{"id":"https://openalex.org/W4394586591","doi":"https://doi.org/10.1109/iske60036.2023.10481254","title":"Enhanced Density Clustering Based on Density Decay Structure and Spectral Clustering","display_name":"Enhanced Density Clustering Based on Density Decay Structure and Spectral Clustering","publication_year":2023,"publication_date":"2023-11-17","ids":{"openalex":"https://openalex.org/W4394586591","doi":"https://doi.org/10.1109/iske60036.2023.10481254"},"language":"en","primary_location":{"id":"doi:10.1109/iske60036.2023.10481254","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iske60036.2023.10481254","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 18th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","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/A5102591019","display_name":"Yutong Ke","orcid":null},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yutong Ke","raw_affiliation_strings":["SWJTU-Leeds Joint School, Southwest Jiaotong University,Chengdu,China","SWJTU-Leeds Joint School, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SWJTU-Leeds Joint School, Southwest Jiaotong University,Chengdu,China","institution_ids":["https://openalex.org/I4800084"]},{"raw_affiliation_string":"SWJTU-Leeds Joint School, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022455662","display_name":"Zhiguo Long","orcid":"https://orcid.org/0000-0002-2714-3453"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiguo Long","raw_affiliation_strings":["School of Computing and Artificial Intelligence, Southwest Jiaotong University,Chengdu,China","School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing and Artificial Intelligence, Southwest Jiaotong University,Chengdu,China","institution_ids":["https://openalex.org/I4800084"]},{"raw_affiliation_string":"School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046157723","display_name":"Hua Meng","orcid":"https://orcid.org/0000-0002-9570-6430"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hua Meng","raw_affiliation_strings":["School of Mathematics, Southwest Jiaotong University,Chengdu,China","School of Mathematics, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics, Southwest Jiaotong University,Chengdu,China","institution_ids":["https://openalex.org/I4800084"]},{"raw_affiliation_string":"School of Mathematics, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4800084"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.44752834,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"111","last_page":"118"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13731","display_name":"Advanced Computing and Algorithms","score":0.8745999932289124,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T13731","display_name":"Advanced Computing and Algorithms","score":0.8745999932289124,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.7814000248908997,"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":0.826575756072998},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.47025975584983826},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.42249977588653564},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2820320129394531}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.826575756072998},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.47025975584983826},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.42249977588653564},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2820320129394531}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iske60036.2023.10481254","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iske60036.2023.10481254","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 18th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.4300000071525574}],"awards":[{"id":"https://openalex.org/G5677524167","display_name":null,"funder_award_id":"2682022ZTPY082,2682023ZTPY027","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G703940693","display_name":null,"funder_award_id":"61806170","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2011430131","https://openalex.org/W2089609272","https://openalex.org/W2121947440","https://openalex.org/W2165835468","https://openalex.org/W2789456849","https://openalex.org/W2950244530","https://openalex.org/W2953618482","https://openalex.org/W2955986943","https://openalex.org/W2964152782","https://openalex.org/W2966530783","https://openalex.org/W3106882279","https://openalex.org/W3121769020","https://openalex.org/W3159363511","https://openalex.org/W3165254886","https://openalex.org/W4224102499","https://openalex.org/W4294311154","https://openalex.org/W4313270572"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W4391913857","https://openalex.org/W1482912984"],"abstract_inverted_index":{"Density":[0],"Peak":[1],"Clustering":[2],"(DPC)":[3],"has":[4],"attracted":[5],"considerable":[6],"attention":[7],"and":[8,48,126,154,160,175,184],"many":[9],"improving":[10],"variants":[11,17],"have":[12,19],"been":[13],"proposed.":[14],"However,":[15],"these":[16,53],"still":[18],"some":[20,185],"limitations,":[21,54],"such":[22],"as":[23,105,116],"the":[24,33,42,58,64,70,92,119,122,152,158,169,197],"inability":[25],"to":[26,39,63,76,89,114,141,149,195],"handle":[27],"data":[28,68,104,159],"with":[29,80],"large":[30],"density":[31,59,82,100],"differences,":[32],"frequent":[34],"use":[35],"of":[36,45,66,69,96,121,138,157,186,199],"hierarchical":[37,139],"clustering":[38,136,140,171,182],"combine":[40,142],"subclusters,":[41],"imperfect":[43],"consideration":[44],"global":[46,155],"structure,":[47,124],"low":[49],"efficiency.":[50,162],"To":[51],"overcome":[52],"by":[55],"observing":[56],"that":[57,168],"decay":[60,83,101],"phenomenon":[61],"conforms":[62],"characteristics":[65,120],"most":[67],"same":[71],"class,":[72],"this":[73],"paper":[74],"proposes":[75],"identify":[77],"sub":[78,106,143],"clusters":[79,144],"a":[81,86,110,117,146],"structure":[84,156],"in":[85,94,103,129,145],"nearest-neighbor":[87],"range,":[88],"better":[90,150],"reflect":[91],"differences":[93],"den-sities":[95],"data.":[97],"By":[98],"considering":[99],"structures":[102],"clusters,":[107],"we":[108,133,191],"exploit":[109],"sophisticated":[111],"similarity":[112],"measure":[113],"consider":[115],"whole":[118],"overall":[123],"distribution,":[125],"core":[127],"points":[128],"each":[130],"subcluster.":[131],"Finally,":[132],"apply":[134],"spectral":[135,181],"instead":[137],"one-shot":[147],"manner,":[148],"balance":[151],"local":[153],"improve":[161],"Experiments":[163],"on":[164],"real-world":[165],"datasets":[166],"demonstrate":[167],"proposed":[170,200],"algorithm":[172],"performs":[173],"well":[174],"out-performs":[176],"existing":[177],"methods,":[178],"including":[179],"DPC,":[180],"algorithms,":[183],"their":[187],"latest":[188],"variants.":[189],"Additionally,":[190],"conducted":[192],"ablation":[193],"experiments":[194],"verify":[196],"necessity":[198],"components.":[201]},"counts_by_year":[],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}