{"id":"https://openalex.org/W2759884981","doi":"https://doi.org/10.1162/neco_a_01014","title":"An Initialization Method Based on Hybrid Distance for k-Means Algorithm","display_name":"An Initialization Method Based on Hybrid Distance for k-Means Algorithm","publication_year":2017,"publication_date":"2017-09-28","ids":{"openalex":"https://openalex.org/W2759884981","doi":"https://doi.org/10.1162/neco_a_01014","mag":"2759884981","pmid":"https://pubmed.ncbi.nlm.nih.gov/28957026"},"language":"en","primary_location":{"id":"doi:10.1162/neco_a_01014","is_oa":false,"landing_page_url":"https://doi.org/10.1162/neco_a_01014","pdf_url":null,"source":{"id":"https://openalex.org/S207023548","display_name":"Neural Computation","issn_l":"0899-7667","issn":["0899-7667","1530-888X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718","https://openalex.org/P4310316440"],"host_organization_lineage_names":["The MIT Press","Massachusetts Institute of Technology"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computation","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5101750857","display_name":"Jie Yang","orcid":"https://orcid.org/0000-0002-3109-472X"},"institutions":[{"id":"https://openalex.org/I21945476","display_name":"Shanghai Normal University","ror":"https://ror.org/01cxqmw89","country_code":"CN","type":"education","lineage":["https://openalex.org/I21945476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jie Yang","raw_affiliation_strings":["College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China","institution_ids":["https://openalex.org/I21945476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054182752","display_name":"Yan Ma","orcid":"https://orcid.org/0000-0003-4626-1401"},"institutions":[{"id":"https://openalex.org/I21945476","display_name":"Shanghai Normal University","ror":"https://ror.org/01cxqmw89","country_code":"CN","type":"education","lineage":["https://openalex.org/I21945476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yan Ma","raw_affiliation_strings":["College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China","institution_ids":["https://openalex.org/I21945476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065311088","display_name":"Xiangfen Zhang","orcid":"https://orcid.org/0000-0002-5332-3175"},"institutions":[{"id":"https://openalex.org/I21945476","display_name":"Shanghai Normal University","ror":"https://ror.org/01cxqmw89","country_code":"CN","type":"education","lineage":["https://openalex.org/I21945476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiangfen Zhang","raw_affiliation_strings":["College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China","institution_ids":["https://openalex.org/I21945476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047882020","display_name":"Shunbao Li","orcid":"https://orcid.org/0000-0002-0011-5938"},"institutions":[{"id":"https://openalex.org/I21945476","display_name":"Shanghai Normal University","ror":"https://ror.org/01cxqmw89","country_code":"CN","type":"education","lineage":["https://openalex.org/I21945476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shunbao Li","raw_affiliation_strings":["College Mathematics and Science, Shanghai Normal University, Shanghai 200234, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College Mathematics and Science, Shanghai Normal University, Shanghai 200234, China","institution_ids":["https://openalex.org/I21945476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100458681","display_name":"Yuping Zhang","orcid":"https://orcid.org/0000-0001-8986-0354"},"institutions":[{"id":"https://openalex.org/I21945476","display_name":"Shanghai Normal University","ror":"https://ror.org/01cxqmw89","country_code":"CN","type":"education","lineage":["https://openalex.org/I21945476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuping Zhang","raw_affiliation_strings":["College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China","institution_ids":["https://openalex.org/I21945476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5047882020","https://openalex.org/A5054182752","https://openalex.org/A5065311088","https://openalex.org/A5100458681","https://openalex.org/A5101750857"],"corresponding_institution_ids":["https://openalex.org/I21945476"],"apc_list":null,"apc_paid":null,"fwci":3.1939,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.93309428,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"29","issue":"11","first_page":"3094","last_page":"3117"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9997000098228455,"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":0.9997000098228455,"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/T11106","display_name":"Data Management and Algorithms","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9915000200271606,"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":0.8111357688903809},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.7891353368759155},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.6683228015899658},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.6145498752593994},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6119843125343323},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.592707097530365},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.5866081714630127},{"id":"https://openalex.org/keywords/k-medians-clustering","display_name":"k-medians clustering","score":0.4645751416683197},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.4587256610393524},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.45826464891433716},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.45589566230773926},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4348278045654297},{"id":"https://openalex.org/keywords/distance-measures","display_name":"Distance measures","score":0.42656373977661133},{"id":"https://openalex.org/keywords/determining-the-number-of-clusters-in-a-data-set","display_name":"Determining the number of clusters in a data set","score":0.41811931133270264},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3987809121608734},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3554724454879761},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.31967055797576904},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.3075984716415405},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.25923627614974976}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8111357688903809},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.7891353368759155},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.6683228015899658},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.6145498752593994},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6119843125343323},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.592707097530365},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.5866081714630127},{"id":"https://openalex.org/C115328559","wikidata":"https://www.wikidata.org/wiki/Q4041956","display_name":"k-medians clustering","level":5,"score":0.4645751416683197},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.4587256610393524},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.45826464891433716},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.45589566230773926},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4348278045654297},{"id":"https://openalex.org/C2639959","wikidata":"https://www.wikidata.org/wiki/Q1344778","display_name":"Distance measures","level":2,"score":0.42656373977661133},{"id":"https://openalex.org/C149872217","wikidata":"https://www.wikidata.org/wiki/Q5265701","display_name":"Determining the number of clusters in a data set","level":5,"score":0.41811931133270264},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3987809121608734},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3554724454879761},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.31967055797576904},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.3075984716415405},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25923627614974976},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1162/neco_a_01014","is_oa":false,"landing_page_url":"https://doi.org/10.1162/neco_a_01014","pdf_url":null,"source":{"id":"https://openalex.org/S207023548","display_name":"Neural Computation","issn_l":"0899-7667","issn":["0899-7667","1530-888X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315718","host_organization_name":"The MIT Press","host_organization_lineage":["https://openalex.org/P4310315718","https://openalex.org/P4310316440"],"host_organization_lineage_names":["The MIT Press","Massachusetts Institute of Technology"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Computation","raw_type":"journal-article"},{"id":"pmid:28957026","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28957026","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural computation","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309612","display_name":"Natural Science Foundation of Shanghai","ror":null},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322374","display_name":"Shanghai Normal University","ror":"https://ror.org/01cxqmw89"},{"id":"https://openalex.org/F4320332688","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W147612390","https://openalex.org/W1489608363","https://openalex.org/W1578658900","https://openalex.org/W1594924988","https://openalex.org/W1602306524","https://openalex.org/W1973264045","https://openalex.org/W1989270503","https://openalex.org/W2002041442","https://openalex.org/W2022201359","https://openalex.org/W2029248817","https://openalex.org/W2045691329","https://openalex.org/W2061008146","https://openalex.org/W2070896531","https://openalex.org/W2075098580","https://openalex.org/W2122051577","https://openalex.org/W2130880600","https://openalex.org/W2137578940","https://openalex.org/W2142458924","https://openalex.org/W2165835468","https://openalex.org/W2168408108","https://openalex.org/W2599272755","https://openalex.org/W4205821171","https://openalex.org/W4233830635"],"related_works":["https://openalex.org/W1491908038","https://openalex.org/W2803938633","https://openalex.org/W4310575853","https://openalex.org/W4384026335","https://openalex.org/W2599363393","https://openalex.org/W3046546608","https://openalex.org/W1987634878","https://openalex.org/W2598823661","https://openalex.org/W3025379803","https://openalex.org/W2018402912"],"abstract_inverted_index":{"The":[0],"traditional":[1],"[Formula:":[2],"see":[3],"text]-means":[4],"algorithm":[5,22,92,142,158],"has":[6],"been":[7],"widely":[8],"used":[9],"as":[10,61,63],"a":[11,75,108],"simple":[12],"and":[13,68,84,151],"efficient":[14],"clustering":[15,111,115,134],"method.":[16],"However,":[17],"the":[18,27,34,50,56,64,102,114,120,129,140,153,156],"performance":[19],"of":[20,29,52,58,155],"this":[21,46],"is":[23,42],"highly":[24],"dependent":[25],"on":[26,87,119,147],"selection":[28],"initial":[30,39,95],"cluster":[31,40,96],"centers.":[32],"Therefore,":[33],"method":[35],"adopted":[36],"for":[37,93],"choosing":[38],"centers":[41,97],"extremely":[43],"important.":[44],"In":[45,71],"letter,":[47],"we":[48,73,89,106],"redefine":[49],"density":[51],"points":[53,67],"according":[54],"to":[55,127,159],"number":[57],"its":[59],"neighbors,":[60],"well":[62],"distance":[65,77,83],"between":[66],"their":[69],"neighbors.":[70],"addition,":[72],"define":[74],"new":[76,109],"measure":[78],"that":[79,98,139],"considers":[80],"both":[81],"Euclidean":[82],"density.":[85],"Based":[86],"that,":[88],"propose":[90,107],"an":[91],"selecting":[94],"can":[99,124],"dynamically":[100],"adjust":[101],"weighting":[103],"parameter.":[104],"Furthermore,":[105],"internal":[110],"validation":[112,116],"measure,":[113],"index":[117],"based":[118],"neighbors":[121],"(CVN),":[122],"which":[123],"be":[125],"exploited":[126],"select":[128],"optimal":[130],"result":[131],"among":[132],"multiple":[133],"results.":[135],"Experimental":[136],"results":[137],"show":[138],"proposed":[141,157],"outperforms":[143],"existing":[144],"initialization":[145],"methods":[146],"real-world":[148],"data":[149,160],"sets":[150,161],"demonstrates":[152],"adaptability":[154],"with":[162],"various":[163],"characteristics.":[164]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":4}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2017-10-06T00:00:00"}