country_code":"IR","type":"education","lineage":["https://openalex.org/I3132928613"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mehdi Salkhordeh Haghighi","raw_affiliation_strings":["Faculty of Computer Engineering Sadjad University of Technology Mashhad IRAN, Iran"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer Engineering Sadjad University of Technology Mashhad IRAN, Iran","institution_ids":["https://openalex.org/I3132928613"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5012181761"],"corresponding_institution_ids":["https://openalex.org/I4210147344","https://openalex.org/I4576418"],"apc_list":null,"apc_paid":null,"fwci":2.4469,"has_fulltext":false,"cited_by_count":48,"citation_normalized_percentile":{"value":0.91475935,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"13","last_page":"18"},"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9897000193595886,"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/T12384","display_name":"Customer churn and segmentation","score":0.9697999954223633,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.9113527536392212},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7602974772453308},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.7076288461685181},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.537905752658844},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.47939085960388184},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.4586508274078369},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.4327225089073181},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.4033205807209015},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.36006593704223633},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.331359326839447},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2770657539367676}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.9113527536392212},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7602974772453308},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.7076288461685181},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.537905752658844},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.47939085960388184},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.4586508274078369},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.4327225089073181},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.4033205807209015},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.36006593704223633},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.331359326839447},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2770657539367676}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3447654.3447657","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447654.3447657","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 The 9th International Conference on Networks, Communication and Computing","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":32,"referenced_works":["https://openalex.org/W1483598450","https://openalex.org/W2094025768","https://openalex.org/W2127218421","https://openalex.org/W2181223040","https://openalex.org/W2356195073","https://openalex.org/W2520303620","https://openalex.org/W2544075565","https://openalex.org/W2586376538","https://openalex.org/W2742371826","https://openalex.org/W2753555091","https://openalex.org/W2770487168","https://openalex.org/W2770718574","https://openalex.org/W2777310340","https://openalex.org/W2789511664","https://openalex.org/W2811454289","https://openalex.org/W2891639990","https://openalex.org/W2911815211","https://openalex.org/W2943533080","https://openalex.org/W2954403177","https://openalex.org/W2960962270","https://openalex.org/W2964330706","https://openalex.org/W2966065262","https://openalex.org/W2971225814","https://openalex.org/W2995246767","https://openalex.org/W2998652752","https://openalex.org/W3000051746","https://openalex.org/W3034077436","https://openalex.org/W3037721581","https://openalex.org/W3048809473","https://openalex.org/W3080538929","https://openalex.org/W6603190838","https://openalex.org/W6727418292"],"related_works":["https://openalex.org/W4301002638","https://openalex.org/W2371010743","https://openalex.org/W2163563073","https://openalex.org/W3088133960","https://openalex.org/W1987613674","https://openalex.org/W3186815950","https://openalex.org/W4253632195","https://openalex.org/W2393707058","https://openalex.org/W2590117803","https://openalex.org/W3124860551"],"abstract_inverted_index":{"Recently,":[0],"the":[1,6,21,33,51,65,69,95,123,127,148,153],"world":[2],"is":[3,39,45,74,84,101],"experiencing":[4],"generating":[5],"huge":[7],"amount":[8],"of":[9,32,43,68,130,139,156],"data":[10,26,35,44,46],"in":[11,105],"different":[12,128],"domains.":[13,107],"Data":[14,17,48],"mining":[15,36],"and":[16,19,27,89,121,142],"analytics":[18],"are":[20,59,159],"practices":[22],"used":[23,40,62,75,104],"for":[24,76,78,165],"analyzing":[25],"extracting":[28],"hidden":[29],"knowledge.":[30],"One":[31,67],"major":[34],"methods":[37],"which":[38,73,100],"to":[41,63,111,118,147,161],"analysis":[42],"clustering.":[47,66],"clustering":[49,77,98,132],"ease":[50],"extract":[52],"information":[53],"from":[54],"each":[55],"cluster":[56],"separately.":[57],"There":[58],"many":[60,87],"algorithms":[61,72],"perform":[64],"most":[70,96],"famous":[71],"more":[79],"than":[80],"half":[81],"a":[82,113,137,163],"century":[83],"k-means.":[85],"By":[86,150],"optimization":[88],"enhancement,":[90],"K-means":[91],"still":[92,102],"considers":[93],"as":[94],"popular":[97],"algorithm":[99],"being":[103],"various":[106],"This":[108,134],"research":[109],"attempts":[110],"conduct":[112],"Systematic":[114],"literature":[115],"Review":[116],"(SLR)":[117],"collect,":[119],"classify,":[120],"analyze":[122],"primary":[124],"studies":[125],"about":[126],"version":[129],"k-means":[131],"algorithm.":[133],"SLR":[135],"gives":[136],"means":[138],"finding,":[140],"appraising,":[141],"interpreting":[143],"existing":[144],"researches":[145],"pertinent":[146],"topic.":[149],"narrowing":[151],"down":[152],"crucial":[154],"sections":[155],"debate,":[157],"we":[158],"hoping":[160],"establish":[162],"foundation":[164],"upcoming":[166],"researches.":[167]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":12}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
