{"id":"https://openalex.org/W7123335275","doi":"https://doi.org/10.1109/access.2026.3653624","title":"AUFS-Samba: Adaptive Unsupervised Feature Selection for Mixed Data Type Using Simulated Annealing and Multi-Armed Bandit","display_name":"AUFS-Samba: Adaptive Unsupervised Feature Selection for Mixed Data Type Using Simulated Annealing and Multi-Armed Bandit","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7123335275","doi":"https://doi.org/10.1109/access.2026.3653624"},"language":null,"primary_location":{"id":"doi:10.1109/access.2026.3653624","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3653624","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3653624","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067822209","display_name":"Hasta Pratama","orcid":null},"institutions":[{"id":"https://openalex.org/I134635517","display_name":"Bandung Institute of Technology","ror":"https://ror.org/00apj8t60","country_code":"ID","type":"education","lineage":["https://openalex.org/I134635517"]}],"countries":["ID"],"is_corresponding":true,"raw_author_name":"Hasta Pratama","raw_affiliation_strings":["Doctoral Program of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, Indonesia"],"affiliations":[{"raw_affiliation_string":"Doctoral Program of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, Indonesia","institution_ids":["https://openalex.org/I134635517"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049558335","display_name":"Fetty Fitriyanti Lubis","orcid":"https://orcid.org/0000-0002-0397-9782"},"institutions":[{"id":"https://openalex.org/I134635517","display_name":"Bandung Institute of Technology","ror":"https://ror.org/00apj8t60","country_code":"ID","type":"education","lineage":["https://openalex.org/I134635517"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Fetty Fitriyanti Lubis","raw_affiliation_strings":["School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, Indonesia"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, Indonesia","institution_ids":["https://openalex.org/I134635517"]}]},{"author_position":"last","author":{"id":null,"display_name":"Jaka Sembiring","orcid":null},"institutions":[{"id":"https://openalex.org/I134635517","display_name":"Bandung Institute of Technology","ror":"https://ror.org/00apj8t60","country_code":"ID","type":"education","lineage":["https://openalex.org/I134635517"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Jaka Sembiring","raw_affiliation_strings":["School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, Indonesia"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, Indonesia","institution_ids":["https://openalex.org/I134635517"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5067822209"],"corresponding_institution_ids":["https://openalex.org/I134635517"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09364919,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"8149","last_page":"8173"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.2809999883174896,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.2809999883174896,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.2538999915122986,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.08669999986886978,"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":0.6567999720573425},{"id":"https://openalex.org/keywords/simulated-annealing","display_name":"Simulated annealing","score":0.6464999914169312},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6348000168800354},{"id":"https://openalex.org/keywords/silhouette","display_name":"Silhouette","score":0.6068000197410583},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5547999739646912},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.51419997215271},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.5108000040054321},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.41269999742507935}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7368000149726868},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6567999720573425},{"id":"https://openalex.org/C126980161","wikidata":"https://www.wikidata.org/wiki/Q863783","display_name":"Simulated annealing","level":2,"score":0.6464999914169312},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6348000168800354},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6261000037193298},{"id":"https://openalex.org/C58103923","wikidata":"https://www.wikidata.org/wiki/Q2286025","display_name":"Silhouette","level":2,"score":0.6068000197410583},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5547999739646912},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.51419997215271},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.5108000040054321},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42239999771118164},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41269999742507935},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3871999979019165},{"id":"https://openalex.org/C46714192","wikidata":"https://www.wikidata.org/wiki/Q4680763","display_name":"Adaptive simulated annealing","level":3,"score":0.336899995803833},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.30059999227523804},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.28619998693466187},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2754000127315521},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2660999894142151},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.2583000063896179},{"id":"https://openalex.org/C125014702","wikidata":"https://www.wikidata.org/wiki/Q4680749","display_name":"Adaptive learning","level":2,"score":0.25760000944137573},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2556999921798706}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/access.2026.3653624","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3653624","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3653624","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3653624","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W2077922582","https://openalex.org/W2343420905","https://openalex.org/W2740555475","https://openalex.org/W2791315675","https://openalex.org/W2900404321","https://openalex.org/W2911627187","https://openalex.org/W2986328536","https://openalex.org/W2995624411","https://openalex.org/W3013968491","https://openalex.org/W3015269186","https://openalex.org/W3044085020","https://openalex.org/W3044853528","https://openalex.org/W3082553634","https://openalex.org/W3094858158","https://openalex.org/W3120493664","https://openalex.org/W3139149890","https://openalex.org/W3163012881","https://openalex.org/W3197222752","https://openalex.org/W3197235344","https://openalex.org/W3204294171","https://openalex.org/W3206722405","https://openalex.org/W3212062851","https://openalex.org/W4225550289","https://openalex.org/W4289236186","https://openalex.org/W4294877672","https://openalex.org/W4384525165","https://openalex.org/W4389611930","https://openalex.org/W4389612065","https://openalex.org/W4390278117","https://openalex.org/W4391529596","https://openalex.org/W4402438228","https://openalex.org/W4403980043","https://openalex.org/W4405543960","https://openalex.org/W4406444903","https://openalex.org/W4409364286","https://openalex.org/W4409422765","https://openalex.org/W4411173423"],"related_works":[],"abstract_inverted_index":{"Unsupervised":[0,85],"feature":[1,20,70,197],"selection":[2,60],"(UFS)":[3],"for":[4,137,212],"mixed-type":[5,99,140],"data":[6,29,100,141],"is":[7,127],"challenging":[8],"because":[9],"there":[10],"are":[11],"no":[12],"labels,":[13],"and":[14,41,62,69,91,135,195,204,208,217],"traditional":[15],"methods":[16,57,131],"cannot":[17],"handle":[18],"heterogeneous":[19,77,216],"spaces":[21],"effectively.":[22],"Many":[23],"existing":[24],"approaches":[25],"often":[26],"rely":[27],"on":[28,98,139,174,215],"transformation,":[30],"such":[31,45],"as":[32,46],"encoding":[33],"or":[34],"discretization,":[35],"which":[36,95],"may":[37],"distort":[38],"semantic":[39],"meaning":[40],"cause":[42],"evaluation":[43],"bias,":[44],"the":[47,121,129,162,202],"Bias":[48],"of":[49,123,206],"Criterion":[50],"Values":[51],"to":[52,75,132,156,169],"Dimension":[53],"(BCVD).":[54],"Additionally,":[55],"most":[56],"lack":[58],"adaptive":[59,106],"mechanisms":[61],"do":[63],"not":[64],"jointly":[65],"consider":[66],"clustering":[67,185],"quality":[68,186],"redundancy,":[71],"limiting":[72],"their":[73],"applicability":[74],"real-world":[76,176],"data.":[78,219],"In":[79],"this":[80],"paper,":[81],"we":[82],"propose":[83],"Adaptive":[84],"Feature":[86],"Selection":[87],"using":[88,108],"Simulated":[89,117],"Annealing":[90,118],"Multi-Armed":[92,110],"Bandit":[93,111],"(AUFS-Samba),":[94],"operates":[96],"directly":[97],"without":[101,142],"requiring":[102],"transformation.":[103,143],"AUFS-Samba":[104,126,181,207],"combines":[105],"exploration":[107,155],"a":[109],"(MAB)":[112],"with":[113],"global":[114],"optimization":[115,168],"via":[116],"(SA).":[119],"To":[120],"best":[122],"our":[124],"knowledge,":[125],"among":[128],"first":[130],"combine":[133],"MAB":[134,154],"SA":[136,167],"UFS":[138],"Our":[144],"method":[145],"uses":[146],"entropy-corrected":[147],"k-Most":[148],"Similar":[149],"Neighbor":[150],"Correlation":[151],"(kMSNC)":[152],"during":[153,166],"reduce":[157],"redundancy.":[158],"It":[159],"also":[160],"applies":[161],"Gower-based":[163],"Silhouette":[164],"Score":[165],"improve":[170],"cluster":[171],"coherence.":[172],"Experiments":[173],"eight":[175],"UCI":[177],"datasets":[178],"show":[179],"that":[180],"consistently":[182],"achieves":[183],"higher":[184],"than":[187],"representative":[188],"state-of-the-art":[189],"baselines,":[190],"while":[191],"selecting":[192],"compact,":[193],"interpretable,":[194],"relevant":[196],"subsets.":[198],"These":[199],"findings":[200],"demonstrate":[201],"effectiveness":[203],"robustness":[205],"its":[209],"practical":[210],"potential":[211],"unsupervised":[213],"learning":[214],"unlabeled":[218]},"counts_by_year":[],"updated_date":"2026-03-25T23:56:10.502304","created_date":"2026-01-14T00:00:00"}