{"id":"https://openalex.org/W3104507548","doi":"https://doi.org/10.1109/access.2020.3035461","title":"IEEE Access Special Section Editorial: AI-Driven Big Data Processing: Theory, Methodology, and Applications","display_name":"IEEE Access Special Section Editorial: AI-Driven Big Data Processing: Theory, Methodology, and Applications","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3104507548","doi":"https://doi.org/10.1109/access.2020.3035461","mag":"3104507548"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3035461","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3035461","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09254098.pdf","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://ieeexplore.ieee.org/ielx7/6287639/8948470/09254098.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039812471","display_name":"Zhanyu Ma","orcid":"https://orcid.org/0000-0003-2950-2488"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhanyu Ma","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2950-2488","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100733417","display_name":"Sunwoo Kim","orcid":"https://orcid.org/0000-0002-7055-6587"},"institutions":[{"id":"https://openalex.org/I4575257","display_name":"Hanyang University","ror":"https://ror.org/046865y68","country_code":"KR","type":"education","lineage":["https://openalex.org/I4575257"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sunwoo Kim","raw_affiliation_strings":["Hanyang University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hanyang University, Seoul, South Korea","institution_ids":["https://openalex.org/I4575257"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010346028","display_name":"Pascual Mart\u00ednez-G\u00f3mez","orcid":"https://orcid.org/0000-0002-0098-0534"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pascual Martinez-Gomez","raw_affiliation_strings":["Amazon, Seattle, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Amazon, Seattle, WA, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007791793","display_name":"Jalil Taghia","orcid":"https://orcid.org/0000-0001-8880-1168"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Jalil Taghia","raw_affiliation_strings":["KTH Royal Institute of Technology, Stockholm, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046046128","display_name":"Yi-Zhe Song","orcid":"https://orcid.org/0000-0001-5908-3275"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yi-Zhe Song","raw_affiliation_strings":["University of Surrey, Guildford, U.K"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Surrey, Guildford, U.K","institution_ids":["https://openalex.org/I28290843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068625546","display_name":"Huiji Gao","orcid":"https://orcid.org/0009-0006-0424-248X"},"institutions":[{"id":"https://openalex.org/I1316064682","display_name":"LinkedIn (United States)","ror":"https://ror.org/02fyxhe35","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I1316064682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huiji Gao","raw_affiliation_strings":["LinkedIn, Sunnyvale, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LinkedIn, Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I1316064682"]}]}],"institutions":[],"countries_distinct_count":5,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.1304,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.5659509,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"8","issue":null,"first_page":"199882","last_page":"199898"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.5821999907493591,"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"}},"topics":[{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.5821999907493591,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.5716000199317932,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.5544999837875366,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.8592387437820435},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7950531840324402},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.6107121706008911},{"id":"https://openalex.org/keywords/special-section","display_name":"Special section","score":0.5760776400566101},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5328170657157898},{"id":"https://openalex.org/keywords/data-processing","display_name":"Data processing","score":0.5048354268074036},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46500834822654724},{"id":"https://openalex.org/keywords/the-internet","display_name":"The Internet","score":0.46433699131011963},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4188615083694458},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.18596002459526062},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.18304750323295593},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09700459241867065},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.07706266641616821}],"concepts":[{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.8592387437820435},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7950531840324402},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.6107121706008911},{"id":"https://openalex.org/C2993458768","wikidata":"https://www.wikidata.org/wiki/Q3477549","display_name":"Special section","level":2,"score":0.5760776400566101},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5328170657157898},{"id":"https://openalex.org/C138827492","wikidata":"https://www.wikidata.org/wiki/Q6661985","display_name":"Data processing","level":2,"score":0.5048354268074036},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46500834822654724},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.46433699131011963},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4188615083694458},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.18596002459526062},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.18304750323295593},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09700459241867065},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.07706266641616821},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C61696701","wikidata":"https://www.wikidata.org/wiki/Q770766","display_name":"Engineering physics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3035461","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3035461","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09254098.pdf","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"},{"id":"pmh:oai:doaj.org/article:a1108a7f7db4479ebad66ede5dccf570","is_oa":true,"landing_page_url":"https://doaj.org/article/a1108a7f7db4479ebad66ede5dccf570","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 199882-199898 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3035461","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3035461","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09254098.pdf","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":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.6299999952316284}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3104507548.pdf","grobid_xml":"https://content.openalex.org/works/W3104507548.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4390608645","https://openalex.org/W4247566972","https://openalex.org/W4394895745","https://openalex.org/W2960264696","https://openalex.org/W3090563135","https://openalex.org/W2497432351","https://openalex.org/W4206777497","https://openalex.org/W2910064364","https://openalex.org/W4255224757","https://openalex.org/W2744241569"],"abstract_inverted_index":{"With":[0],"the":[1,15,65,76,108],"rapid":[2],"development":[3,66],"of":[4,67],"network":[5],"infrastructures":[6],"and":[7,19,25,47,87,98,104,110,114],"personal":[8],"electronic":[9],"products,":[10],"big":[11,37,69,89],"data":[12,38,70,90],"generated":[13],"from":[14,107],"Internet,":[16],"sensing":[17],"networks,":[18],"other":[20,119],"equipment":[21],"are":[22],"rapidly":[23],"growing":[24],"have":[26,50],"received":[27],"increasing":[28],"attention":[29],"in":[30,64,91],"recent":[31],"years.":[32],"Recently,":[33],"artificial":[34],"intelligence":[35],"(AI)-driven":[36],"processing":[39],"technologies":[40],"based":[41],"on":[42],"pattern":[43],"recognition,":[44],"machine":[45],"learning,":[46],"deep":[48],"learning":[49],"been":[51],"intensively":[52],"applied":[53],"to":[54,74,82,85,102,112],"dealing":[55],"with":[56],"large-scale":[57],"heterogeneous":[58],"data.":[59],"However,":[60],"challenges":[61],"still":[62],"exist":[63],"AI-driven":[68],"processing.":[71],"In":[72],"order":[73],"meet":[75],"existing":[77],"challenges,":[78],"it":[79],"is":[80,95],"important":[81],"consider":[83],"how":[84,101,111],"analyze":[86],"process":[88],"a":[92],"way":[93],"that":[94],"more":[96],"effective":[97],"reduces":[99],"costs,":[100],"discover":[103],"understand":[105],"knowledge":[106],"data,":[109],"generalize":[113],"transfer":[115],"these":[116],"discoveries":[117],"into":[118],"application":[120],"fields.":[121]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}