{"id":"https://openalex.org/W4226250081","doi":"https://doi.org/10.1109/iske54062.2021.9755344","title":"A Novel Clustering Algorithm via the Support and K-Nearest Neighbors of Data","display_name":"A Novel Clustering Algorithm via the Support and K-Nearest Neighbors of Data","publication_year":2021,"publication_date":"2021-11-26","ids":{"openalex":"https://openalex.org/W4226250081","doi":"https://doi.org/10.1109/iske54062.2021.9755344"},"language":"en","primary_location":{"id":"doi:10.1109/iske54062.2021.9755344","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iske54062.2021.9755344","pdf_url":null,"source":{"id":"https://openalex.org/S4363608381","display_name":"2021 16th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 16th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5103278510","display_name":"Hengshan Zhang","orcid":"https://orcid.org/0000-0003-0364-463X"},"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":"Hengshan Zhang","raw_affiliation_strings":["Xi&#x2019;an University of Posts and Telecommunications,School of Computer Science and Technology,Xi&#x2019;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Posts and Telecommunications,School of Computer Science and Technology,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101771276","display_name":"Xiaoyan Liu","orcid":"https://orcid.org/0000-0002-8848-9220"},"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":"Xiaoyan Liu","raw_affiliation_strings":["Xi&#x2019;an University of Posts and Telecommunications,School of Computer Science and Technology,Xi&#x2019;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Posts and Telecommunications,School of Computer Science and Technology,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027221015","display_name":"Jiaxuan Xu","orcid":"https://orcid.org/0000-0003-0518-506X"},"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":"Jiaxuan Xu","raw_affiliation_strings":["Xi&#x2019;an University of Posts and Telecommunications,School of Computer Science and Technology,Xi&#x2019;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Posts and Telecommunications,School of Computer Science and Technology,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115599660","display_name":"Haoru Li","orcid":"https://orcid.org/0000-0002-9658-3305"},"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":"Haoru Li","raw_affiliation_strings":["Xi&#x2019;an University of Posts and Telecommunications,School of Computer Science and Technology,Xi&#x2019;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Posts and Telecommunications,School of Computer Science and Technology,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100751424","display_name":"Zhongmin Wang","orcid":"https://orcid.org/0000-0003-0870-454X"},"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":"Zhongmin Wang","raw_affiliation_strings":["Xi&#x2019;an University of Posts and Telecommunications,School of Computer Science and Technology,Xi&#x2019;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Posts and Telecommunications,School of Computer Science and Technology,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I4210136859"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100419627","display_name":"Yanping Chen","orcid":"https://orcid.org/0000-0001-6548-6070"},"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":"Yanping Chen","raw_affiliation_strings":["Xi&#x2019;an University of Posts and Telecommunications,School of Computer Science and Technology,Xi&#x2019;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Posts and Telecommunications,School of Computer Science and Technology,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I4210136859"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210136859"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"40 7","issue":null,"first_page":"598","last_page":"603"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9984999895095825,"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":0.9984999895095825,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9970999956130981,"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":0.9930999875068665,"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":0.8622205257415771},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6416745781898499},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5594538450241089},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5501813888549805},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5272616147994995},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.5142773985862732},{"id":"https://openalex.org/keywords/single-linkage-clustering","display_name":"Single-linkage clustering","score":0.5048097372055054},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4734575152397156},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4716431498527527},{"id":"https://openalex.org/keywords/data-point","display_name":"Data point","score":0.47046005725860596},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.46065354347229004},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.42918145656585693},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3992476761341095},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.25989606976509094}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8622205257415771},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6416745781898499},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5594538450241089},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5501813888549805},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5272616147994995},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.5142773985862732},{"id":"https://openalex.org/C22648726","wikidata":"https://www.wikidata.org/wiki/Q7523744","display_name":"Single-linkage clustering","level":5,"score":0.5048097372055054},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4734575152397156},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4716431498527527},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.47046005725860596},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.46065354347229004},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.42918145656585693},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3992476761341095},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25989606976509094},{"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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iske54062.2021.9755344","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iske54062.2021.9755344","pdf_url":null,"source":{"id":"https://openalex.org/S4363608381","display_name":"2021 16th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 16th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W65738273","https://openalex.org/W2035139756","https://openalex.org/W2049758109","https://openalex.org/W2052684427","https://openalex.org/W2059369323","https://openalex.org/W2073459066","https://openalex.org/W2165232124","https://openalex.org/W2563423589","https://openalex.org/W2606436201","https://openalex.org/W2763350515","https://openalex.org/W2789511664","https://openalex.org/W2884662492","https://openalex.org/W2902721797","https://openalex.org/W2951842914","https://openalex.org/W6668990524","https://openalex.org/W6693423202","https://openalex.org/W6730798481","https://openalex.org/W6736268099"],"related_works":["https://openalex.org/W2559422900","https://openalex.org/W2160785859","https://openalex.org/W3120229345","https://openalex.org/W2103650652","https://openalex.org/W2188840951","https://openalex.org/W2171610853","https://openalex.org/W2360225591","https://openalex.org/W2101637161","https://openalex.org/W2342518500","https://openalex.org/W2374506950"],"abstract_inverted_index":{"K-Means":[0],"is":[1,133],"a":[2,38,194],"widely":[3],"used":[4],"algorithm":[5,41,121,166,187],"among":[6,109],"many":[7],"clustering":[8,15,40,152,183,196],"algorithms.":[9],"However,":[10],"in":[11,55],"the":[12,23,43,61,70,79,82,95,99,103,106,110,114,119,124,129,146,150,155,159,165,175,185],"process":[13],"of":[14,25,49,63,72,81,102],"by":[16,153],"K-Means,":[17],"there":[18],"are":[19],"problems,":[20],"such":[21],"as":[22,105,158],"difficulty":[24],"selecting":[26],"K":[27,125],"value,":[28],"high":[29],"parameter":[30],"dependence":[31],"and":[32,45,66,68,91,93,128,169,171,191],"sensitive":[33],"outliers.":[34],"Thus,":[35],"we":[36,59,77,117,144],"propose":[37],"novel":[39],"via":[42],"support":[44,65,104],"K-Nearest":[46],"Neighbors":[47],"(KNN)":[48],"data":[50,64,74,86,96,111,131,177],"to":[51,122],"solve":[52],"these":[53],"problems":[54],"this":[56],"paper.":[57],"Firstly,":[58],"introduce":[60],"concept":[62],"calculate":[67,78],"make":[69],"supports":[71,83],"pair":[73],"sparse.":[75],"Secondly,":[76],"sum":[80,101],"for":[84],"each":[85],"point":[87,97],"with":[88,98,180],"other":[89,181],"points":[90],"select":[92],"consider":[94],"maximum":[100],"cluster":[107],"center":[108],"set.":[112,178],"At":[113],"same":[115],"time,":[116],"use":[118],"KNN":[120],"determine":[123],"value":[126],"selection,":[127],"initial":[130],"set":[132],"divided":[134],"into":[135,149],"M":[136,147],"sub-clusters":[137,148],"(M":[138],"<inf":[139],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[140],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">k</inf>":[141],").":[142],"Then,":[143],"combine":[145],"final":[151],"using":[154],"aggregation":[156],"function":[157],"similarity":[160],"measure.":[161],"When":[162],"processing":[163],"data,":[164],"combines":[167],"density":[168,192],"distance":[170,190],"tests":[172],"it":[173],"on":[174,189],"UCI":[176],"Comparing":[179],"typical":[182],"algorithms,":[184],"hybrid":[186],"based":[188],"has":[193],"better":[195],"effect.":[197]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
