{"id":"https://openalex.org/W2951416632","doi":"https://doi.org/10.1109/tbdata.2019.2922969","title":"Finding and Tracking Multi-Density Clusters in Online Dynamic Data Streams","display_name":"Finding and Tracking Multi-Density Clusters in Online Dynamic Data Streams","publication_year":2019,"publication_date":"2019-06-14","ids":{"openalex":"https://openalex.org/W2951416632","doi":"https://doi.org/10.1109/tbdata.2019.2922969","mag":"2951416632"},"language":"en","primary_location":{"id":"doi:10.1109/tbdata.2019.2922969","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2019.2922969","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.dora.dmu.ac.uk/handle/2086/17876","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080581679","display_name":"Conor Fahy","orcid":"https://orcid.org/0000-0002-9549-284X"},"institutions":[{"id":"https://openalex.org/I66943878","display_name":"De Montfort University","ror":"https://ror.org/0312pnr83","country_code":"GB","type":"education","lineage":["https://openalex.org/I66943878"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Conor Fahy","raw_affiliation_strings":["Centre for Computational Intelligence (CCI), School of Computer Science and Informatics, De Montfort University, The Gateway, Leicester, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0002-9549-284X","affiliations":[{"raw_affiliation_string":"Centre for Computational Intelligence (CCI), School of Computer Science and Informatics, De Montfort University, The Gateway, Leicester, United Kingdom","institution_ids":["https://openalex.org/I66943878"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040583251","display_name":"Shengxiang Yang","orcid":"https://orcid.org/0000-0001-7222-4917"},"institutions":[{"id":"https://openalex.org/I66943878","display_name":"De Montfort University","ror":"https://ror.org/0312pnr83","country_code":"GB","type":"education","lineage":["https://openalex.org/I66943878"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Shengxiang Yang","raw_affiliation_strings":["Centre for Computational Intelligence (CCI), School of Computer Science and Informatics, De Montfort University, The Gateway, Leicester, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0001-7222-4917","affiliations":[{"raw_affiliation_string":"Centre for Computational Intelligence (CCI), School of Computer Science and Informatics, De Montfort University, The Gateway, Leicester, United Kingdom","institution_ids":["https://openalex.org/I66943878"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I66943878"],"apc_list":null,"apc_paid":null,"fwci":1.5531,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.87200915,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"8","issue":"1","first_page":"178","last_page":"192"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","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/T12761","display_name":"Data Stream Mining Techniques","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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9962000250816345,"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":0.9958999752998352,"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/computer-science","display_name":"Computer science","score":0.8130355477333069},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7719581723213196},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.6530033349990845},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6243801116943359},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6044062376022339},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.508770763874054},{"id":"https://openalex.org/keywords/dbscan","display_name":"DBSCAN","score":0.484079509973526},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.4420982599258423},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.4258178770542145},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3445231318473816},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.23703846335411072},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.22190234065055847},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.14092370867729187}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8130355477333069},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7719581723213196},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.6530033349990845},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6243801116943359},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6044062376022339},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.508770763874054},{"id":"https://openalex.org/C46576248","wikidata":"https://www.wikidata.org/wiki/Q1114630","display_name":"DBSCAN","level":5,"score":0.484079509973526},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.4420982599258423},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.4258178770542145},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3445231318473816},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.23703846335411072},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.22190234065055847},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.14092370867729187},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tbdata.2019.2922969","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2019.2922969","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-article"},{"id":"pmh:oai:dora.dmu.ac.uk:2086/17876","is_oa":true,"landing_page_url":"https://www.dora.dmu.ac.uk/handle/2086/17876","pdf_url":null,"source":{"id":"https://openalex.org/S4306400394","display_name":"DMU Open Research Archive (De Montfort University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66943878","host_organization_name":"De Montfort University","host_organization_lineage":["https://openalex.org/I66943878"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"}],"best_oa_location":{"id":"pmh:oai:dora.dmu.ac.uk:2086/17876","is_oa":true,"landing_page_url":"https://www.dora.dmu.ac.uk/handle/2086/17876","pdf_url":null,"source":{"id":"https://openalex.org/S4306400394","display_name":"DMU Open Research Archive (De Montfort University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66943878","host_organization_name":"De Montfort University","host_organization_lineage":["https://openalex.org/I66943878"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3975464728","display_name":null,"funder_award_id":"EP/K001523/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G5662168501","display_name":null,"funder_award_id":"EP/K001310/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G7042882887","display_name":null,"funder_award_id":"61673331","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8793558268","display_name":"Evolutionary Computation for Dynamic Optimisation in Network Environments","funder_award_id":"EP/K001523/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W86423600","https://openalex.org/W182707955","https://openalex.org/W855829896","https://openalex.org/W1523741643","https://openalex.org/W1552074189","https://openalex.org/W1565377632","https://openalex.org/W1673310716","https://openalex.org/W1970088130","https://openalex.org/W1975081465","https://openalex.org/W1975852288","https://openalex.org/W1977556410","https://openalex.org/W1987799824","https://openalex.org/W2003411394","https://openalex.org/W2008298394","https://openalex.org/W2030096042","https://openalex.org/W2033403400","https://openalex.org/W2041565863","https://openalex.org/W2055902670","https://openalex.org/W2064314060","https://openalex.org/W2072240081","https://openalex.org/W2097091016","https://openalex.org/W2112482089","https://openalex.org/W2129395028","https://openalex.org/W2135335717","https://openalex.org/W2141245797","https://openalex.org/W2143560894","https://openalex.org/W2150312211","https://openalex.org/W2152601912","https://openalex.org/W2157107726","https://openalex.org/W2165207129","https://openalex.org/W2165232124","https://openalex.org/W2170936641","https://openalex.org/W2252617635","https://openalex.org/W2482589566","https://openalex.org/W2559950244","https://openalex.org/W2618055708","https://openalex.org/W2795483971","https://openalex.org/W3003253354","https://openalex.org/W4234406933","https://openalex.org/W4244030505","https://openalex.org/W4292083457","https://openalex.org/W6680192438"],"related_works":["https://openalex.org/W4389449520","https://openalex.org/W127192698","https://openalex.org/W2570600173","https://openalex.org/W2893008024","https://openalex.org/W2394193399","https://openalex.org/W2743735673","https://openalex.org/W2522231769","https://openalex.org/W4312214159","https://openalex.org/W2045938006","https://openalex.org/W4378676944"],"abstract_inverted_index":{"Change":[0],"is":[1,21,138,151,162,167],"one":[2],"of":[3,36,56,62,85,96,146,180],"the":[4,44,79,83,118,126,144],"biggest":[5],"challenges":[6],"in":[7,23,47,90,125],"dynamic":[8,92],"stream":[9],"mining.":[10],"From":[11],"a":[12,34,48,68,91,112,178],"data-mining":[13],"perspective,":[14],"adapting":[15],"<italic":[16],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[17],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">and":[18],"tracking</i>":[19],"change":[20,30],"desirable":[22],"order":[24],"to":[25,42,74,111,117,143,153,169,172,200],"understand":[26],"how":[27],"and":[28,82,87,103,141,157,182,198],"why":[29],"has":[31],"occurred.":[32],"Clustering,":[33],"form":[35],"unsupervised":[37],"learning,":[38],"can":[39,190],"be":[40],"used":[41],"identify":[43],"underlying":[45],"patterns":[46,194],"stream.":[49,93],"Density-based":[50],"clustering":[51],"identifies":[52],"clusters":[53,102,122],"as":[54],"areas":[55,61],"high":[57],"density":[58],"separated":[59],"by":[60],"low":[63],"density.":[64],"This":[65],"paper":[66],"proposes":[67],"Multi-Density":[69],"Stream":[70],"Clustering":[71],"(MDSC)":[72],"algorithm":[73],"address":[75],"these":[76],"two":[77,97],"problems;":[78],"multi-density":[80],"problem":[81,84],"discovering":[86],"tracking":[88],"changes":[89],"MDSC":[94,166,189],"consists":[95],"on-line":[98],"components;":[99],"discovered,":[100],"labelled":[101,140],"an":[104,129,154],"outlier":[105,119],"buffer.":[106,120],"Incoming":[107],"points":[108],"are":[109,123],"assigned":[110],"live":[113,147],"cluster":[114,137],"or":[115],"passed":[116],"New":[121],"discovered":[124,136],"buffer":[127],"using":[128],"ant-inspired":[130],"swarm":[131],"intelligence":[132],"approach.":[133],"The":[134],"newly":[135],"uniquely":[139],"added":[142],"set":[145],"clusters.":[148],"Processed":[149],"data":[150],"subject":[152],"ageing":[155],"function":[156],"will":[158],"disappear":[159],"when":[160],"it":[161],"no":[163],"longer":[164],"relevant.":[165],"shown":[168],"perform":[170],"favourably":[171],"state-of-the-art":[173],"peer":[174],"stream-clustering":[175],"algorithms":[176],"on":[177],"range":[179],"real":[181],"synthetic":[183],"data-streams.":[184],"Experimental":[185],"results":[186],"suggest":[187],"that":[188],"discover":[191],"qualitatively":[192],"useful":[193],"while":[195],"being":[196],"scalable":[197],"robust":[199],"noise.":[201]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
