{"id":"https://openalex.org/W3114527563","doi":"https://doi.org/10.1109/tencon50793.2020.9293922","title":"Unsupervised Clustering based on Feature-value / Instance Transposition Selection","display_name":"Unsupervised Clustering based on Feature-value / Instance Transposition Selection","publication_year":2020,"publication_date":"2020-11-16","ids":{"openalex":"https://openalex.org/W3114527563","doi":"https://doi.org/10.1109/tencon50793.2020.9293922","mag":"3114527563"},"language":"en","primary_location":{"id":"doi:10.1109/tencon50793.2020.9293922","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon50793.2020.9293922","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","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/A5013799882","display_name":"Akira Kusaba","orcid":"https://orcid.org/0000-0002-1296-9180"},"institutions":[{"id":"https://openalex.org/I135598925","display_name":"Kyushu University","ror":"https://ror.org/00p4k0j84","country_code":"JP","type":"education","lineage":["https://openalex.org/I135598925"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Akira Kusaba","raw_affiliation_strings":["Research Institute for Applied Mechanics, Kyushu University, Fukuoka, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Institute for Applied Mechanics, Kyushu University, Fukuoka, Japan","institution_ids":["https://openalex.org/I135598925"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072516978","display_name":"Takako Hashimoto","orcid":"https://orcid.org/0000-0002-7762-8336"},"institutions":[{"id":"https://openalex.org/I46943848","display_name":"Chiba University of Commerce","ror":"https://ror.org/02qn0vb48","country_code":"JP","type":"education","lineage":["https://openalex.org/I46943848"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takako Hashimoto","raw_affiliation_strings":["Commerce and Economics Chiba, University of Commerce, Chiba, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Commerce and Economics Chiba, University of Commerce, Chiba, Japan","institution_ids":["https://openalex.org/I46943848"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039423670","display_name":"Kilho Shin","orcid":"https://orcid.org/0000-0002-0425-8485"},"institutions":[{"id":"https://openalex.org/I45391821","display_name":"Gakushuin University","ror":"https://ror.org/037s2db26","country_code":"JP","type":"education","lineage":["https://openalex.org/I45391821"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kilho Shin","raw_affiliation_strings":["Computer Centre, Gakushuin University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Centre, Gakushuin University, Tokyo, Japan","institution_ids":["https://openalex.org/I45391821"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029804415","display_name":"David Shepard","orcid":null},"institutions":[{"id":"https://openalex.org/I4210099074","display_name":"Evidation Health (United States)","ror":"https://ror.org/00vhpak23","country_code":"US","type":"company","lineage":["https://openalex.org/I4210099074"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Lawrence Shepard","raw_affiliation_strings":["Evidation Health, Los Angeles, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Evidation Health, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I4210099074"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028025312","display_name":"Tetsuji Kuboyama","orcid":"https://orcid.org/0000-0003-1590-0231"},"institutions":[{"id":"https://openalex.org/I45391821","display_name":"Gakushuin University","ror":"https://ror.org/037s2db26","country_code":"JP","type":"education","lineage":["https://openalex.org/I45391821"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tetsuji Kuboyama","raw_affiliation_strings":["Computer Centre, Gakushuin University, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Centre, Gakushuin University, Tokyo, Japan","institution_ids":["https://openalex.org/I45391821"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16845578,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"27","issue":null,"first_page":"1192","last_page":"1197"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9958999752998352,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9941999912261963,"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":0.8086438179016113},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7736638784408569},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6347657442092896},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6233927607536316},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5986062288284302},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.523303747177124},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4713297188282013},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4617922306060791},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4299898147583008},{"id":"https://openalex.org/keywords/transposition","display_name":"Transposition (logic)","score":0.41656994819641113},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36437591910362244}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8086438179016113},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7736638784408569},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6347657442092896},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6233927607536316},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5986062288284302},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.523303747177124},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4713297188282013},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4617922306060791},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4299898147583008},{"id":"https://openalex.org/C12455157","wikidata":"https://www.wikidata.org/wiki/Q7835331","display_name":"Transposition (logic)","level":2,"score":0.41656994819641113},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36437591910362244},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tencon50793.2020.9293922","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon50793.2020.9293922","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8100000023841858,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W120692785","https://openalex.org/W167115076","https://openalex.org/W1560107318","https://openalex.org/W1567888612","https://openalex.org/W1673310716","https://openalex.org/W1880262756","https://openalex.org/W2015489723","https://openalex.org/W2028348615","https://openalex.org/W2063904635","https://openalex.org/W2076219102","https://openalex.org/W2079697937","https://openalex.org/W2084028080","https://openalex.org/W2091693228","https://openalex.org/W2108032102","https://openalex.org/W2128873747","https://openalex.org/W2137958601","https://openalex.org/W2140156026","https://openalex.org/W2149620660","https://openalex.org/W2154053567","https://openalex.org/W2158933803","https://openalex.org/W2167888943","https://openalex.org/W2168332560","https://openalex.org/W2187089797","https://openalex.org/W2519452557","https://openalex.org/W2524602629","https://openalex.org/W2564737579","https://openalex.org/W2724588361","https://openalex.org/W2771838897","https://openalex.org/W2963014045","https://openalex.org/W3011654416","https://openalex.org/W3141396188","https://openalex.org/W6604905834","https://openalex.org/W6606712637","https://openalex.org/W6633497745","https://openalex.org/W6637131181","https://openalex.org/W6639619044","https://openalex.org/W6681822384","https://openalex.org/W6682933812","https://openalex.org/W6684485952","https://openalex.org/W6726954673","https://openalex.org/W6731009841"],"related_works":["https://openalex.org/W2073700517","https://openalex.org/W4288062113","https://openalex.org/W3151485003","https://openalex.org/W2356141215","https://openalex.org/W2361312893","https://openalex.org/W3215624820","https://openalex.org/W4292765704","https://openalex.org/W4207057333","https://openalex.org/W4386564352","https://openalex.org/W2952668426"],"abstract_inverted_index":{"This":[0,134],"paper":[1],"presents":[2],"FITS,":[3],"or":[4],"Feature-value":[5],"/":[6],"Instance":[7],"Transposition":[8],"Selection,":[9],"a":[10,17,50,138,166],"method":[11,140,152],"for":[12,90],"unsupervised":[13,25],"clustering.":[14],"FITS":[15,36,76],"is":[16,110,121,153,173],"tractable,":[18],"explicable":[19],"clustering":[20,83,103],"method,":[21],"which":[22],"leverages":[23,77],"the":[24,34,62,70,119,163,176],"feature":[26,65,101,144,171],"value":[27],"selection":[28,72,172],"algorithm":[29],"known":[30],"as":[31],"UFVS":[32,41],"in":[33,84,87,155,175],"literature.":[35],"combines":[37],"repeated":[38],"rounds":[39],"of":[40,45,52,64,92,94,98,126,150,158,170,178],"with":[42],"alternating":[43],"steps":[44],"matrix":[46],"transposition":[47],"to":[48,74],"produce":[49],"set":[51],"homogenous":[53],"clusters":[54],"that":[55],"describe":[56],"data":[57,107,160,183],"well.":[58],"By":[59],"repeatedly":[60],"swapping":[61],"role":[63],"and":[66,68,80,96,118,146],"instance":[67],"applying":[69],"same":[71],"process":[73],"them,":[75],"UFVS's":[78],"speed":[79],"can":[81],"perform":[82],"our":[85],"experiments":[86],"tens":[88],"milliseconds":[89],"datasets":[91],"thousands":[93,97],"features":[95],"instances.We":[99],"performed":[100],"selection-based":[102],"on":[104,142],"two":[105],"real-world":[106],"sets.":[108],"One":[109],"aimed":[111,122],"at":[112,123],"topic":[113],"extraction":[114,145],"from":[115,129],"Twitter":[116,159],"data,":[117],"other":[120,164],"gaining":[124],"awareness":[125],"energy":[127],"conservation":[128],"time-series":[130],"power":[131,181],"consumption":[132,182],"data.":[133],"study":[135],"also":[136],"proposes":[137],"novel":[139],"based":[141],"iterative":[143],"transposition.":[147],"The":[148],"effectiveness":[149],"this":[151],"shown":[154],"an":[156],"application":[157,177],"analysis.":[161,184],"On":[162],"hand,":[165],"more":[167],"straightforward":[168],"use":[169],"adopted":[174],"time":[179],"series":[180]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
