{"id":"https://openalex.org/W3210699650","doi":"https://doi.org/10.3233/ida-205340","title":"MD-SPKM: A set pair k-modes clustering algorithm for incomplete categorical matrix data","display_name":"MD-SPKM: A set pair k-modes clustering algorithm for incomplete categorical matrix data","publication_year":2021,"publication_date":"2021-10-29","ids":{"openalex":"https://openalex.org/W3210699650","doi":"https://doi.org/10.3233/ida-205340","mag":"3210699650"},"language":"en","primary_location":{"id":"doi:10.3233/ida-205340","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-205340","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/A5101530010","display_name":"Chunying Zhang","orcid":"https://orcid.org/0000-0003-2721-7018"},"institutions":[{"id":"https://openalex.org/I137506752","display_name":"North China University of Science and Technology","ror":"https://ror.org/04z4wmb81","country_code":"CN","type":"education","lineage":["https://openalex.org/I137506752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunying Zhang","raw_affiliation_strings":["College of Science, North China University of Science and Technology, Tangshan, Hebei, China","Key Laboratory of Data Science and Application of Hebei Province, Tangshan, Hebei, China"],"affiliations":[{"raw_affiliation_string":"College of Science, North China University of Science and Technology, Tangshan, Hebei, China","institution_ids":["https://openalex.org/I137506752"]},{"raw_affiliation_string":"Key Laboratory of Data Science and Application of Hebei Province, Tangshan, Hebei, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006026887","display_name":"Ruiyan Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I137506752","display_name":"North China University of Science and Technology","ror":"https://ror.org/04z4wmb81","country_code":"CN","type":"education","lineage":["https://openalex.org/I137506752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruiyan Gao","raw_affiliation_strings":["College of Science, North China University of Science and Technology, Tangshan, Hebei, China"],"affiliations":[{"raw_affiliation_string":"College of Science, North China University of Science and Technology, Tangshan, Hebei, China","institution_ids":["https://openalex.org/I137506752"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100329212","display_name":"Jiahao Wang","orcid":"https://orcid.org/0000-0001-5891-3070"},"institutions":[{"id":"https://openalex.org/I137506752","display_name":"North China University of Science and Technology","ror":"https://ror.org/04z4wmb81","country_code":"CN","type":"education","lineage":["https://openalex.org/I137506752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahao Wang","raw_affiliation_strings":["College of Science, North China University of Science and Technology, Tangshan, Hebei, China"],"affiliations":[{"raw_affiliation_string":"College of Science, North China University of Science and Technology, Tangshan, Hebei, China","institution_ids":["https://openalex.org/I137506752"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006158306","display_name":"Chen Song","orcid":"https://orcid.org/0000-0003-1918-5052"},"institutions":[{"id":"https://openalex.org/I137506752","display_name":"North China University of Science and Technology","ror":"https://ror.org/04z4wmb81","country_code":"CN","type":"education","lineage":["https://openalex.org/I137506752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Song Chen","raw_affiliation_strings":["College of Science, North China University of Science and Technology, Tangshan, Hebei, China"],"affiliations":[{"raw_affiliation_string":"College of Science, North China University of Science and Technology, Tangshan, Hebei, China","institution_ids":["https://openalex.org/I137506752"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016889877","display_name":"Fengchun Liu","orcid":"https://orcid.org/0000-0002-6374-1557"},"institutions":[{"id":"https://openalex.org/I137506752","display_name":"North China University of Science and Technology","ror":"https://ror.org/04z4wmb81","country_code":"CN","type":"education","lineage":["https://openalex.org/I137506752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fengchun Liu","raw_affiliation_strings":["Qianan College, North China University of Science and Technology, Tangshan, Hebei, China"],"affiliations":[{"raw_affiliation_string":"Qianan College, North China University of Science and Technology, Tangshan, Hebei, China","institution_ids":["https://openalex.org/I137506752"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101434926","display_name":"Jing Ren","orcid":"https://orcid.org/0009-0007-4495-3136"},"institutions":[{"id":"https://openalex.org/I137506752","display_name":"North China University of Science and Technology","ror":"https://ror.org/04z4wmb81","country_code":"CN","type":"education","lineage":["https://openalex.org/I137506752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Ren","raw_affiliation_strings":["College of Science, North China University of Science and Technology, Tangshan, Hebei, China"],"affiliations":[{"raw_affiliation_string":"College of Science, North China University of Science and Technology, Tangshan, Hebei, China","institution_ids":["https://openalex.org/I137506752"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080271448","display_name":"Xiaoze Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I137506752","display_name":"North China University of Science and Technology","ror":"https://ror.org/04z4wmb81","country_code":"CN","type":"education","lineage":["https://openalex.org/I137506752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoze Feng","raw_affiliation_strings":["College of Science, North China University of Science and Technology, Tangshan, Hebei, China"],"affiliations":[{"raw_affiliation_string":"College of Science, North China University of Science and Technology, Tangshan, Hebei, China","institution_ids":["https://openalex.org/I137506752"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5016889877"],"corresponding_institution_ids":["https://openalex.org/I137506752"],"apc_list":null,"apc_paid":null,"fwci":0.7398,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.75790263,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"25","issue":"6","first_page":"1507","last_page":"1524"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9861000180244446,"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/T14392","display_name":"Geoscience and Mining Technology","score":0.9821000099182129,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8353941440582275},{"id":"https://openalex.org/keywords/categorical-variable","display_name":"Categorical variable","score":0.6885620951652527},{"id":"https://openalex.org/keywords/single-linkage-clustering","display_name":"Single-linkage clustering","score":0.6758402585983276},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5958802700042725},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.591853141784668},{"id":"https://openalex.org/keywords/complete-linkage-clustering","display_name":"Complete-linkage clustering","score":0.5813255906105042},{"id":"https://openalex.org/keywords/k-medians-clustering","display_name":"k-medians clustering","score":0.5651347041130066},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5168716907501221},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.5037471652030945},{"id":"https://openalex.org/keywords/determining-the-number-of-clusters-in-a-data-set","display_name":"Determining the number of clusters in a data set","score":0.4843217432498932},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.45998185873031616},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.45910099148750305},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4500364661216736},{"id":"https://openalex.org/keywords/distance-matrix","display_name":"Distance matrix","score":0.41666245460510254},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4139728844165802},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4071398079395294},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.30945640802383423},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1271083950996399}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8353941440582275},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.6885620951652527},{"id":"https://openalex.org/C22648726","wikidata":"https://www.wikidata.org/wiki/Q7523744","display_name":"Single-linkage clustering","level":5,"score":0.6758402585983276},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5958802700042725},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.591853141784668},{"id":"https://openalex.org/C23822008","wikidata":"https://www.wikidata.org/wiki/Q5156437","display_name":"Complete-linkage clustering","level":5,"score":0.5813255906105042},{"id":"https://openalex.org/C115328559","wikidata":"https://www.wikidata.org/wiki/Q4041956","display_name":"k-medians clustering","level":5,"score":0.5651347041130066},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5168716907501221},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.5037471652030945},{"id":"https://openalex.org/C149872217","wikidata":"https://www.wikidata.org/wiki/Q5265701","display_name":"Determining the number of clusters in a data set","level":5,"score":0.4843217432498932},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.45998185873031616},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.45910099148750305},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4500364661216736},{"id":"https://openalex.org/C111208986","wikidata":"https://www.wikidata.org/wiki/Q901698","display_name":"Distance matrix","level":2,"score":0.41666245460510254},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4139728844165802},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4071398079395294},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.30945640802383423},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1271083950996399},{"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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/ida-205340","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-205340","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1803866654","https://openalex.org/W2149230623","https://openalex.org/W2168408108","https://openalex.org/W2257180492","https://openalex.org/W2297889545","https://openalex.org/W2357375775","https://openalex.org/W2404246691","https://openalex.org/W2531336713","https://openalex.org/W2605960758","https://openalex.org/W2772904413","https://openalex.org/W2788485712","https://openalex.org/W2801314826","https://openalex.org/W2892294644","https://openalex.org/W2948387392","https://openalex.org/W2960962270","https://openalex.org/W3005555742","https://openalex.org/W7067674075"],"related_works":["https://openalex.org/W2229552629","https://openalex.org/W2188840951","https://openalex.org/W1481928625","https://openalex.org/W2263992973","https://openalex.org/W2338192130","https://openalex.org/W2308893070","https://openalex.org/W4232307982","https://openalex.org/W2598125667","https://openalex.org/W3092684173","https://openalex.org/W2324024418"],"abstract_inverted_index":{"In":[0],"order":[1],"to":[2,90,96],"solve":[3],"the":[4,16,33,48,69,73,76,78,81,86,93,103,122,134,139],"clustering":[5,27,108,143,156],"problem":[6],"with":[7],"incomplete":[8,62,148],"and":[9,14,21,75,85,101,117,127,153,162],"categorical":[10,149],"matrix":[11,63,150],"data":[12,125,151],"sets,":[13,152],"considering":[15,68],"uncertain":[17,70],"relationship":[18,71],"between":[19,61,72],"samples":[20,64],"clusters,":[22],"a":[23,55],"set":[24,37,56,106,140],"pair":[25,38,57,107,141],"k-modes":[26,44,53,142],"algorithm":[28,144],"is":[29,41,65,99,109],"proposed":[30],"(MD-SPKM).":[31],"Firstly,":[32],"correlation":[34],"theory":[35],"of":[36,51,80,105],"information":[39],"granule":[40],"introduced":[42],"into":[43],"clustering.":[45],"By":[46],"improving":[47],"distance":[49,58,84],"formula":[50,89],"traditional":[52],"algorithm,":[54],"measurement":[59],"method":[60],"defined.":[66],"Secondly,":[67],"sample":[74,94],"cluster,":[77],"definition":[79],"intra-cluster":[82],"average":[83],"threshold":[87],"calculation":[88],"determine":[91],"whether":[92],"belongs":[95],"multiple":[97],"clusters":[98],"given,":[100],"then":[102],"result":[104],"formed,":[110],"which":[111],"includes":[112],"positive":[113],"region,":[114],"boundary":[115],"region":[116],"negative":[118],"region.":[119],"Finally,":[120],"through":[121],"selected":[123],"three":[124],"sets":[126],"four":[128],"contrast":[129],"algorithms":[130],"for":[131],"experimental":[132,135],"evaluation,":[133],"results":[136],"show":[137],"that":[138],"can":[145],"effectively":[146],"handle":[147],"has":[154],"good":[155],"performance":[157],"in":[158],"Accuracy,":[159],"Recall,":[160],"ARI":[161],"NMI.":[163]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}