{"id":"https://openalex.org/W2015455656","doi":"https://doi.org/10.1142/s0218001412500188","title":"DETERMINISTIC INITIALIZATION OF THE K-MEANS ALGORITHM USING HIERARCHICAL CLUSTERING","display_name":"DETERMINISTIC INITIALIZATION OF THE K-MEANS ALGORITHM USING HIERARCHICAL CLUSTERING","publication_year":2012,"publication_date":"2012-11-01","ids":{"openalex":"https://openalex.org/W2015455656","doi":"https://doi.org/10.1142/s0218001412500188","mag":"2015455656"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001412500188","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001412500188","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1304.7465","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"M. EMRE CELEBI","orcid":null},"institutions":[{"id":"https://openalex.org/I26489229","display_name":"Louisiana State University in Shreveport","ror":"https://ror.org/02c4cbt39","country_code":"US","type":"education","lineage":["https://openalex.org/I26489229"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"M. EMRE CELEBI","raw_affiliation_strings":["Department of Computer Science, Louisiana State University, Shreveport, LA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Louisiana State University, Shreveport, LA, USA","institution_ids":["https://openalex.org/I26489229"]}]},{"author_position":"last","author":{"id":null,"display_name":"HASSAN A. KINGRAVI","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"HASSAN A. KINGRAVI","raw_affiliation_strings":["School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I26489229"],"apc_list":null,"apc_paid":null,"fwci":5.3372,"has_fulltext":false,"cited_by_count":51,"citation_normalized_percentile":{"value":0.95408868,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"26","issue":"07","first_page":"1250018","last_page":"1250018"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9125000238418579,"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":0.9125000238418579,"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":0.026599999517202377,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.019600000232458115,"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/initialization","display_name":"Initialization","score":0.9028000235557556},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6780999898910522},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.5231999754905701},{"id":"https://openalex.org/keywords/hierarchical-clustering","display_name":"Hierarchical clustering","score":0.5177000164985657},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41609999537467957},{"id":"https://openalex.org/keywords/hierarchical-clustering-of-networks","display_name":"Hierarchical clustering of networks","score":0.40230000019073486},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.3334999978542328}],"concepts":[{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.9028000235557556},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6895999908447266},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6780999898910522},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.5231999754905701},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.5177000164985657},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.47760000824928284},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45739999413490295},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41609999537467957},{"id":"https://openalex.org/C82261393","wikidata":"https://www.wikidata.org/wiki/Q17038699","display_name":"Hierarchical clustering of networks","level":5,"score":0.40230000019073486},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.374099999666214},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.3334999978542328},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.3215999901294708},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.3124000132083893},{"id":"https://openalex.org/C22648726","wikidata":"https://www.wikidata.org/wiki/Q7523744","display_name":"Single-linkage clustering","level":5,"score":0.2948000133037567},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.28999999165534973},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2833000123500824},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.27730000019073486},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.2689000070095062},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.25780001282691956},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.25609999895095825}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1142/s0218001412500188","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001412500188","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1304.7465","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1304.7465","pdf_url":"https://arxiv.org/pdf/1304.7465","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1304.7465","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1304.7465","pdf_url":"https://arxiv.org/pdf/1304.7465","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W142275858","https://openalex.org/W1493454437","https://openalex.org/W1640718925","https://openalex.org/W1970800786","https://openalex.org/W1973264045","https://openalex.org/W1977556410","https://openalex.org/W1980317569","https://openalex.org/W1989270503","https://openalex.org/W1992419399","https://openalex.org/W2010140249","https://openalex.org/W2011430131","https://openalex.org/W2024168391","https://openalex.org/W2029248817","https://openalex.org/W2054787086","https://openalex.org/W2059515884","https://openalex.org/W2060207914","https://openalex.org/W2066965880","https://openalex.org/W2069552821","https://openalex.org/W2072131729","https://openalex.org/W2073568237","https://openalex.org/W2073849744","https://openalex.org/W2074408893","https://openalex.org/W2075098580","https://openalex.org/W2080710904","https://openalex.org/W2082897749","https://openalex.org/W2086959852","https://openalex.org/W2095595785","https://openalex.org/W2096832794","https://openalex.org/W2123386615","https://openalex.org/W2126337883","https://openalex.org/W2133003941","https://openalex.org/W2133059825","https://openalex.org/W2140405352","https://openalex.org/W2144405306","https://openalex.org/W2149596792","https://openalex.org/W2150593711","https://openalex.org/W2160039585","https://openalex.org/W2161160262","https://openalex.org/W3083424454"],"related_works":[],"abstract_inverted_index":{"K-means":[0],"is":[1,19],"undoubtedly":[2],"the":[3,23,27,49,62,133,149,160,165],"most":[4],"widely":[5],"used":[6],"partitional":[7],"clustering":[8],"algorithm.":[9],"Unfortunately,":[10],"due":[11],"to":[12,22,36,154],"its":[13],"gradient":[14],"descent":[15],"nature,":[16],"this":[17,38,104],"algorithm":[18],"highly":[20,83,144],"sensitive":[21],"initial":[24],"placement":[25],"of":[26,41,51,118,129,148,167],"cluster":[28],"centers.":[29],"Numerous":[30],"initialization":[31,86,152],"methods":[32,66,87,153],"have":[33,45],"been":[34],"proposed":[35,81,161],"address":[37],"problem.":[39],"Many":[40],"these":[42,119],"methods,":[43],"however,":[44],"superlinear":[46],"complexity":[47],"in":[48],"number":[50],"data":[52,59,130],"points,":[53],"making":[54],"them":[55],"impractical":[56],"for":[57],"large":[58,125],"sets.":[60],"On":[61],"other":[63],"hand,":[64],"linear":[65],"are":[67,93,143],"often":[68],"random":[69,151],"and/or":[70],"order-sensitive,":[71],"which":[72],"renders":[73],"their":[74],"results":[75],"unrepeatable.":[76],"Recently,":[77],"Su":[78],"and":[79,90,101,126,141,158],"Dy":[80],"two":[82,120],"successful":[84],"hierarchical":[85,169],"named":[88],"Var-Part":[89,140],"PCA-Part":[91,142],"that":[92,113,139,159],"not":[94],"only":[95],"linear,":[96],"but":[97],"also":[98],"deterministic":[99],"(nonrandom)":[100],"order-invariant.":[102],"In":[103],"paper,":[105],"we":[106],"propose":[107],"a":[108,115,124],"discriminant":[109],"analysis":[110],"based":[111],"approach":[112,162],"addresses":[114],"common":[116],"deficiency":[117],"methods.":[121,170],"Experiments":[122],"on":[123],"diverse":[127],"collection":[128],"sets":[131],"from":[132],"UCI":[134],"machine":[135],"learning":[136],"repository":[137],"demonstrate":[138],"competitive":[145],"with":[146],"one":[147],"best":[150],"date,":[155],"i.e.":[156],"k-means++,":[157],"significantly":[163],"improves":[164],"performance":[166],"both":[168]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":12},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":11}],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2016-06-24T00:00:00"}
