{"id":"https://openalex.org/W4390401824","doi":"https://doi.org/10.1109/itnac59571.2023.10368569","title":"CaliProb: Probability-based Calibration Model for Robust Predictions in Environments with Data Biases","display_name":"CaliProb: Probability-based Calibration Model for Robust Predictions in Environments with Data Biases","publication_year":2023,"publication_date":"2023-11-29","ids":{"openalex":"https://openalex.org/W4390401824","doi":"https://doi.org/10.1109/itnac59571.2023.10368569"},"language":"en","primary_location":{"id":"doi:10.1109/itnac59571.2023.10368569","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/itnac59571.2023.10368569","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 33rd International Telecommunication Networks and Applications Conference","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/A5113083982","display_name":"Yu-Ran Jeon","orcid":null},"institutions":[{"id":"https://openalex.org/I165677929","display_name":"Sungshin Women's University","ror":"https://ror.org/0500xzf72","country_code":"KR","type":"education","lineage":["https://openalex.org/I165677929"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Yu-Ran Jeon","raw_affiliation_strings":["Sungshin Women's University,Department of Future Convergence Technology Engineering,Seoul,Korea"],"affiliations":[{"raw_affiliation_string":"Sungshin Women's University,Department of Future Convergence Technology Engineering,Seoul,Korea","institution_ids":["https://openalex.org/I165677929"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102413542","display_name":"Jung-Hwa Ryu","orcid":null},"institutions":[{"id":"https://openalex.org/I165677929","display_name":"Sungshin Women's University","ror":"https://ror.org/0500xzf72","country_code":"KR","type":"education","lineage":["https://openalex.org/I165677929"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jung-Hwa Ryu","raw_affiliation_strings":["Sungshin Women's University,Department of Future Convergence Technology Engineering,Seoul,Korea"],"affiliations":[{"raw_affiliation_string":"Sungshin Women's University,Department of Future Convergence Technology Engineering,Seoul,Korea","institution_ids":["https://openalex.org/I165677929"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100350562","display_name":"Soyeon Kim","orcid":"https://orcid.org/0000-0001-7049-9191"},"institutions":[{"id":"https://openalex.org/I165677929","display_name":"Sungshin Women's University","ror":"https://ror.org/0500xzf72","country_code":"KR","type":"education","lineage":["https://openalex.org/I165677929"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"So-Yeon Kim","raw_affiliation_strings":["Sungshin Women's University,Department of Future Convergence Technology Engineering,Seoul,Korea"],"affiliations":[{"raw_affiliation_string":"Sungshin Women's University,Department of Future Convergence Technology Engineering,Seoul,Korea","institution_ids":["https://openalex.org/I165677929"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058838577","display_name":"Na-Eun Park","orcid":"https://orcid.org/0009-0008-0939-5762"},"institutions":[{"id":"https://openalex.org/I165677929","display_name":"Sungshin Women's University","ror":"https://ror.org/0500xzf72","country_code":"KR","type":"education","lineage":["https://openalex.org/I165677929"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Na-Eun Park","raw_affiliation_strings":["Sungshin Women's University,Department of Future Convergence Technology Engineering,Seoul,Korea"],"affiliations":[{"raw_affiliation_string":"Sungshin Women's University,Department of Future Convergence Technology Engineering,Seoul,Korea","institution_ids":["https://openalex.org/I165677929"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070969150","display_name":"Il-Gu Lee","orcid":"https://orcid.org/0000-0002-5777-4029"},"institutions":[{"id":"https://openalex.org/I165677929","display_name":"Sungshin Women's University","ror":"https://ror.org/0500xzf72","country_code":"KR","type":"education","lineage":["https://openalex.org/I165677929"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Il-Gu Lee","raw_affiliation_strings":["Sungshin Women's University,Department of Future Convergence Technology Engineering and Convergence Security Engineering,Seoul,Korea"],"affiliations":[{"raw_affiliation_string":"Sungshin Women's University,Department of Future Convergence Technology Engineering and Convergence Security Engineering,Seoul,Korea","institution_ids":["https://openalex.org/I165677929"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5113083982"],"corresponding_institution_ids":["https://openalex.org/I165677929"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21437906,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"70","last_page":"75"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9850000143051147,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9850000143051147,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9671000242233276,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.96670001745224,"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/overfitting","display_name":"Overfitting","score":0.8676938414573669},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6828160881996155},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.6604421138763428},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.547168493270874},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5467097759246826},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4537343382835388},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.44679003953933716},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4105570912361145},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38088735938072205},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.27404657006263733},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.16368171572685242},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13780620694160461}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8676938414573669},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6828160881996155},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.6604421138763428},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.547168493270874},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5467097759246826},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4537343382835388},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.44679003953933716},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4105570912361145},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38088735938072205},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.27404657006263733},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.16368171572685242},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13780620694160461},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itnac59571.2023.10368569","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/itnac59571.2023.10368569","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 33rd International Telecommunication Networks and Applications Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322064","display_name":"Korea Institute for Advancement of Technology","ror":"https://ror.org/015w1qa96"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2911884683","https://openalex.org/W2963933775","https://openalex.org/W3031198949","https://openalex.org/W3032338640","https://openalex.org/W3095711016","https://openalex.org/W3136169814","https://openalex.org/W3136993381","https://openalex.org/W3192807145","https://openalex.org/W4228999433","https://openalex.org/W4281692184","https://openalex.org/W4284685167","https://openalex.org/W4306850149","https://openalex.org/W4312231739","https://openalex.org/W4324067490","https://openalex.org/W4361799734","https://openalex.org/W6757904846"],"related_works":["https://openalex.org/W2991587282","https://openalex.org/W4288018740","https://openalex.org/W3008919350","https://openalex.org/W2989490741","https://openalex.org/W3092506759","https://openalex.org/W2367545121","https://openalex.org/W4248881655","https://openalex.org/W2482165163","https://openalex.org/W3010890513","https://openalex.org/W120741642"],"abstract_inverted_index":{"Various":[0],"studies":[1],"have":[2,15,41],"focused":[3,17],"on":[4,18],"solving":[5],"data":[6,19,24,48,83,92,128,141,171,193],"bias":[7,57,93,142],"problems":[8],"in":[9,67,81,165,188],"artificial":[10],"intelligence.":[11],"However,":[12,34],"conventional":[13],"approaches":[14],"primarily":[16],"biases":[20,38,172],"originating":[21],"from":[22],"imbalanced":[23],"distributions":[25],"between":[26,39],"sensor":[27],"nodes":[28],"and":[29,63,74,138,169,173],"algorithms":[30],"owing":[31],"to":[32,60,97],"overfitting.":[33],"methods":[35,70],"handling":[36],"the":[37,68,75,103,110,118,127,130,135,140,150,161,185],"sensors":[40],"rarely":[42],"been":[43],"considered.":[44],"In":[45,85,106],"general,":[46],"when":[47],"are":[49],"trained":[50],"using":[51,143],"multiple":[52],"heterogeneous":[53],"devices,":[54,79],"a":[55,82,91,98,189],"device":[56,73,99],"occurs":[58],"due":[59,96],"process,":[61],"voltage,":[62],"temperature":[64],"variations,":[65],"differences":[66],"preprocessing":[69],"for":[71,121],"each":[72,122],"aging":[76],"of":[77,124,160,184],"specific":[78],"resulting":[80],"bias.":[84,194],"this":[86],"study,":[87],"we":[88,108],"prove":[89],"that":[90,159,177,183],"can":[94],"occur":[95],"bias,":[100],"which":[101],"deteriorates":[102],"training":[104,132],"performance.":[105],"response,":[107],"propose":[109],"probability-based":[111],"calibration":[112],"(CaliProb)":[113],"model.":[114,152],"This":[115],"model":[116,164,187],"compares":[117],"predicted":[119],"probabilities":[120],"piece":[123],"data,":[125,137],"selects":[126],"with":[129,167,191],"best":[131],"performance":[133],"as":[134],"reference":[136,145],"calibrates":[139],"these":[144],"data.":[146],"We":[147],"experimentally":[148],"verify":[149],"CaliProb":[151],"It":[153],"exhibits":[154],"an":[155,175],"accuracy":[156,176],"greater":[157],"than":[158,182],"uncalibrated":[162],"general":[163],"situations":[166],"low":[168],"high":[170],"achieves":[174],"is":[178],"approximately":[179],"12.2%":[180],"higher":[181],"Non-calibrated":[186],"case":[190],"abundant":[192]},"counts_by_year":[],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}