{"id":"https://openalex.org/W2604925222","doi":"https://doi.org/10.1145/3033288.3033347","title":"Two Step Clustering Model for K-Means Algorithm","display_name":"Two Step Clustering Model for K-Means Algorithm","publication_year":2016,"publication_date":"2016-12-17","ids":{"openalex":"https://openalex.org/W2604925222","doi":"https://doi.org/10.1145/3033288.3033347","mag":"2604925222"},"language":"en","primary_location":{"id":"doi:10.1145/3033288.3033347","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3033288.3033347","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fifth International Conference on Network, 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/A5033320509","display_name":"Narongsak Chayangkoon","orcid":null},"institutions":[{"id":"https://openalex.org/I198105771","display_name":"Kasetsart University","ror":"https://ror.org/05gzceg21","country_code":"TH","type":"education","lineage":["https://openalex.org/I198105771"]}],"countries":["TH"],"is_corresponding":true,"raw_author_name":"Narongsak Chayangkoon","raw_affiliation_strings":["Department of Computer Science, Kasetsart University, Bangkok, Thailand"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Kasetsart University, Bangkok, Thailand","institution_ids":["https://openalex.org/I198105771"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046925206","display_name":"Anongnart Srivihok","orcid":"https://orcid.org/0000-0003-3795-8426"},"institutions":[{"id":"https://openalex.org/I198105771","display_name":"Kasetsart University","ror":"https://ror.org/05gzceg21","country_code":"TH","type":"education","lineage":["https://openalex.org/I198105771"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Anongnart Srivihok","raw_affiliation_strings":["Department of Computer Science, Kasetsart University, Bangkok, Thailand"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Kasetsart University, Bangkok, Thailand","institution_ids":["https://openalex.org/I198105771"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5033320509"],"corresponding_institution_ids":["https://openalex.org/I198105771"],"apc_list":null,"apc_paid":null,"fwci":0.4285,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.81142844,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"213","last_page":"217"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9980999827384949,"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":0.9980999827384949,"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/T10057","display_name":"Face and Expression Recognition","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9908999800682068,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7877008318901062},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6560723185539246},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6257376670837402},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6021486520767212},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4904060363769531},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.48301467299461365},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.44525039196014404},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.43706780672073364},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4132179021835327},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39023980498313904},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.11783069372177124}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7877008318901062},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6560723185539246},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6257376670837402},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6021486520767212},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4904060363769531},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48301467299461365},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.44525039196014404},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.43706780672073364},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4132179021835327},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39023980498313904},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.11783069372177124}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3033288.3033347","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3033288.3033347","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fifth International Conference on Network, 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":25,"referenced_works":["https://openalex.org/W1482678562","https://openalex.org/W1580679247","https://openalex.org/W1665908496","https://openalex.org/W1920010643","https://openalex.org/W1970820654","https://openalex.org/W1989270503","https://openalex.org/W1992419399","https://openalex.org/W2004480295","https://openalex.org/W2017337590","https://openalex.org/W2036216970","https://openalex.org/W2049633694","https://openalex.org/W2085487226","https://openalex.org/W2099242680","https://openalex.org/W2102753129","https://openalex.org/W2102831150","https://openalex.org/W2103868202","https://openalex.org/W2127218421","https://openalex.org/W2136023023","https://openalex.org/W2155925556","https://openalex.org/W2165964124","https://openalex.org/W2170493694","https://openalex.org/W2188565066","https://openalex.org/W2299467264","https://openalex.org/W4255264342","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W1975632186","https://openalex.org/W3027745756","https://openalex.org/W3205213561","https://openalex.org/W2531880140","https://openalex.org/W2126145365","https://openalex.org/W2036609560","https://openalex.org/W346861917","https://openalex.org/W3024018414","https://openalex.org/W1542592062","https://openalex.org/W4380081032"],"abstract_inverted_index":{"In":[0,48,60,72],"this":[1,49],"paper,":[2],"we":[3,51,63,77,131,146,152,160,173],"propose":[4],"Two":[5],"Step":[6],"Clustering":[7],"Model":[8,20,171,188,224,237],"for":[9,15,28,42,74,138,149,157,203],"finding":[10,139,204],"the":[11,22,29,37,40,53,61,119,124,133,140,144,150,158,169,175,180,193,205,210,221,231,239],"number":[12,38,206],"of":[13,24,39,118,135,168,182,207,242],"clusters":[14,41,208],"K-Means":[16,25,46],"Algorithm.":[17,47],"The":[18,81,93,101,116],"Hybrid":[19,58,170,187,223,236],"solves":[21],"weakness":[23],"Algorithm":[26],"especially":[27],"general":[30],"users":[31],"who":[32],"will":[33],"try":[34],"to":[35],"find":[36],"cluster":[43,211],"analysis":[44,212],"by":[45,55,178],"research,":[50],"solve":[52],"problem":[54],"proposing":[56],"a":[57,227],"Model.":[59],"experiment,":[62],"used":[64,78,83,95,103,112,147,153,161,191],"10":[65],"datasets":[66],"from":[67],"UCI":[68],"machine":[69],"learning":[70],"repository.":[71],"addition,":[73],"feature":[75,128],"selection":[76],"three":[79,136],"algorithms.":[80],"first":[82,145],"Best":[84,104],"First":[85,105],"Search":[86,106],"and":[87,97,107,127,156,172,209],"Correction":[88],"--Based":[89],"Feature":[90],"Subset":[91,109],"Selection.":[92],"second":[94],"Ranker":[96],"Principal":[98,196],"Component":[99,197],"Analysis.":[100,198],"third":[102],"Wrapper":[108],"Evaluator,":[110],"classification":[111],"Na\u00efve":[113],"Bayes":[114],"Classifier.":[115],"determinants":[117],"baseline":[120],"model":[121],"didn't":[122],"use":[123],"searching":[125,190],"method":[126],"selection.":[129],"Moreover,":[130],"compared":[132,174],"performance":[134,166,229],"algorithms":[137,232],"k":[141],"value.":[142],"For":[143,199],"EM,":[148],"second,":[151],"Cascade":[154],"K-Means,":[155],"third,":[159],"Canopy.":[162],"We":[163],"also":[164],"evaluated":[165],"testing":[167],"criterion":[176],"clustering":[177],"using":[179],"Sum":[181,241],"Squared":[183,243],"Errors.":[184,244],"Thus,":[185],"our":[186,217,235],"includes":[189],"Ranker,":[192],"evaluator":[194],"uses":[195,213],"clustering,":[200],"Expectation":[201],"Maximization":[202],"simple":[214],"K-mean.":[215],"Furthermore,":[216],"experimental":[218],"results":[219],"showed":[220],"best":[222],"approach":[225],"achieves":[226],"higher":[228],"that":[230],"available":[233],"in":[234],"had":[238],"lowest":[240]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}