{"id":"https://openalex.org/W2043799446","doi":"https://doi.org/10.1109/icnc.2013.6818108","title":"Evolutionary clustering with DBSCAN","display_name":"Evolutionary clustering with DBSCAN","publication_year":2013,"publication_date":"2013-07-01","ids":{"openalex":"https://openalex.org/W2043799446","doi":"https://doi.org/10.1109/icnc.2013.6818108","mag":"2043799446"},"language":"en","primary_location":{"id":"doi:10.1109/icnc.2013.6818108","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnc.2013.6818108","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 Ninth International Conference on Natural Computation (ICNC)","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/A5100649616","display_name":"Yuchao Zhang","orcid":"https://orcid.org/0009-0006-0191-3612"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yuchao Zhang","raw_affiliation_strings":["Beijing Institute of System Engineering, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of System Engineering, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086089915","display_name":"Hongfu Liu","orcid":"https://orcid.org/0000-0002-4261-8154"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongfu Liu","raw_affiliation_strings":["School of Economics and Management, Beihang University, Beijing, China","School of Economics and Management; Beihang University; Beijing China"],"affiliations":[{"raw_affiliation_string":"School of Economics and Management, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"School of Economics and Management; Beihang University; Beijing China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101561136","display_name":"Bo Deng","orcid":"https://orcid.org/0000-0001-7170-701X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bo Deng","raw_affiliation_strings":["Beijing Institute of System Engineering, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of System Engineering, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100649616"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4809,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.75688625,"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":"923","last_page":"928"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9941999912261963,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9941999912261963,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9904999732971191,"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":0.968999981880188,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/dbscan","display_name":"DBSCAN","score":0.9310779571533203},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.881009578704834},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6341093182563782},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.6210991144180298},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.5995217561721802},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.5615127682685852},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.5489868521690369},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5031484961509705},{"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":0.48599228262901306},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4857240319252014},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.4805896282196045},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4662410616874695},{"id":"https://openalex.org/keywords/single-linkage-clustering","display_name":"Single-linkage clustering","score":0.45572203397750854},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.41939643025398254}],"concepts":[{"id":"https://openalex.org/C46576248","wikidata":"https://www.wikidata.org/wiki/Q1114630","display_name":"DBSCAN","level":5,"score":0.9310779571533203},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.881009578704834},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6341093182563782},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.6210991144180298},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.5995217561721802},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.5615127682685852},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.5489868521690369},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5031484961509705},{"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":0.48599228262901306},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4857240319252014},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.4805896282196045},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4662410616874695},{"id":"https://openalex.org/C22648726","wikidata":"https://www.wikidata.org/wiki/Q7523744","display_name":"Single-linkage clustering","level":5,"score":0.45572203397750854},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.41939643025398254}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icnc.2013.6818108","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnc.2013.6818108","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 Ninth International Conference on Natural Computation (ICNC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1604980173","https://openalex.org/W1660133578","https://openalex.org/W1673310716","https://openalex.org/W1977496278","https://openalex.org/W1998819761","https://openalex.org/W2080068757","https://openalex.org/W2109275473","https://openalex.org/W2119939946","https://openalex.org/W2128012710","https://openalex.org/W2129630294","https://openalex.org/W2132914434","https://openalex.org/W2169581671","https://openalex.org/W2170337404","https://openalex.org/W2293546752"],"related_works":["https://openalex.org/W2394193399","https://openalex.org/W2387373525","https://openalex.org/W2809859387","https://openalex.org/W2054669762","https://openalex.org/W2392255773","https://openalex.org/W4220814143","https://openalex.org/W2547681860","https://openalex.org/W2342518500","https://openalex.org/W2103650652","https://openalex.org/W2389934482"],"abstract_inverted_index":{"Clustering":[0],"algorithms":[1,47],"have":[2,48],"been":[3,49],"used":[4],"in":[5],"the":[6,17,20,53,67,93,102,109,114,120,128,139,144,150],"field":[7],"of":[8,19,39,44,61,86,95,104],"data":[9,22],"mining":[10],"for":[11],"such":[12,51,126],"a":[13],"long":[14],"time.":[15],"With":[16],"accumulation":[18],"online":[21],"sets,":[23],"studies":[24],"on":[25,92,108],"cluster":[26],"evolution":[27,151],"were":[28,63],"carried":[29],"out":[30],"so":[31],"as":[32,52,127],"to":[33,65,138],"decrease":[34],"noise":[35],"and":[36,56,113],"maintain":[37],"continuity":[38],"clustering":[40,46,69,79,85,124],"results.":[41],"A":[42],"number":[43],"evolutionary":[45,54,78,123,129],"proposed,":[50],"K-means":[55,130],"Spectral":[57],"clustering,":[58,131],"but":[59,141],"none":[60],"them":[62],"engaged":[64],"solving":[66],"density-based":[68],"problem.":[70],"In":[71],"this":[72],"paper,":[73],"we":[74],"initially":[75],"present":[76],"an":[77],"algorithm":[80],"with":[81,88,119,146],"DBSCAN":[82,116],"(density-based":[83],"spatial":[84],"applications":[87],"noise),":[89],"which":[90],"is":[91],"basis":[94],"temporal":[96],"smoothness":[97],"penalty":[98],"framework.":[99],"We":[100],"conduct":[101],"evaluations":[103],"our":[105,132],"framework":[106],"both":[107],"random":[110],"Gaussian":[111],"dataset":[112],"classical":[115],"dataset.":[117],"Compared":[118],"other":[121],"similar":[122],"algorithms,":[125],"method":[133],"can":[134],"not":[135],"only":[136],"resist":[137],"noise,":[140],"also":[142],"distinguish":[143],"clusters":[145],"arbitrary":[147],"shapes":[148],"during":[149],"process.":[152]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}