{"id":"https://openalex.org/W4400947773","doi":"https://doi.org/10.1145/3672919.3672969","title":"Designing an Efficient Framework for Large-Scale Data Processing and Analysis Based on Deep Learning Technology","display_name":"Designing an Efficient Framework for Large-Scale Data Processing and Analysis Based on Deep Learning Technology","publication_year":2024,"publication_date":"2024-03-01","ids":{"openalex":"https://openalex.org/W4400947773","doi":"https://doi.org/10.1145/3672919.3672969"},"language":"en","primary_location":{"id":"doi:10.1145/3672919.3672969","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3672919.3672969","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 3rd International Conference on Cyber Security, Artificial Intelligence and Digital Economy","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":null,"display_name":"Qian Liu","orcid":"https://orcid.org/0009-0006-8411-3791"},"institutions":[{"id":"https://openalex.org/I170239107","display_name":"University of South Australia","ror":"https://ror.org/01p93h210","country_code":"AU","type":"education","lineage":["https://openalex.org/I170239107"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Qian Liu","raw_affiliation_strings":["University of South Australia, Australia"],"raw_orcid":"https://orcid.org/0009-0006-8411-3791","affiliations":[{"raw_affiliation_string":"University of South Australia, Australia","institution_ids":["https://openalex.org/I170239107"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036953616","display_name":"Xingda Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I148099405","display_name":"Xi'an University of Architecture and Technology","ror":"https://ror.org/04v2j2k71","country_code":"CN","type":"education","lineage":["https://openalex.org/I148099405"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingda Wang","raw_affiliation_strings":["Xi'an University of Architecture and Technology, China"],"raw_orcid":"https://orcid.org/0009-0002-9931-0887","affiliations":[{"raw_affiliation_string":"Xi'an University of Architecture and Technology, China","institution_ids":["https://openalex.org/I148099405"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I170239107"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09181836,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"269","last_page":"274"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9968000054359436,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9968000054359436,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9775000214576721,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9643999934196472,"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":0.7680848836898804},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5381890535354614},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45907872915267944},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4444180727005005},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3949962854385376}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7680848836898804},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5381890535354614},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45907872915267944},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4444180727005005},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3949962854385376},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3672919.3672969","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3672919.3672969","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 3rd International Conference on Cyber Security, Artificial Intelligence and Digital Economy","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":8,"referenced_works":["https://openalex.org/W2546614363","https://openalex.org/W2784246882","https://openalex.org/W2922086451","https://openalex.org/W2928389720","https://openalex.org/W2947411064","https://openalex.org/W3100321043","https://openalex.org/W3133979803","https://openalex.org/W3134292696"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W3009238340","https://openalex.org/W4321369474","https://openalex.org/W4360585206","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756","https://openalex.org/W4323565446"],"abstract_inverted_index":{"This":[0,128],"paper":[1],"presents":[2],"a":[3,80,136],"comprehensive":[4],"framework":[5,24,76],"designed":[6],"for":[7,124,140,147,153],"the":[8,17,26,33,41,45,117,132],"efficient":[9,138],"processing":[10],"and":[11,35,48,63,68,93,97,109,143],"analysis":[12,108],"of":[13,19,28,37,50],"large-scale":[14,125],"data":[15,38,88,99,126],"through":[16],"integration":[18],"deep":[20,29,56,122,150],"learning":[21,30,57,123,151],"technologies.":[22],"The":[23,75],"leverages":[25],"capabilities":[27],"to":[31,66,131],"enhance":[32],"accuracy":[34,111],"speed":[36],"analysis,":[39],"addressing":[40],"challenges":[42],"posed":[43],"by":[44,134],"sheer":[46],"volume":[47],"complexity":[49],"modern":[51],"datasets.":[52],"It":[53],"incorporates":[54],"advanced":[55],"models,":[58],"including":[59],"convolutional":[60],"neural":[61],"networks":[62],"sparse":[64],"coding,":[65],"extract":[67],"analyze":[69],"features":[70],"from":[71],"large":[72],"datasets":[73],"effectively.":[74],"is":[77],"built":[78],"upon":[79],"robust":[81],"architecture":[82],"that":[83],"integrates":[84],"with":[85],"existing":[86],"big":[87,154],"technologies":[89],"like":[90],"Hadoop,":[91],"Spark,":[92],"TensorFlow,":[94],"facilitating":[95],"scalable":[96],"distributed":[98],"processing.":[100],"Experimental":[101],"results":[102],"demonstrate":[103],"significant":[104],"improvements":[105],"in":[106,120,149],"performance":[107],"prediction":[110],"across":[112],"various":[113],"application":[114],"domains,":[115],"highlighting":[116],"framework's":[118],"effectiveness":[119],"harnessing":[121],"analysis.":[127],"study":[129],"contributes":[130],"field":[133],"proposing":[135],"scalable,":[137],"solution":[139],"data-driven":[141],"decision-making":[142],"opens":[144],"new":[145],"avenues":[146],"research":[148],"applications":[152],"data.":[155]},"counts_by_year":[],"updated_date":"2025-12-22T23:10:17.713674","created_date":"2025-10-10T00:00:00"}