{"id":"https://openalex.org/W4291993864","doi":"https://doi.org/10.1108/dta-08-2021-0222","title":"TMsDP: two-stage density peak clustering based on multi-strategy optimization","display_name":"TMsDP: two-stage density peak clustering based on multi-strategy optimization","publication_year":2022,"publication_date":"2022-08-16","ids":{"openalex":"https://openalex.org/W4291993864","doi":"https://doi.org/10.1108/dta-08-2021-0222"},"language":"en","primary_location":{"id":"doi:10.1108/dta-08-2021-0222","is_oa":true,"landing_page_url":"https://doi.org/10.1108/dta-08-2021-0222","pdf_url":"https://www.emerald.com/insight/content/doi/10.1108/DTA-08-2021-0222/full/pdf?title=tmsdp-two-stage-density-peak-clustering-based-on-multi-strategy-optimization","source":{"id":"https://openalex.org/S4210171756","display_name":"Data Technologies and Applications","issn_l":"2514-9288","issn":["2514-9288","2514-9318"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Technologies and Applications","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://www.emerald.com/insight/content/doi/10.1108/DTA-08-2021-0222/full/pdf?title=tmsdp-two-stage-density-peak-clustering-based-on-multi-strategy-optimization","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059572314","display_name":"Jie Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I179324530","display_name":"Jilin University of Finance and Economics","ror":"https://ror.org/04az9eh24","country_code":"CN","type":"education","lineage":["https://openalex.org/I179324530"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Ma","raw_affiliation_strings":["School of Business and Management, Jilin University, Changchun, China"],"raw_orcid":"https://orcid.org/0000-0002-9005-0751","affiliations":[{"raw_affiliation_string":"School of Business and Management, Jilin University, Changchun, China","institution_ids":["https://openalex.org/I179324530"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001350847","display_name":"Zhiyuan Hao","orcid":"https://orcid.org/0000-0002-9215-2874"},"institutions":[{"id":"https://openalex.org/I179324530","display_name":"Jilin University of Finance and Economics","ror":"https://ror.org/04az9eh24","country_code":"CN","type":"education","lineage":["https://openalex.org/I179324530"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhiyuan Hao","raw_affiliation_strings":["School of Business and Management, Jilin University, Changchun, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Business and Management, Jilin University, Changchun, China","institution_ids":["https://openalex.org/I179324530"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012138380","display_name":"Mo Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I152031979","display_name":"Nanjing Normal University","ror":"https://ror.org/036trcv74","country_code":"CN","type":"education","lineage":["https://openalex.org/I152031979"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Mo Hu","raw_affiliation_strings":["Department of Network and New Media, School of Journalism and Communication, Nanjing Normal University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Network and New Media, School of Journalism and Communication, Nanjing Normal University, Nanjing, China","institution_ids":["https://openalex.org/I152031979"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5001350847","https://openalex.org/A5012138380"],"corresponding_institution_ids":["https://openalex.org/I152031979","https://openalex.org/I179324530"],"apc_list":null,"apc_paid":null,"fwci":0.2775,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.62636252,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"58","issue":"3","first_page":"380","last_page":"406"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9957000017166138,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8375027179718018},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5975736975669861},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5884880423545837},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.550698459148407},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5121264457702637},{"id":"https://openalex.org/keywords/k-medians-clustering","display_name":"k-medians clustering","score":0.4783753454685211},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.46342694759368896},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.4568312168121338},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.4469906687736511},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.42646434903144836},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3656703531742096},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34546399116516113},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3435550332069397},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33602607250213623},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.2795698940753937},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.16024717688560486},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.15744516253471375}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8375027179718018},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5975736975669861},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5884880423545837},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.550698459148407},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5121264457702637},{"id":"https://openalex.org/C115328559","wikidata":"https://www.wikidata.org/wiki/Q4041956","display_name":"k-medians clustering","level":5,"score":0.4783753454685211},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46342694759368896},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.4568312168121338},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.4469906687736511},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.42646434903144836},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3656703531742096},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34546399116516113},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3435550332069397},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33602607250213623},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.2795698940753937},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.16024717688560486},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.15744516253471375},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1108/dta-08-2021-0222","is_oa":true,"landing_page_url":"https://doi.org/10.1108/dta-08-2021-0222","pdf_url":"https://www.emerald.com/insight/content/doi/10.1108/DTA-08-2021-0222/full/pdf?title=tmsdp-two-stage-density-peak-clustering-based-on-multi-strategy-optimization","source":{"id":"https://openalex.org/S4210171756","display_name":"Data Technologies and Applications","issn_l":"2514-9288","issn":["2514-9288","2514-9318"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Technologies and Applications","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1108/dta-08-2021-0222","is_oa":true,"landing_page_url":"https://doi.org/10.1108/dta-08-2021-0222","pdf_url":"https://www.emerald.com/insight/content/doi/10.1108/DTA-08-2021-0222/full/pdf?title=tmsdp-two-stage-density-peak-clustering-based-on-multi-strategy-optimization","source":{"id":"https://openalex.org/S4210171756","display_name":"Data Technologies and Applications","issn_l":"2514-9288","issn":["2514-9288","2514-9318"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Technologies and Applications","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6667611114","display_name":null,"funder_award_id":"20210101480JC","funder_id":"https://openalex.org/F4320310121","funder_display_name":"Natural Science Foundation of Jilin Province"}],"funders":[{"id":"https://openalex.org/F4320310121","display_name":"Natural Science Foundation of Jilin Province","ror":null},{"id":"https://openalex.org/F4320322174","display_name":"People's Government of Jilin Province","ror":"https://ror.org/02fzqav45"},{"id":"https://openalex.org/F4320335869","display_name":"National Social Science Fund of China","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4291993864.pdf","grobid_xml":"https://content.openalex.org/works/W4291993864.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W2011430131","https://openalex.org/W2165232124","https://openalex.org/W2165835468","https://openalex.org/W2739661180","https://openalex.org/W2788251668","https://openalex.org/W2789456849","https://openalex.org/W2799925445","https://openalex.org/W2887102415","https://openalex.org/W2889892655","https://openalex.org/W2891196457","https://openalex.org/W2900089459","https://openalex.org/W2900672048","https://openalex.org/W2920725297","https://openalex.org/W2951598408","https://openalex.org/W2953618482","https://openalex.org/W2990619288","https://openalex.org/W3000021816","https://openalex.org/W3004688128","https://openalex.org/W3010984744","https://openalex.org/W3012210245","https://openalex.org/W3022489034","https://openalex.org/W3025793945","https://openalex.org/W3041720305","https://openalex.org/W3042729432","https://openalex.org/W3044283672","https://openalex.org/W3046073088","https://openalex.org/W3046083930","https://openalex.org/W3047655929","https://openalex.org/W3048644634","https://openalex.org/W3092037388","https://openalex.org/W3093243507","https://openalex.org/W3104119337","https://openalex.org/W3112798043","https://openalex.org/W3126945873","https://openalex.org/W3127814053","https://openalex.org/W3150954968","https://openalex.org/W3153640078","https://openalex.org/W3167987296","https://openalex.org/W3175206743","https://openalex.org/W3196437584","https://openalex.org/W3203644918","https://openalex.org/W3211226056"],"related_works":["https://openalex.org/W1457719682","https://openalex.org/W3004745571","https://openalex.org/W2803938633","https://openalex.org/W2380798983","https://openalex.org/W2355295424","https://openalex.org/W3130948113","https://openalex.org/W4310575853","https://openalex.org/W1491908038","https://openalex.org/W1987634878","https://openalex.org/W2187506573"],"abstract_inverted_index":{"Purpose":[0],"The":[1,184,217],"density":[2,162,201],"peak":[3,202],"clustering":[4,112,181,203,223,242],"algorithm":[5],"(DP)":[6],"is":[7],"proposed":[8],"to":[9,38,104,119,139,171,237],"identify":[10,120],"cluster":[11,47,124,147],"centers":[12,48,78,125],"by":[13,133],"two":[14],"parameters,":[15],"i.e.":[16,225],"\u03c1":[17,35,53],"value":[18,23,54,59],"(local":[19],"density)":[20],"and":[21,29,55,109,163,177,193,212,227],"\u03b4":[22,58],"(the":[24],"distance":[25],"between":[26,231,235],"a":[27,33,51,56,93,131,220],"point":[28,31],"another":[30],"with":[32,74],"higher":[34,52,57],"value).":[36],"According":[37],"the":[39,43,45,68,77,84,89,98,106,111,115,128,135,141,145,158,173,179,210,229,241,245],"center-identifying":[40],"principle":[41,65],"of":[42,88,114,144,244],"DP,":[44],"potential":[46,123,146],"should":[49],"have":[50],"than":[60],"other":[61,213],"points.":[62,100],"However,":[63],"this":[64],"may":[66],"limit":[67],"DP":[69,90,211],"from":[70],"identifying":[71],"some":[72],"categories":[73],"multi-centers":[75],"or":[76],"in":[79],"lower-density":[80],"regions.":[81],"In":[82],"addition,":[83],"improper":[85],"assignment":[86,95],"strategy":[87,138],"could":[91],"cause":[92],"wrong":[94],"result":[96],"for":[97,156],"non-center":[99],"This":[101],"paper":[102],"aims":[103],"address":[105],"aforementioned":[107],"issues":[108],"improve":[110],"performance":[113,243],"DP.":[116,246],"Design/methodology/approach":[117],"First,":[118],"as":[121,126],"many":[122],"possible,":[127],"authors":[129,218],"construct":[130],"point-domain":[132,161],"introducing":[134],"pinhole":[136],"imaging":[137],"extend":[140],"searching":[142],"range":[143],"centers.":[148],"Second,":[149],"they":[150,167],"design":[151],"different":[152],"novel":[153,221],"calculation":[154],"methods":[155],"calculating":[157],"domain":[159,164,169,174],"distance,":[160],"similarity.":[165],"Third,":[166],"adopt":[168],"similarity":[170],"achieve":[172],"merging":[175],"process":[176],"optimize":[178,240],"final":[180],"results.":[182],"Findings":[183],"experimental":[185],"results":[186],"on":[187,205],"analyzing":[188],"12":[189,194],"synthetic":[190],"data":[191,196],"sets":[192,197],"real-world":[195],"show":[198],"that":[199,234],"two-stage":[200],"based":[204],"multi-strategy":[206],"optimization":[207],"(TMsDP)":[208],"outperforms":[209],"state-of-the-art":[214],"algorithms.":[215],"Originality/value":[216],"propose":[219],"DP-based":[222],"method,":[224],"TMsDP,":[226],"transform":[228],"relationship":[230],"points":[232],"into":[233],"domains":[236],"ultimately":[238],"further":[239]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}