{"id":"https://openalex.org/W2530976809","doi":"https://doi.org/10.3233/jifs-169102","title":"Adaptive cutoff distance: Clustering by fast search and find of density peaks","display_name":"Adaptive cutoff distance: Clustering by fast search and find of density peaks","publication_year":2016,"publication_date":"2016-10-14","ids":{"openalex":"https://openalex.org/W2530976809","doi":"https://doi.org/10.3233/jifs-169102","mag":"2530976809"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-169102","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-169102","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"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":"Journal of Intelligent & Fuzzy Systems","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/A5042681178","display_name":"Rashid Mehmood","orcid":"https://orcid.org/0000-0002-3488-9413"},"institutions":[{"id":"https://openalex.org/I1323252656","display_name":"Information Technology University","ror":"https://ror.org/00ngv8j44","country_code":"PK","type":"education","lineage":["https://openalex.org/I1323252656"]},{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN","PK"],"is_corresponding":false,"raw_author_name":"Rashid Mehmood","raw_affiliation_strings":["College of Information Science and Technology, Beijing Normal University, Beijing, China","Department of Computer Science and Information Technology, University of Management Sciences and Information Technology, Kotli, AJK, Pakistan"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]},{"raw_affiliation_string":"Department of Computer Science and Information Technology, University of Management Sciences and Information Technology, Kotli, AJK, Pakistan","institution_ids":["https://openalex.org/I1323252656"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030902303","display_name":"Rongfang Bie","orcid":"https://orcid.org/0000-0002-9971-7698"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Rongfang Bie","raw_affiliation_strings":["College of Information Science and Technology, Beijing Normal University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075825541","display_name":"Libin Jiao","orcid":"https://orcid.org/0000-0001-5285-652X"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Libin Jiao","raw_affiliation_strings":["College of Information Science and Technology, Beijing Normal University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052677801","display_name":"Hussain Dawood","orcid":"https://orcid.org/0000-0003-2653-9541"},"institutions":[{"id":"https://openalex.org/I173207729","display_name":"University of Engineering and Technology Taxila","ror":"https://ror.org/03v00ka07","country_code":"PK","type":"education","lineage":["https://openalex.org/I173207729"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Hussain Dawood","raw_affiliation_strings":["Department of Computer Engineering, University of Engineering and Technology, Taxila, Pakistan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, University of Engineering and Technology, Taxila, Pakistan","institution_ids":["https://openalex.org/I173207729"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023255538","display_name":"Yunchun Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunchun Sun","raw_affiliation_strings":["Business School, Beijing Normal University, Beijing, China","Fax: +86 10 58807938","E-mail:"],"affiliations":[{"raw_affiliation_string":"Business School, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]},{"raw_affiliation_string":"Fax: +86 10 58807938","institution_ids":[]},{"raw_affiliation_string":"E-mail:","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5030902303"],"corresponding_institution_ids":["https://openalex.org/I25254941"],"apc_list":null,"apc_paid":null,"fwci":2.9993,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.92928327,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"31","issue":"5","first_page":"2619","last_page":"2628"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9991999864578247,"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":0.9991999864578247,"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9932000041007996,"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/T10057","display_name":"Face and Expression Recognition","score":0.9918000102043152,"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/cluster-analysis","display_name":"Cluster analysis","score":0.8292771577835083},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7475745677947998},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.6467186212539673},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6455981135368347},{"id":"https://openalex.org/keywords/cutoff","display_name":"Cutoff","score":0.5842961668968201},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5817632675170898},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5402272939682007},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4478708505630493},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35383957624435425},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3375973105430603},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2596780061721802},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.22934365272521973},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07995504140853882}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8292771577835083},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7475745677947998},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.6467186212539673},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6455981135368347},{"id":"https://openalex.org/C2778217198","wikidata":"https://www.wikidata.org/wiki/Q556977","display_name":"Cutoff","level":2,"score":0.5842961668968201},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5817632675170898},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5402272939682007},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4478708505630493},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35383957624435425},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3375973105430603},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2596780061721802},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.22934365272521973},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07995504140853882},{"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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:10.3233/jifs-169102","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-169102","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"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":"Journal of Intelligent & Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6800000071525574}],"awards":[],"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":57,"referenced_works":["https://openalex.org/W78652687","https://openalex.org/W185333964","https://openalex.org/W204885769","https://openalex.org/W1487619820","https://openalex.org/W1489950266","https://openalex.org/W1559168694","https://openalex.org/W1673310716","https://openalex.org/W1841961408","https://openalex.org/W1965351978","https://openalex.org/W1967979390","https://openalex.org/W1970964752","https://openalex.org/W1971022913","https://openalex.org/W1972969203","https://openalex.org/W1983908352","https://openalex.org/W1985822472","https://openalex.org/W2000738254","https://openalex.org/W2000888069","https://openalex.org/W2014268383","https://openalex.org/W2022686119","https://openalex.org/W2047186200","https://openalex.org/W2052560264","https://openalex.org/W2058226207","https://openalex.org/W2074841815","https://openalex.org/W2079296583","https://openalex.org/W2085593730","https://openalex.org/W2089413639","https://openalex.org/W2101234009","https://openalex.org/W2103384206","https://openalex.org/W2109890799","https://openalex.org/W2120438042","https://openalex.org/W2125464731","https://openalex.org/W2127218421","https://openalex.org/W2128255537","https://openalex.org/W2130473611","https://openalex.org/W2145773134","https://openalex.org/W2153268908","https://openalex.org/W2153464267","https://openalex.org/W2164500538","https://openalex.org/W2165232124","https://openalex.org/W2165835468","https://openalex.org/W2169789030","https://openalex.org/W2170955556","https://openalex.org/W2216180200","https://openalex.org/W2233864206","https://openalex.org/W2234184493","https://openalex.org/W2288572574","https://openalex.org/W2295256067","https://openalex.org/W2295884465","https://openalex.org/W2314379296","https://openalex.org/W2415890883","https://openalex.org/W2964318036","https://openalex.org/W3012821532","https://openalex.org/W3104298728","https://openalex.org/W4235675433","https://openalex.org/W4254229595","https://openalex.org/W4285719527","https://openalex.org/W6675354045"],"related_works":["https://openalex.org/W3092388660","https://openalex.org/W2378211422","https://openalex.org/W1986953345","https://openalex.org/W2328322229","https://openalex.org/W3175879137","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W2119262383","https://openalex.org/W972276598","https://openalex.org/W2086519370"],"abstract_inverted_index":{"Clustering":[0],"by":[1,15,100],"fast":[2],"search":[3],"and":[4,35,140,169,200],"find":[5],"of":[6,51,70,104,125,133,144,171],"density":[7,69,124],"peaks":[8],"(CFSFDP)":[9],"was":[10],"proposed":[11,183],"to":[12,66,79,94,121,159,193],"create":[13],"clusters":[14,47,190],"finding":[16],"high-density":[17],"peaks,":[18],"quickly.":[19],"CFSFDP":[20,52],"mainly":[21],"based":[22,165],"on":[23,135,150,166,177],"two":[24],"rules:":[25],"1)":[26],"a":[27,31,37,42,77,131],"cluster":[28,38],"center":[29,39],"has":[30],"high":[32],"dense":[33],"point":[34],"2)":[36],"lies":[40],"at":[41],"large":[43],"distance":[44,58],"from":[45],"other":[46],"centers.":[48],"The":[49,146,174],"effectiveness":[50],"highly":[53],"depends":[54],"upon":[55],"the":[56,68,81,96,102,115,154,167,172,182,194],"cutoff":[57],"(":[59],"C":[60,83,98,119,185],"d":[61,84,99,120,186],"),":[62],"which":[63],"is":[64,76],"used":[65,158],"estimate":[67,95],"each":[71,126],"data":[72,127],"point.":[73,128],"However,":[74],"there":[75],"need":[78],"provide":[80],"predefined":[82],".":[85],"In":[86],"this":[87],"paper,":[88],"we":[89],"propose":[90],"an":[91],"adaptive":[92,184],"way":[93],"accurate":[97,123],"using":[101],"characteristics":[103],"Improved":[105],"Sheather-Jones":[106],"(ISJ)":[107],"method":[108,113,187],"named":[109],"as":[110,191],"IJS-CFSFDP.":[111],"ISJ":[112],"provides":[114],"best":[116],"estimation":[117],"for":[118],"measure":[122],"We":[129],"perform":[130],"number":[132],"experiments":[134],"standard":[136],"benchmark":[137],"clustering":[138,148],"datasets":[139,179],"real":[141],"academic":[142],"dataset":[143,152],"students.":[145],"evaluated":[147],"results":[149,176],"education":[151],"validate":[153],"IJS-CFSFDP":[155],"can":[156],"be":[157],"make":[160],"intelligent":[161],"contents":[162],"delivery":[163],"system":[164],"capability":[168],"intelligence":[170],"student.":[173],"experimental":[175],"synthetic":[178],"show":[180],"that":[181],"creates":[188],"better":[189],"compare":[192],"CFSFDP,":[195],"mean":[196],"shift,":[197],"affinity":[198],"propagation":[199],"k-means.":[201]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":2}],"updated_date":"2026-02-11T14:41:00.668223","created_date":"2025-10-10T00:00:00"}