{"id":"https://openalex.org/W3183138758","doi":"https://doi.org/10.1145/3459082","title":"Unsupervised Subspace Extraction via Deep Kernelized Clustering","display_name":"Unsupervised Subspace Extraction via Deep Kernelized Clustering","publication_year":2021,"publication_date":"2021-07-20","ids":{"openalex":"https://openalex.org/W3183138758","doi":"https://doi.org/10.1145/3459082","mag":"3183138758"},"language":"en","primary_location":{"id":"doi:10.1145/3459082","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459082","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","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/A5043362073","display_name":"Gyoung S. Na","orcid":"https://orcid.org/0000-0001-9803-0782"},"institutions":[{"id":"https://openalex.org/I4210151417","display_name":"Korea Research Institute of Chemical Technology","ror":"https://ror.org/043k4kk20","country_code":"KR","type":"facility","lineage":["https://openalex.org/I4210151417"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Gyoung S. Na","raw_affiliation_strings":["Korea Research Institute of Chemical Technology, Gajeong-ro, Yuseong-gu, Daejeon, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-9803-0782","affiliations":[{"raw_affiliation_string":"Korea Research Institute of Chemical Technology, Gajeong-ro, Yuseong-gu, Daejeon, South Korea","institution_ids":["https://openalex.org/I4210151417"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014403909","display_name":"Hyunju Chang","orcid":"https://orcid.org/0000-0001-7241-5342"},"institutions":[{"id":"https://openalex.org/I4210151417","display_name":"Korea Research Institute of Chemical Technology","ror":"https://ror.org/043k4kk20","country_code":"KR","type":"facility","lineage":["https://openalex.org/I4210151417"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyunju Chang","raw_affiliation_strings":["Korea Research Institute of Chemical Technology, Gajeong-ro, Yuseong-gu, Daejeon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Korea Research Institute of Chemical Technology, Gajeong-ro, Yuseong-gu, Daejeon, South Korea","institution_ids":["https://openalex.org/I4210151417"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210151417"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07814536,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"16","issue":"1","first_page":"1","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9997000098228455,"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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9977999925613403,"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/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7000617980957031},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6899118423461914},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.66236811876297},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6486743688583374},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5984879732131958},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5905094146728516},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5792205333709717},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5606644749641418},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5064784288406372},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5023097991943359},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.4637983441352844},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4302999973297119},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.414448618888855},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4008141756057739},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3548964858055115}],"concepts":[{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7000617980957031},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6899118423461914},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.66236811876297},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6486743688583374},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5984879732131958},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5905094146728516},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5792205333709717},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5606644749641418},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5064784288406372},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5023097991943359},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.4637983441352844},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4302999973297119},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.414448618888855},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4008141756057739},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3548964858055115},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3459082","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459082","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G52894611","display_name":null,"funder_award_id":"SI2151\u201010","funder_id":"https://openalex.org/F4320322101","funder_display_name":"Korea Research Institute of Chemical Technology"}],"funders":[{"id":"https://openalex.org/F4320322101","display_name":"Korea Research Institute of Chemical Technology","ror":"https://ror.org/043k4kk20"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W114517082","https://openalex.org/W1487321909","https://openalex.org/W2013108033","https://openalex.org/W2022163189","https://openalex.org/W2070611982","https://openalex.org/W2076063813","https://openalex.org/W2122538988","https://openalex.org/W2123649031","https://openalex.org/W2132655161","https://openalex.org/W2187089797","https://openalex.org/W2216838936","https://openalex.org/W2217442075","https://openalex.org/W2725606191","https://openalex.org/W2791961904","https://openalex.org/W2800292742","https://openalex.org/W2919115771","https://openalex.org/W2963885538","https://openalex.org/W2984353870","https://openalex.org/W2995135701","https://openalex.org/W2997585558","https://openalex.org/W3001998614","https://openalex.org/W3009375285","https://openalex.org/W3023291995","https://openalex.org/W3091418863","https://openalex.org/W3124370183","https://openalex.org/W3125965402"],"related_works":["https://openalex.org/W1995622179","https://openalex.org/W1484111231","https://openalex.org/W4391160746","https://openalex.org/W1552543208","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W1641615907","https://openalex.org/W3089231081","https://openalex.org/W2093956241"],"abstract_inverted_index":{"Feature":[0],"extraction":[1,29,42,60,86,138],"has":[2,30],"been":[3],"widely":[4,38],"studied":[5],"to":[6,20],"find":[7,110],"informative":[8],"latent":[9,54,67],"features":[10],"and":[11,102,122,146],"reduce":[12],"the":[13,21,53,66,119,125,129,132,151],"dimensionality":[14,64,127],"of":[15,65,118,128,140,153],"data.":[16,106],"In":[17,77],"particular,":[18],"due":[19],"difficulty":[22],"in":[23,34],"obtaining":[24],"labeled":[25],"data,":[26],"unsupervised":[27,40,84],"feature":[28,41,55,59,68,85,121,137],"received":[31],"much":[32],"attention":[33],"data":[35,48],"mining.":[36],"However,":[37],"used":[39],"methods":[43,61],"require":[44,62,98],"side":[45,100],"information":[46,101],"about":[47],"or":[49],"rigid":[50,103],"assumptions":[51,104],"on":[52,105],"space.":[56],"Furthermore,":[57,107],"most":[58],"predefined":[63],"space,which":[69],"should":[70],"be":[71],"manually":[72],"tuned":[73],"as":[74],"a":[75,82,111,115],"hyperparameter.":[76],"this":[78],"article,":[79],"we":[80,147],"propose":[81],"new":[83],"method":[87],"called":[88],"Unsupervised":[89],"Subspace":[90],"Extractor":[91],"(":[92],"USE":[93,108,141,154],"),":[94],"which":[95],"does":[96],"not":[97],"any":[99],"can":[109],"subspace":[112,130],"generated":[113],"by":[114],"nonlinear":[116,134],"combination":[117],"input":[120],"automatically":[123],"determine":[124],"optimal":[126],"for":[131,155],"given":[133],"combination.":[135],"The":[136],"process":[139],"is":[142],"well":[143],"justified":[144],"mathematically,":[145],"also":[148],"empirically":[149],"demonstrate":[150],"effectiveness":[152],"several":[156],"benchmark":[157],"datasets.":[158]},"counts_by_year":[],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
