{"id":"https://openalex.org/W4406459265","doi":"https://doi.org/10.1109/bigdata62323.2024.10825566","title":"EXCON: Extreme Instance-based Contrastive Representation Learning of Severely Imbalanced Multivariate Time Series for Solar Flare Prediction","display_name":"EXCON: Extreme Instance-based Contrastive Representation Learning of Severely Imbalanced Multivariate Time Series for Solar Flare Prediction","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406459265","doi":"https://doi.org/10.1109/bigdata62323.2024.10825566"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825566","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825566","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","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/A5114426778","display_name":"Onur Vural","orcid":null},"institutions":[{"id":"https://openalex.org/I121980950","display_name":"Utah State University","ror":"https://ror.org/00h6set76","country_code":"US","type":"education","lineage":["https://openalex.org/I121980950"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Onur Vural","raw_affiliation_strings":["Utah State University,Department of Computer Science,Logan,UT,USA,84322"],"affiliations":[{"raw_affiliation_string":"Utah State University,Department of Computer Science,Logan,UT,USA,84322","institution_ids":["https://openalex.org/I121980950"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050715780","display_name":"Shah Muhammad Hamdi","orcid":"https://orcid.org/0000-0002-9303-7835"},"institutions":[{"id":"https://openalex.org/I121980950","display_name":"Utah State University","ror":"https://ror.org/00h6set76","country_code":"US","type":"education","lineage":["https://openalex.org/I121980950"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shah Muhammad Hamdi","raw_affiliation_strings":["Utah State University,Department of Computer Science,Logan,UT,USA,84322"],"affiliations":[{"raw_affiliation_string":"Utah State University,Department of Computer Science,Logan,UT,USA,84322","institution_ids":["https://openalex.org/I121980950"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010973892","display_name":"Souka\u00efna Filali Boubrahimi","orcid":"https://orcid.org/0000-0001-5693-6383"},"institutions":[{"id":"https://openalex.org/I121980950","display_name":"Utah State University","ror":"https://ror.org/00h6set76","country_code":"US","type":"education","lineage":["https://openalex.org/I121980950"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Soukaina Filali Boubrahimi","raw_affiliation_strings":["Utah State University,Department of Computer Science,Logan,UT,USA,84322"],"affiliations":[{"raw_affiliation_string":"Utah State University,Department of Computer Science,Logan,UT,USA,84322","institution_ids":["https://openalex.org/I121980950"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5114426778"],"corresponding_institution_ids":["https://openalex.org/I121980950"],"apc_list":null,"apc_paid":null,"fwci":0.7242,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.73594669,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1476","last_page":"1483"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14319","display_name":"Currency Recognition and Detection","score":0.9648000001907349,"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/T14319","display_name":"Currency Recognition and Detection","score":0.9648000001907349,"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/T11059","display_name":"Market Dynamics and Volatility","score":0.9611999988555908,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/solar-flare","display_name":"Solar flare","score":0.6788625121116638},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.642314612865448},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6379328370094299},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.6288658380508423},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.6066206693649292},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5578088164329529},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5409037470817566},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.47990357875823975},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41397541761398315},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.08664727210998535},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.08564165234565735},{"id":"https://openalex.org/keywords/astrophysics","display_name":"Astrophysics","score":0.07887506484985352}],"concepts":[{"id":"https://openalex.org/C185001636","wikidata":"https://www.wikidata.org/wiki/Q119830","display_name":"Solar flare","level":2,"score":0.6788625121116638},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.642314612865448},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6379328370094299},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.6288658380508423},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.6066206693649292},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5578088164329529},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5409037470817566},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.47990357875823975},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41397541761398315},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.08664727210998535},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.08564165234565735},{"id":"https://openalex.org/C44870925","wikidata":"https://www.wikidata.org/wiki/Q37547","display_name":"Astrophysics","level":1,"score":0.07887506484985352},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825566","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825566","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W2010544740","https://openalex.org/W2029038480","https://openalex.org/W2055916162","https://openalex.org/W2093586470","https://openalex.org/W2102042772","https://openalex.org/W2110362175","https://openalex.org/W2187089797","https://openalex.org/W2585090940","https://openalex.org/W2783151135","https://openalex.org/W2783809466","https://openalex.org/W2967988901","https://openalex.org/W2982438846","https://openalex.org/W3041430681","https://openalex.org/W3042807565","https://openalex.org/W3096655658","https://openalex.org/W3102780218","https://openalex.org/W3109603638","https://openalex.org/W3115948762","https://openalex.org/W3136374795","https://openalex.org/W3160088684","https://openalex.org/W3190152617","https://openalex.org/W4210481843","https://openalex.org/W4289360400","https://openalex.org/W4382239668","https://openalex.org/W4390437161","https://openalex.org/W4392904612","https://openalex.org/W4403776755","https://openalex.org/W4403818965","https://openalex.org/W6755529311","https://openalex.org/W6787312032","https://openalex.org/W6860865637","https://openalex.org/W6873381360"],"related_works":["https://openalex.org/W2067443264","https://openalex.org/W31566076","https://openalex.org/W4297902562","https://openalex.org/W2741186499","https://openalex.org/W2804652951","https://openalex.org/W2118640767","https://openalex.org/W2119012848","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"In":[0,48],"heliophysics":[1],"research,":[2],"predicting":[3],"solar":[4,25,30,41,55,93,195,233],"flares":[5,94],"is":[6,71],"crucial":[7],"due":[8],"to":[9,12,39,73,84,107,136,153,162,176,213],"their":[10],"potential":[11],"substantially":[13],"impact":[14],"both":[15,214],"space-based":[16],"systems":[17],"and":[18,157,216,222,236,244,254],"Earth\u2019s":[19],"infrastructure.":[20],"Magnetic":[21],"field":[22],"data":[23],"from":[24,123],"active":[26],"regions,":[27],"recorded":[28],"by":[29],"imaging":[31],"observatories,":[32],"are":[33,95],"transformed":[34],"into":[35],"multivariate":[36,52,66,124,217],"time":[37,53,67,125,218,238],"series":[38,68,126,219,239],"enable":[40],"flare":[42,56,196,234],"prediction":[43,89,197],"using":[44],"temporal":[45,143],"window-based":[46],"analysis.":[47],"the":[49,85,163,182,231],"realm":[50],"of":[51],"series-driven":[54],"prediction,":[57],"addressing":[58],"severe":[59],"class":[60,87,135,204],"imbalance":[61,205],"with":[62,82,147,242],"effective":[63],"strategies":[64],"for":[65,133,166],"representation":[69,103],"learning":[70,104,174],"key":[72],"developing":[74],"robust":[75,167],"predictive":[76],"models.":[77],"Traditional":[78],"methods":[79],"often":[80],"struggle":[81],"overfitting":[83],"majority":[86],"in":[88,181,194,250],"tasks":[90],"where":[91],"major":[92],"infrequent.":[96],"This":[97,199],"work":[98],"presents":[99],"EX-CON,":[100],"a":[101,142,148,160,189,209],"contrastive":[102,131,173],"framework":[105],"designed":[106],"enhance":[108],"classification":[109,224,252],"performance":[110,253],"amidst":[111],"such":[112],"imbalances.":[113],"EXCON":[114],"operates":[115],"through":[116],"four":[117],"stages:":[118],"(1)":[119],"obtaining":[120],"core":[121],"features":[122],"data;":[127],"(2)":[128],"selecting":[129],"distinctive":[130],"representations":[132],"each":[134],"maximize":[137],"inter-class":[138],"separation;":[139],"(3)":[140],"training":[141],"feature":[144,183],"embedding":[145],"module":[146],"custom":[149],"extreme":[150],"reconstruction":[151],"loss":[152],"minimize":[154],"intra-class":[155],"variation;":[156],"(4)":[158],"applying":[159],"classifier":[161],"learned":[164],"embeddings":[165],"classification.":[168],"The":[169],"proposed":[170],"method":[171],"leverages":[172],"principles":[175],"map":[177],"similar":[178],"instances":[179],"closer":[180],"space":[184],"while":[185],"distancing":[186],"dissimilar":[187],"ones,":[188],"strategy":[190],"not":[191,201],"extensively":[192],"explored":[193],"tasks.":[198],"approach":[200],"only":[202],"addresses":[203],"but":[206],"also":[207],"offers":[208],"versatile":[210],"solution":[211],"applicable":[212],"univariate":[215],"across":[220],"binary":[221,243],"multiclass":[223,245],"problems.":[225],"Experimental":[226],"results,":[227],"including":[228],"evaluations":[229],"on":[230],"benchmark":[232],"dataset":[235],"multiple":[237],"archive":[240],"datasets":[241],"labels,":[246],"demonstrate":[247],"EXCON\u2019s":[248],"efficacy":[249],"enhancing":[251],"reducing":[255],"overfitting.":[256]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2025-10-10T00:00:00"}