{"id":"https://openalex.org/W3119203814","doi":"https://doi.org/10.1145/3427476","title":"Potential Deep Learning Solutions to Persistent and Emerging Big Data Challenges\u2014A Practitioners\u2019 Cookbook","display_name":"Potential Deep Learning Solutions to Persistent and Emerging Big Data Challenges\u2014A Practitioners\u2019 Cookbook","publication_year":2021,"publication_date":"2021-01-02","ids":{"openalex":"https://openalex.org/W3119203814","doi":"https://doi.org/10.1145/3427476","mag":"3119203814"},"language":"en","primary_location":{"id":"doi:10.1145/3427476","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3427476","pdf_url":null,"source":{"id":"https://openalex.org/S157921468","display_name":"ACM Computing Surveys","issn_l":"0360-0300","issn":["0360-0300","1557-7341"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Computing Surveys","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/A5021644642","display_name":"Behroz Mirza","orcid":"https://orcid.org/0000-0003-0899-1526"},"institutions":[{"id":"https://openalex.org/I201384688","display_name":"National University of Computer and Emerging Sciences","ror":"https://ror.org/003eyb898","country_code":"PK","type":"education","lineage":["https://openalex.org/I201384688"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Behroz Mirza","raw_affiliation_strings":["National University of Computer and Emerging Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Computer and Emerging Sciences","institution_ids":["https://openalex.org/I201384688"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004232654","display_name":"Tahir Syed","orcid":"https://orcid.org/0000-0003-0638-9689"},"institutions":[{"id":"https://openalex.org/I4210165529","display_name":"University of Business and Technology","ror":"https://ror.org/05tcr1n44","country_code":"SA","type":"education","lineage":["https://openalex.org/I4210165529"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Tahir Q. Syed","raw_affiliation_strings":["Institute of Business Administration"],"raw_orcid":"https://orcid.org/0000-0003-0638-9689","affiliations":[{"raw_affiliation_string":"Institute of Business Administration","institution_ids":["https://openalex.org/I4210165529"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085502049","display_name":"Behraj Khan","orcid":"https://orcid.org/0000-0003-0985-9543"},"institutions":[{"id":"https://openalex.org/I201384688","display_name":"National University of Computer and Emerging Sciences","ror":"https://ror.org/003eyb898","country_code":"PK","type":"education","lineage":["https://openalex.org/I201384688"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Behraj Khan","raw_affiliation_strings":["National University of Computer and Emerging Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Computer and Emerging Sciences","institution_ids":["https://openalex.org/I201384688"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082500119","display_name":"Yameen Malik","orcid":null},"institutions":[{"id":"https://openalex.org/I4210093985","display_name":"Selected Electronic Technologies (Germany)","ror":"https://ror.org/01eaddk85","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210093985"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Yameen Malik","raw_affiliation_strings":["Seedcode inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Seedcode inc","institution_ids":["https://openalex.org/I4210093985"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.13,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.53936597,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":"54","issue":"1","first_page":"1","last_page":"39"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9993000030517578,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9993000030517578,"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":0.9979000091552734,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9976999759674072,"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/computer-science","display_name":"Computer science","score":0.859213650226593},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.8002508878707886},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7806788086891174},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.69157874584198},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6282094120979309},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5748015642166138},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.49301430583000183},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.43974828720092773},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3521498143672943},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.15728431940078735}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.859213650226593},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.8002508878707886},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7806788086891174},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.69157874584198},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6282094120979309},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5748015642166138},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.49301430583000183},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.43974828720092773},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3521498143672943},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.15728431940078735},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3427476","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3427476","pdf_url":null,"source":{"id":"https://openalex.org/S157921468","display_name":"ACM Computing Surveys","issn_l":"0360-0300","issn":["0360-0300","1557-7341"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Computing Surveys","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6800000071525574,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":99,"referenced_works":["https://openalex.org/W56293434","https://openalex.org/W948663339","https://openalex.org/W1013960042","https://openalex.org/W1492420801","https://openalex.org/W1494137514","https://openalex.org/W1500868819","https://openalex.org/W1516184288","https://openalex.org/W1552248124","https://openalex.org/W1689711448","https://openalex.org/W1892382968","https://openalex.org/W1894514722","https://openalex.org/W1904826605","https://openalex.org/W1954735160","https://openalex.org/W1960364170","https://openalex.org/W1984020445","https://openalex.org/W1994002853","https://openalex.org/W1998092191","https://openalex.org/W2051196068","https://openalex.org/W2068319486","https://openalex.org/W2094426896","https://openalex.org/W2098057602","https://openalex.org/W2109574129","https://openalex.org/W2111072639","https://openalex.org/W2118023920","https://openalex.org/W2120480077","https://openalex.org/W2121971770","https://openalex.org/W2122951085","https://openalex.org/W2134167315","https://openalex.org/W2136114025","https://openalex.org/W2136655611","https://openalex.org/W2138412635","https://openalex.org/W2141350700","https://openalex.org/W2145339207","https://openalex.org/W2145868540","https://openalex.org/W2153353890","https://openalex.org/W2156406284","https://openalex.org/W2158054309","https://openalex.org/W2160648405","https://openalex.org/W2161336914","https://openalex.org/W2163922914","https://openalex.org/W2173213060","https://openalex.org/W2209594346","https://openalex.org/W2238108400","https://openalex.org/W2302101267","https://openalex.org/W2341914330","https://openalex.org/W2344580970","https://openalex.org/W2345132057","https://openalex.org/W2408432900","https://openalex.org/W2549139847","https://openalex.org/W2552464054","https://openalex.org/W2556148058","https://openalex.org/W2576071426","https://openalex.org/W2576683119","https://openalex.org/W2587703207","https://openalex.org/W2592049476","https://openalex.org/W2596142952","https://openalex.org/W2609731728","https://openalex.org/W2611632661","https://openalex.org/W2654252668","https://openalex.org/W2739714724","https://openalex.org/W2750549109","https://openalex.org/W2750947836","https://openalex.org/W2760845379","https://openalex.org/W2763583057","https://openalex.org/W2767547957","https://openalex.org/W2767735117","https://openalex.org/W2778613407","https://openalex.org/W2792014014","https://openalex.org/W2795260399","https://openalex.org/W2798680770","https://openalex.org/W2889526258","https://openalex.org/W2892921685","https://openalex.org/W2898036135","https://openalex.org/W2900922550","https://openalex.org/W2906399906","https://openalex.org/W2912150279","https://openalex.org/W2912213068","https://openalex.org/W2912506132","https://openalex.org/W2912722627","https://openalex.org/W2925804722","https://openalex.org/W2942231644","https://openalex.org/W2947934595","https://openalex.org/W2963770778","https://openalex.org/W2963826396","https://openalex.org/W2964020599","https://openalex.org/W2964248614","https://openalex.org/W2972087877","https://openalex.org/W2982207148","https://openalex.org/W2995191368","https://openalex.org/W2996276196","https://openalex.org/W3004442222","https://openalex.org/W3018357277","https://openalex.org/W3037226137","https://openalex.org/W3049665466","https://openalex.org/W3123554940","https://openalex.org/W4234552385","https://openalex.org/W4242263965","https://openalex.org/W4255466416","https://openalex.org/W4292022450"],"related_works":["https://openalex.org/W2159052453","https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2752972570","https://openalex.org/W4297051394","https://openalex.org/W2734887215","https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W2093324316"],"abstract_inverted_index":{"The":[0,153],"phenomenon":[1],"of":[2,23,62,93,116,135,165,170,177,185],"Big":[3,83,136],"Data":[4,84,137],"continues":[5],"to":[6,43,81,157],"present":[7,69],"moving":[8,32],"targets":[9],"for":[10],"the":[11,20,120,133,149,158,171,175,183],"scientific":[12],"and":[13,39,45,55,59,76,98,101,144,168,181],"technological":[14],"state-of-the-art.":[15],"This":[16,122],"work":[17,123],"demonstrates":[18],"that":[19,110],"solution":[21],"space":[22],"these":[24],"challenges":[25,129],"has":[26],"expanded":[27],"with":[28,53,96],"deep":[29,74,150],"learning":[30,48,52,151],"now":[31],"beyond":[33],"traditional":[34],"applications":[35],"in":[36,148,163,187],"computer":[37],"vision":[38],"natural":[40],"language":[41],"processing":[42],"diverse":[44],"core":[46],"machine":[47],"tasks":[49],"such":[50],"as":[51,79],"streaming":[54],"non-iid-data,":[56],"partial":[57],"supervision,":[58],"large":[60],"volumes":[61],"distributed":[63],"data":[64],"while":[65],"preserving":[66],"privacy.":[67],"We":[68],"a":[70,89,126],"framework":[71],"coalescing":[72],"multiple":[73],"methods":[75],"corresponding":[77],"models":[78],"responses":[80],"specific":[82],"challenges.":[85],"First,":[86],"we":[87,111],"perform":[88],"detailed":[90],"per-challenge":[91],"review":[92],"existing":[94],"techniques,":[95],"benchmarks":[97],"usage":[99],"advice,":[100],"subsequently":[102],"synthesize":[103],"them":[104],"together":[105],"into":[106],"one":[107,117],"organic":[108],"construct":[109],"discover":[112],"principally":[113],"uses":[114],"extensions":[115],"underlying":[118],"model,":[119],"autoencoder.":[121],"therefore":[124],"provides":[125],"synthesis":[127],"where":[128],"at":[130],"scale":[131],"across":[132],"Vs":[134],"could":[138],"be":[139],"addressed":[140],"by":[141],"new":[142],"algorithms":[143],"architectures":[145],"being":[146,155],"proposed":[147,156],"community.":[152],"value":[154],"reader":[159],"from":[160],"either":[161],"community":[162],"terms":[164],"nomenclature,":[166],"concepts,":[167],"techniques":[169],"other":[172],"would":[173],"advance":[174,184],"cause":[176],"multi-disciplinary,":[178],"transversal":[179],"research":[180],"accelerate":[182],"technology":[186],"both":[188],"domains.":[189]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}