{"id":"https://openalex.org/W3204812266","doi":"https://doi.org/10.1109/tase.2021.3111096","title":"Restricted Relevance Vector Machine for Missing Data and Application to Virtual Metrology","display_name":"Restricted Relevance Vector Machine for Missing Data and Application to Virtual Metrology","publication_year":2021,"publication_date":"2021-10-02","ids":{"openalex":"https://openalex.org/W3204812266","doi":"https://doi.org/10.1109/tase.2021.3111096","mag":"3204812266"},"language":"en","primary_location":{"id":"doi:10.1109/tase.2021.3111096","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2021.3111096","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Automation Science and Engineering","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/A5081790325","display_name":"Jeongsub Choi","orcid":"https://orcid.org/0000-0003-2220-295X"},"institutions":[{"id":"https://openalex.org/I12097938","display_name":"West Virginia University","ror":"https://ror.org/011vxgd24","country_code":"US","type":"education","lineage":["https://openalex.org/I12097938"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Jeongsub Choi","raw_affiliation_strings":["Department of Management Information Systems, West Virginia University, Morgantown, WV, USA"],"affiliations":[{"raw_affiliation_string":"Department of Management Information Systems, West Virginia University, Morgantown, WV, USA","institution_ids":["https://openalex.org/I12097938"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053309949","display_name":"Youngdoo Son","orcid":"https://orcid.org/0000-0002-1912-5853"},"institutions":[{"id":"https://openalex.org/I205490536","display_name":"Dongguk University","ror":"https://ror.org/057q6n778","country_code":"KR","type":"education","lineage":["https://openalex.org/I205490536"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Youngdoo Son","raw_affiliation_strings":["Department of Industrial and Systems Engineering, Dongguk University–Seoul, Seoul, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, Dongguk University–Seoul, Seoul, South Korea","institution_ids":["https://openalex.org/I205490536"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033748503","display_name":"Myong K. Jeong","orcid":"https://orcid.org/0000-0002-4124-5253"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Myong K. Jeong","raw_affiliation_strings":["Department of Industrial and Systems Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ, USA","institution_ids":["https://openalex.org/I102322142"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5081790325"],"corresponding_institution_ids":["https://openalex.org/I12097938"],"apc_list":null,"apc_paid":null,"fwci":0.7538,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.77122064,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"19","issue":"4","first_page":"3172","last_page":"3183"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10188","display_name":"Advanced machining processes and optimization","score":0.989799976348877,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11856","display_name":"Thermography and Photoacoustic Techniques","score":0.9865999817848206,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/relevance-vector-machine","display_name":"Relevance vector machine","score":0.7521668672561646},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.6826375722885132},{"id":"https://openalex.org/keywords/semiconductor-device-fabrication","display_name":"Semiconductor device fabrication","score":0.6509029269218445},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5922608375549316},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.5434759259223938},{"id":"https://openalex.org/keywords/metrology","display_name":"Metrology","score":0.5129820704460144},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5044487714767456},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.492796927690506},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4687661826610565},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4223608374595642},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.3692520260810852},{"id":"https://openalex.org/keywords/wafer","display_name":"Wafer","score":0.2818310260772705},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2726603150367737},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.123078852891922},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09652101993560791}],"concepts":[{"id":"https://openalex.org/C14948415","wikidata":"https://www.wikidata.org/wiki/Q7310972","display_name":"Relevance vector machine","level":3,"score":0.7521668672561646},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.6826375722885132},{"id":"https://openalex.org/C66018809","wikidata":"https://www.wikidata.org/wiki/Q1570432","display_name":"Semiconductor device fabrication","level":3,"score":0.6509029269218445},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5922608375549316},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.5434759259223938},{"id":"https://openalex.org/C195766429","wikidata":"https://www.wikidata.org/wiki/Q394","display_name":"Metrology","level":2,"score":0.5129820704460144},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5044487714767456},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.492796927690506},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4687661826610565},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4223608374595642},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3692520260810852},{"id":"https://openalex.org/C160671074","wikidata":"https://www.wikidata.org/wiki/Q267131","display_name":"Wafer","level":2,"score":0.2818310260772705},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2726603150367737},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.123078852891922},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09652101993560791},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tase.2021.3111096","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2021.3111096","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Automation Science and Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W105168457","https://openalex.org/W129411626","https://openalex.org/W1485082296","https://openalex.org/W1648445109","https://openalex.org/W1930229752","https://openalex.org/W1963944592","https://openalex.org/W1974528911","https://openalex.org/W1983609366","https://openalex.org/W1992329416","https://openalex.org/W1996458756","https://openalex.org/W1997241682","https://openalex.org/W2000651380","https://openalex.org/W2009743662","https://openalex.org/W2012305784","https://openalex.org/W2023084735","https://openalex.org/W2039015671","https://openalex.org/W2044855549","https://openalex.org/W2049633694","https://openalex.org/W2056945148","https://openalex.org/W2072124697","https://openalex.org/W2076922282","https://openalex.org/W2078263418","https://openalex.org/W2082879727","https://openalex.org/W2083653302","https://openalex.org/W2097167237","https://openalex.org/W2104381478","https://openalex.org/W2115896184","https://openalex.org/W2127053344","https://openalex.org/W2131339080","https://openalex.org/W2139833307","https://openalex.org/W2141127927","https://openalex.org/W2143481518","https://openalex.org/W2147973445","https://openalex.org/W2156909104","https://openalex.org/W2162313689","https://openalex.org/W2166774870","https://openalex.org/W2176657689","https://openalex.org/W2226450201","https://openalex.org/W2346456480","https://openalex.org/W2578338006","https://openalex.org/W2594580367","https://openalex.org/W2777729492","https://openalex.org/W2808993481","https://openalex.org/W2811224883","https://openalex.org/W2884425876","https://openalex.org/W2938161931","https://openalex.org/W2978187484","https://openalex.org/W2978430608","https://openalex.org/W3003045510","https://openalex.org/W3004395473","https://openalex.org/W3015790446","https://openalex.org/W3049493925","https://openalex.org/W4211049957","https://openalex.org/W4300187280","https://openalex.org/W6605268666","https://openalex.org/W6636690510","https://openalex.org/W6684942582","https://openalex.org/W6688645734"],"related_works":["https://openalex.org/W3049453136","https://openalex.org/W2541565311","https://openalex.org/W2784019465","https://openalex.org/W4284688182","https://openalex.org/W2994560360","https://openalex.org/W2026561823","https://openalex.org/W4285147743","https://openalex.org/W3136396548","https://openalex.org/W3204812266","https://openalex.org/W2979641641"],"abstract_inverted_index":{"In":[0,77],"semiconductor":[1,44,148],"manufacturing,":[2],"virtual":[3,139],"metrology":[4,140],"(VM)":[5,141],"is":[6,29,183],"a":[7,30,72,82,189,193,198,231,239,249,277],"method":[8,196,241],"of":[9,13,74,233,261],"predicting":[10],"physical":[11],"measurements":[12],"wafer":[14,116,145,167,211,274],"qualities":[15,168,275],"using":[16,105,226],"in-process":[17],"information":[18],"from":[19,48,61,91,111,161],"sensors":[20],"on":[21,144,252],"production":[22,162],"equipment.":[23],"The":[24,118,178],"relevance":[25,179],"vector":[26,180],"machine":[27,34,181],"(RVM)":[28,182],"sparse":[31,190],"Bayesian":[32,194],"kernel":[33,195],"that":[35,86,186,286],"has":[36,142],"been":[37],"widely":[38],"used":[39],"for":[40,66,99,115,154,197,242],"VM":[41],"modeling":[42],"in":[43,147,169,203,210],"manufacturing.":[45],"Missing":[46,201],"values":[47],"equipment":[49,164],"sensors,":[50],"however,":[51,214],"preclude":[52],"training":[53],"an":[54,112,184],"RVM":[55,84,243],"model":[56,75,132,216,234,250,265,278,289,296],"due":[57,150,206],"to":[58,71,95,135,151,174,192,207,222,230,247,280],"missing":[59,128,224],"kernels":[60,68],"incomplete":[62,97,204,245,262,299],"instances.":[63],"Moreover,":[64],"imputation":[65,227],"such":[67],"can":[69,165,187,272],"lead":[70,229],"loss":[73,232],"sparsity.":[76,133,235,283],"this":[78],"work,":[79],"we":[80],"propose":[81],"restricted":[83],"(RRVM)":[85],"selects":[87],"its":[88,152,282],"basis":[89],"functions":[90],"only":[92],"complete":[93],"instances":[94,255,263,300],"handle":[96],"data":[98,107,110,129,176,205,225,246],"VM.":[100],"We":[101],"conduct":[102],"the":[103,121,219,258,268,287],"experiments":[104],"toy":[106],"and":[108,157,218,294],"real-life":[109],"etching":[113],"process":[114,155,163],"fabrication.":[117],"results":[119],"indicate":[120,285],"model\u2019s":[122],"competitive":[123,291],"prediction":[124,199,292],"accuracy":[125],"with":[126,244],"massive":[127],"while":[130],"maintaining":[131],"Note":[134],"Practitioners\u2014In":[136],"recent":[137],"decades,":[138],"focused":[143],"fabrication":[146,212],"manufacturing":[149],"advantages":[153],"monitoring":[156],"automation.":[158],"Typically,":[159],"signals":[160],"predict":[166,273],"VM,":[170],"which":[171],"often":[172],"leads":[173],"high":[175],"dimensionality.":[177],"algorithm":[185],"provide":[188],"solution":[191],"model.":[200],"components":[202,260],"sensor":[208],"failures":[209],"processes,":[213],"hinder":[215],"training,":[217],"existing":[220],"approaches":[221],"handling":[223],"may":[228],"This":[236],"article":[237],"proposes":[238],"new":[240],"train":[248],"built":[251],"fully":[253],"available":[254,259],"by":[256],"incorporating":[257],"into":[264],"training.":[266],"Using":[267],"proposed":[269,288],"method,":[270],"one":[271],"building":[276],"trained":[279],"maintain":[281],"Experiments":[284],"achieves":[290],"performance":[293],"maintains":[295],"sparsity":[297],"when":[298],"are":[301],"used.":[302]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}