{"id":"https://openalex.org/W4400113722","doi":"https://doi.org/10.1109/mipro60963.2024.10569814","title":"Optimizing Machine Learning Training: A Comparative Study of Storage Types for Efficient Large Dataset Processing","display_name":"Optimizing Machine Learning Training: A Comparative Study of Storage Types for Efficient Large Dataset Processing","publication_year":2024,"publication_date":"2024-05-20","ids":{"openalex":"https://openalex.org/W4400113722","doi":"https://doi.org/10.1109/mipro60963.2024.10569814"},"language":"en","primary_location":{"id":"doi:10.1109/mipro60963.2024.10569814","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/mipro60963.2024.10569814","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 47th MIPRO ICT and Electronics Convention (MIPRO)","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/A5099635529","display_name":"Luka Lasic","orcid":null},"institutions":[{"id":"https://openalex.org/I2799440398","display_name":"Rochester Institute of Technology Croatia","ror":"https://ror.org/03jgxzm03","country_code":"HR","type":"education","lineage":["https://openalex.org/I2799440398"]}],"countries":["HR"],"is_corresponding":true,"raw_author_name":"Luka Lasic","raw_affiliation_strings":["RIT Croatia"],"affiliations":[{"raw_affiliation_string":"RIT Croatia","institution_ids":["https://openalex.org/I2799440398"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037365104","display_name":"Aleksander Radovan","orcid":"https://orcid.org/0000-0001-6905-091X"},"institutions":[{"id":"https://openalex.org/I4210102288","display_name":"Algebra University College","ror":"https://ror.org/019m6wk21","country_code":"HR","type":"education","lineage":["https://openalex.org/I4210102288"]}],"countries":["HR"],"is_corresponding":false,"raw_author_name":"Aleksander Radovan","raw_affiliation_strings":["Algebra University College"],"affiliations":[{"raw_affiliation_string":"Algebra University College","institution_ids":["https://openalex.org/I4210102288"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074812351","display_name":"Branko Mihaljevi\u0107","orcid":"https://orcid.org/0000-0002-2579-7058"},"institutions":[{"id":"https://openalex.org/I2799440398","display_name":"Rochester Institute of Technology Croatia","ror":"https://ror.org/03jgxzm03","country_code":"HR","type":"education","lineage":["https://openalex.org/I2799440398"]}],"countries":["HR"],"is_corresponding":false,"raw_author_name":"Branko Mihaljevi\u0107","raw_affiliation_strings":["RIT Croatia"],"affiliations":[{"raw_affiliation_string":"RIT Croatia","institution_ids":["https://openalex.org/I2799440398"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5099635529"],"corresponding_institution_ids":["https://openalex.org/I2799440398"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.13086496,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2074","last_page":"2078"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.9944999814033508,"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"}},"topics":[{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.9944999814033508,"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"}},{"id":"https://openalex.org/T11181","display_name":"Advanced Data Storage Technologies","score":0.9944999814033508,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/computer-science","display_name":"Computer science","score":0.8345483541488647},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.6544074416160583},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5221890807151794},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.518251895904541},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4321902394294739}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8345483541488647},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.6544074416160583},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5221890807151794},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.518251895904541},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4321902394294739},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mipro60963.2024.10569814","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/mipro60963.2024.10569814","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 47th MIPRO ICT and Electronics Convention (MIPRO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1174071369","https://openalex.org/W1995751017","https://openalex.org/W2064762429","https://openalex.org/W2166629703","https://openalex.org/W2567696826"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"This":[0,57],"research":[1,58,165],"paper":[2],"explores":[3],"various":[4],"storage":[5,32,124,156,178],"types":[6],"suitable":[7],"for":[8,91,110,150],"handling":[9],"large":[10],"datasets":[11,54,99],"within":[12],"machine":[13,45,77,151,189],"learning":[14,46,78,152,190],"projects.":[15],"The":[16,88,119],"study":[17],"focuses":[18],"on":[19,27,130],"a":[20,131,169],"comparison":[21],"of":[22,44,50,68,85,98,100,104,114,134,146,163,188],"performance":[23],"metrics,":[24],"specifically":[25],"focusing":[26],"the":[28,42,48,65,72,83,96,123,135,144,147,161,175,183],"read":[29,105,116],"operations":[30],"from":[31],"employing":[33],"textual":[34],"files,":[35],"relational":[36],"databases,":[37],"and":[38,112,186],"NoSQL":[39],"databases.":[40],"In":[41],"realm":[43],"projects,":[47],"significance":[49],"efficiently":[51],"reading":[52],"extensive":[53],"is":[55,80],"vital.":[56],"seeks":[59],"to":[60,64,75,82,128,167,173,182],"describe":[61],"alternative":[62],"approaches":[63],"varying":[66],"sizes":[67],"datasets,":[69],"recognizing":[70],"that":[71,122],"time":[73],"required":[74],"train":[76],"models":[79],"related":[81,172],"efficiency":[84,185],"data":[86],"retrieval.":[87],"methodology":[89],"employed":[90],"this":[92,164],"comparative":[93],"analysis":[94],"encompasses":[95],"utilization":[97],"different":[101],"sizes,":[102],"measurement":[103],"operation":[106,117],"durations,":[107],"iterative":[108],"measurements":[109],"precision,":[111],"computation":[113],"average":[115],"durations.":[118],"results":[120,162],"show":[121],"type":[125],"decisions":[126],"need":[127],"depend":[129],"specific":[132],"size":[133],"dataset,":[136],"as":[137,139],"well":[138],"certain":[140],"characteristics,":[141],"thereby":[142,180],"optimizing":[143],"length":[145],"training":[148],"process":[149],"models.":[153],"By":[154],"aligning":[155],"choices":[157],"with":[158],"dataset":[159,177],"dimensions,":[160],"help":[166],"make":[168],"better":[170],"decision":[171],"choosing":[174],"right":[176],"type,":[179],"contributing":[181],"overall":[184],"efficacy":[187],"systems.":[191]},"counts_by_year":[],"updated_date":"2025-12-19T19:40:27.379048","created_date":"2025-10-10T00:00:00"}
