{"id":"https://openalex.org/W3210318391","doi":"https://doi.org/10.3233/ida-205459","title":"Time-series data dynamic density clustering","display_name":"Time-series data dynamic density clustering","publication_year":2021,"publication_date":"2021-10-29","ids":{"openalex":"https://openalex.org/W3210318391","doi":"https://doi.org/10.3233/ida-205459","mag":"3210318391"},"language":"en","primary_location":{"id":"doi:10.3233/ida-205459","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-205459","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","raw_type":"journal-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/A5101850564","display_name":"Hao Chen","orcid":"https://orcid.org/0000-0001-6458-4584"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hao Chen","raw_affiliation_strings":["School of Computer Science and Technology, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an, Shaanxi, China","Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an, Shaanxi, China","School of Computer Science and Technology, Xi'an University of Posts and Telecommunications, Xi'an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an, Shaanxi, China","institution_ids":["https://openalex.org/I4210136859"]},{"raw_affiliation_string":"Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an, Shaanxi, China","institution_ids":["https://openalex.org/I4210136859"]},{"raw_affiliation_string":"School of Computer Science and Technology, Xi'an University of Posts and Telecommunications, Xi'an, Shaanxi, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002322690","display_name":"Yu Xia","orcid":"https://orcid.org/0000-0002-5212-0931"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Xia","raw_affiliation_strings":["School of Computer Science and Technology, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an, Shaanxi, China","School of Computer Science and Technology, Xi'an University of Posts and Telecommunications, Xi'an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an, Shaanxi, China","institution_ids":["https://openalex.org/I4210136859"]},{"raw_affiliation_string":"School of Computer Science and Technology, Xi'an University of Posts and Telecommunications, Xi'an, Shaanxi, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057397960","display_name":"Yuekai Pan","orcid":"https://orcid.org/0000-0001-6962-7301"},"institutions":[{"id":"https://openalex.org/I4210136859","display_name":"Xi\u2019an University of Posts and Telecommunications","ror":"https://ror.org/04jn0td46","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210136859"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuekai Pan","raw_affiliation_strings":["School of Computer Science and Technology, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an, Shaanxi, China","School of Computer Science and Technology, Xi'an University of Posts and Telecommunications, Xi'an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an, Shaanxi, China","institution_ids":["https://openalex.org/I4210136859"]},{"raw_affiliation_string":"School of Computer Science and Technology, Xi'an University of Posts and Telecommunications, Xi'an, Shaanxi, China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077035751","display_name":"Qing Yang","orcid":"https://orcid.org/0000-0002-7529-9065"},"institutions":[{"id":"https://openalex.org/I4210095228","display_name":"Xi'an Physical Education University","ror":"https://ror.org/00pt5by23","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210095228"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Yang","raw_affiliation_strings":["School of Sport and Health Sciences, Xi\u2019an Physical Education University, Xi\u2019an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"School of Sport and Health Sciences, Xi\u2019an Physical Education University, Xi\u2019an, Shaanxi, China","institution_ids":["https://openalex.org/I4210095228"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101850564"],"corresponding_institution_ids":["https://openalex.org/I4210136859"],"apc_list":null,"apc_paid":null,"fwci":0.1524,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.46227181,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"25","issue":"6","first_page":"1487","last_page":"1506"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9998999834060669,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9800999760627747,"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":0.978600025177002,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8522113561630249},{"id":"https://openalex.org/keywords/timeline","display_name":"Timeline","score":0.8297008275985718},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7321875095367432},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6796788573265076},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.629664957523346},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5410590767860413},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5236485004425049},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5230311155319214},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.49682095646858215},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.4595555067062378},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.45096781849861145},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4215252995491028},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2025887370109558},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1798819899559021},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.17912045121192932},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12344557046890259}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8522113561630249},{"id":"https://openalex.org/C4438859","wikidata":"https://www.wikidata.org/wiki/Q186117","display_name":"Timeline","level":2,"score":0.8297008275985718},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7321875095367432},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6796788573265076},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.629664957523346},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5410590767860413},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5236485004425049},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5230311155319214},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.49682095646858215},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.4595555067062378},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.45096781849861145},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4215252995491028},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2025887370109558},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1798819899559021},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.17912045121192932},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12344557046890259},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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":1,"locations":[{"id":"doi:10.3233/ida-205459","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-205459","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1499049447","https://openalex.org/W1673310716","https://openalex.org/W1974198014","https://openalex.org/W1991213875","https://openalex.org/W2095897464","https://openalex.org/W2106595237","https://openalex.org/W2127218421","https://openalex.org/W2165835468","https://openalex.org/W2412370644","https://openalex.org/W2412666500","https://openalex.org/W2789511664","https://openalex.org/W2796319428","https://openalex.org/W3164648757","https://openalex.org/W4231029117","https://openalex.org/W6796104967"],"related_works":["https://openalex.org/W2491448268","https://openalex.org/W2559422900","https://openalex.org/W2892323093","https://openalex.org/W3144143113","https://openalex.org/W2394193399","https://openalex.org/W2181939267","https://openalex.org/W2390610678","https://openalex.org/W3071522575","https://openalex.org/W2363054820","https://openalex.org/W2101174895"],"abstract_inverted_index":{"In":[0,98,169],"many":[1],"clustering":[2,77,90,153,163],"problems,":[3],"the":[4,29,39,48,51,71,75,84,89,103,107,114,119,148,151,170,179,200],"whole":[5,152],"data":[6,40,49,64,108,129,181],"is":[7,16,45,69,124],"not":[8,80],"always":[9],"static.":[10,46],"Over":[11],"time,":[12],"part":[13],"of":[14,56,63,106,128,133,150],"it":[15,145],"likely":[17],"to":[18,83,118,146,177],"be":[19,32],"changed,":[20],"such":[21],"as":[22],"updated,":[23],"erased,":[24],"etc.":[25],"Suffer":[26],"this":[27,99],"effect,":[28],"timeline":[30,52],"can":[31,143,189],"divided":[33],"into":[34],"multiple":[35],"time":[36,43,67,94,115],"segments.":[37],"And,":[38],"at":[41,92],"each":[42],"slice":[44,116],"Then,":[47],"along":[50],"shows":[53],"a":[54,125,160],"series":[55],"dynamic":[57,161],"intermediate":[58],"states.":[59],"The":[60,185],"union":[61],"set":[62,109,130],"from":[65],"all":[66,195],"slices":[68,95],"called":[70],"time-series":[72,85,167,180],"data.":[73,86,168],"Obviously,":[74],"traditional":[76],"process":[78,91],"does":[79],"apply":[81],"directly":[82],"Meanwhile,":[87],"repeating":[88],"every":[93],"costs":[96],"tremendous.":[97],"paper,":[100],"we":[101,142,158,172],"analyze":[102],"transition":[104],"rules":[105],"and":[110,131],"cluster":[111,134],"structure":[112,135],"when":[113],"shifts":[117],"next.":[120],"We":[121],"find":[122],"there":[123],"distinct":[126],"correlation":[127],"succession":[132],"between":[136],"two":[137],"adjacent":[138],"ones,":[139],"which":[140],"means":[141],"use":[144],"reduce":[147],"cost":[149,202],"process.":[154],"Inspired":[155],"by":[156],"it,":[157],"propose":[159],"density":[162],"method":[164],"(DDC)":[165],"for":[166,182,194],"simulations,":[171],"choose":[173],"6":[174,196],"representative":[175],"problems":[176,197],"construct":[178],"testing":[183],"DDC.":[184],"results":[186,193],"show":[187],"DDC":[188],"get":[190],"high":[191],"accuracy":[192],"while":[198],"reducing":[199],"overall":[201],"markedly.":[203]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}