{"id":"https://openalex.org/W4392254193","doi":"https://doi.org/10.1145/3639479.3639517","title":"An Improved K-PROTOTYPE Clustering Algorithm and Its Application","display_name":"An Improved K-PROTOTYPE Clustering Algorithm and Its Application","publication_year":2023,"publication_date":"2023-12-27","ids":{"openalex":"https://openalex.org/W4392254193","doi":"https://doi.org/10.1145/3639479.3639517"},"language":"en","primary_location":{"id":"doi:10.1145/3639479.3639517","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3639479.3639517","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 6th International Conference on Machine Learning and Natural Language Processing","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/A5063263537","display_name":"\u4fe1\u662d \u81fc\u4e95","orcid":"https://orcid.org/0009-0003-7004-4746"},"institutions":[{"id":"https://openalex.org/I3133083760","display_name":"Sanda University","ror":"https://ror.org/00tp01q71","country_code":"CN","type":"education","lineage":["https://openalex.org/I3133083760"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin Jing","raw_affiliation_strings":["School of Jeneral Education, Shanghai Sanda University, China"],"affiliations":[{"raw_affiliation_string":"School of Jeneral Education, Shanghai Sanda University, China","institution_ids":["https://openalex.org/I3133083760"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074422719","display_name":"Hao Gao","orcid":"https://orcid.org/0009-0003-9872-5877"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hao Gao","raw_affiliation_strings":["SiEn (Qingdao) Integrated Circuits Co., Ltd., China"],"affiliations":[{"raw_affiliation_string":"SiEn (Qingdao) Integrated Circuits Co., Ltd., China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5063263537"],"corresponding_institution_ids":["https://openalex.org/I3133083760"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.41739909,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"182","last_page":"186"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13731","display_name":"Advanced Computing and Algorithms","score":0.7407000064849854,"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":0.7407000064849854,"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/T14025","display_name":"Educational Technology and Assessment","score":0.6730999946594238,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.9343678951263428},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.7050395011901855},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6875113248825073},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.6575783491134644},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.6018840074539185},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5397478342056274},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5189304351806641},{"id":"https://openalex.org/keywords/k-medians-clustering","display_name":"k-medians clustering","score":0.5139052867889404},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.4912695288658142},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.48818808794021606},{"id":"https://openalex.org/keywords/single-linkage-clustering","display_name":"Single-linkage clustering","score":0.4734059274196625},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.42508959770202637},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36723217368125916},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32077956199645996},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1606055200099945}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.9343678951263428},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.7050395011901855},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6875113248825073},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.6575783491134644},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.6018840074539185},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5397478342056274},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5189304351806641},{"id":"https://openalex.org/C115328559","wikidata":"https://www.wikidata.org/wiki/Q4041956","display_name":"k-medians clustering","level":5,"score":0.5139052867889404},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4912695288658142},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.48818808794021606},{"id":"https://openalex.org/C22648726","wikidata":"https://www.wikidata.org/wiki/Q7523744","display_name":"Single-linkage clustering","level":5,"score":0.4734059274196625},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.42508959770202637},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36723217368125916},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32077956199645996},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1606055200099945}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3639479.3639517","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3639479.3639517","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 6th International Conference on Machine Learning and Natural Language Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W2610190296","https://openalex.org/W2767910851","https://openalex.org/W2789701571","https://openalex.org/W2995835451","https://openalex.org/W6605442296"],"related_works":["https://openalex.org/W2559422900","https://openalex.org/W2160785859","https://openalex.org/W3120229345","https://openalex.org/W2374506950","https://openalex.org/W2188840951","https://openalex.org/W2393816671","https://openalex.org/W2358133791","https://openalex.org/W2381835990","https://openalex.org/W4241252752","https://openalex.org/W2358586643"],"abstract_inverted_index":{"The":[0,92,110,151],"K-means":[1],"clustering":[2,71,80,84,108,122,161,179],"algorithm":[3,119,142,158,167],"can":[4,64],"be":[5,65],"used":[6,66,97],"to":[7,25,67,86,98,126,168],"process":[8],"the":[9,27,43,49,60,69,74,83,107,116,128,131,140,155,164,178],"dataset":[10,148],"simply":[11],"and":[12,32,57,143,172,184],"quickly.":[13],"In":[14,124],"this":[15],"paper,":[16],"a":[17,134,147],"weighted":[18,56],"dissimilarity":[19],"measurement":[20,50],"formula":[21],"has":[22,54,120,181],"been":[23,55],"proposed":[24],"address":[26],"issue":[28],"of":[29,46,76,130],"low":[30],"accuracy":[31],"stability":[33],"when":[34],"using":[35,146],"traditional":[36],"K-prototype":[37,118],"algorithms":[38,145],"for":[39,103],"clustering.":[40],"By":[41],"calculating":[42],"aggregation":[44],"degree":[45],"data":[47,171],"attributes,":[48],"distance":[51,62],"between":[52,139],"samples":[53],"calculated.":[58],"And":[59],"maximum-minimum":[61],"method":[63,95],"generate":[68,173],"initial":[70,79],"center,":[72],"avoiding":[73],"possibility":[75],"randomly":[77],"produced":[78],"points":[81],"causing":[82],"results":[85,113,152,180],"fall":[87],"into":[88],"local":[89],"optimal":[90],"results.":[91],"contour":[93],"coefficient":[94],"was":[96,137],"select":[99],"appropriate":[100],"K":[101],"values":[102],"clustering,":[104],"which":[105],"improved":[106,117,132,141,156,165],"effect.":[109],"experimental":[111],"test":[112,136],"show":[114],"that":[115,154],"better":[121,160],"performance.":[123,162],"order":[125],"verify":[127],"effectiveness":[129],"algorithm,":[133],"comparison":[135],"conducted":[138],"other":[144],"from":[149],"UCI.":[150],"showed":[153],"K-Prototype":[157,166],"had":[159],"Using":[163],"cluster":[169],"student":[170,174],"profiles":[175],"by":[176],"analyzing":[177],"certain":[182],"promotion":[183],"application":[185],"significance.":[186]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}