{"id":"https://openalex.org/W4367353906","doi":"https://doi.org/10.1109/mis.2023.3255590","title":"Deep Anomaly Analytics: Advancing the Frontier of Anomaly Detection","display_name":"Deep Anomaly Analytics: Advancing the Frontier of Anomaly Detection","publication_year":2023,"publication_date":"2023-03-01","ids":{"openalex":"https://openalex.org/W4367353906","doi":"https://doi.org/10.1109/mis.2023.3255590"},"language":"en","primary_location":{"id":"doi:10.1109/mis.2023.3255590","is_oa":true,"landing_page_url":"https://doi.org/10.1109/mis.2023.3255590","pdf_url":"https://ieeexplore.ieee.org/ielx7/9670/10111508/10111514.pdf","source":{"id":"https://openalex.org/S114241109","display_name":"IEEE Intelligent Systems","issn_l":"1541-1672","issn":["1541-1672","1941-1294"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Intelligent Systems","raw_type":"journal-article"},"type":"editorial","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://ieeexplore.ieee.org/ielx7/9670/10111508/10111514.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089615958","display_name":"Feng Xia","orcid":"https://orcid.org/0000-0002-8324-1859"},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Feng Xia","raw_affiliation_strings":["RMIT University, Melbourne, Australia"],"raw_orcid":"https://orcid.org/0000-0002-8324-1859","affiliations":[{"raw_affiliation_string":"RMIT University, Melbourne, Australia","institution_ids":["https://openalex.org/I82951845"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001634795","display_name":"Leman Akoglu","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Leman Akoglu","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028089542","display_name":"Char\u0173 C. Aggarwal","orcid":"https://orcid.org/0000-0003-2579-7581"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Charu Aggarwal","raw_affiliation_strings":["IBM T.J. Watson Research Center, Yorktown, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM T.J. Watson Research Center, Yorktown, NY, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100338946","display_name":"Huan Liu","orcid":"https://orcid.org/0000-0002-3264-7904"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huan Liu","raw_affiliation_strings":["Arizona State University, Tempe, AZ, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Arizona State University, Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"38","issue":"2","first_page":"32","last_page":"35"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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":1.0,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9995999932289124,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9932000041007996,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.8350770473480225},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.7422121167182922},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6700969934463501},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5710283517837524},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.5709554553031921},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5585106611251831},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5223894715309143},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5181911587715149},{"id":"https://openalex.org/keywords/visual-analytics","display_name":"Visual analytics","score":0.42626655101776123},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40613284707069397},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33837127685546875},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.13716447353363037}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.8350770473480225},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.7422121167182922},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6700969934463501},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5710283517837524},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.5709554553031921},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5585106611251831},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5223894715309143},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5181911587715149},{"id":"https://openalex.org/C59732488","wikidata":"https://www.wikidata.org/wiki/Q2528440","display_name":"Visual analytics","level":3,"score":0.42626655101776123},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40613284707069397},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33837127685546875},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.13716447353363037},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mis.2023.3255590","is_oa":true,"landing_page_url":"https://doi.org/10.1109/mis.2023.3255590","pdf_url":"https://ieeexplore.ieee.org/ielx7/9670/10111508/10111514.pdf","source":{"id":"https://openalex.org/S114241109","display_name":"IEEE Intelligent Systems","issn_l":"1541-1672","issn":["1541-1672","1941-1294"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Intelligent Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/mis.2023.3255590","is_oa":true,"landing_page_url":"https://doi.org/10.1109/mis.2023.3255590","pdf_url":"https://ieeexplore.ieee.org/ielx7/9670/10111508/10111514.pdf","source":{"id":"https://openalex.org/S114241109","display_name":"IEEE Intelligent Systems","issn_l":"1541-1672","issn":["1541-1672","1941-1294"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Intelligent Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.6499999761581421,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4367353906.pdf","grobid_xml":"https://content.openalex.org/works/W4367353906.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W3040266635","https://openalex.org/W3135550350","https://openalex.org/W3155567600","https://openalex.org/W3157999218","https://openalex.org/W3159854664","https://openalex.org/W3170647102","https://openalex.org/W3184778778","https://openalex.org/W3206604724","https://openalex.org/W4210988752","https://openalex.org/W4213224406","https://openalex.org/W4285039484","https://openalex.org/W4308588518","https://openalex.org/W4312460987","https://openalex.org/W4316022164","https://openalex.org/W4319459049","https://openalex.org/W4323065902","https://openalex.org/W4323519386","https://openalex.org/W6839451561"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2667207928","https://openalex.org/W2912112202","https://openalex.org/W4377864969","https://openalex.org/W3120251014"],"abstract_inverted_index":{"Deep":[0,50],"anomaly":[1,25,51,90,102,116,119],"analytics":[2,26,52],"is":[3],"a":[4,106],"rapidly":[5],"evolving":[6],"field":[7,99],"that":[8,44,138],"leverages":[9],"the":[10,35,54,98],"power":[11],"of":[12,23,97,100],"deep":[13,24,89,101],"learning":[14],"to":[15,34,38,48,56,72,134],"identify":[16],"anomalies":[17,40],"in":[18,30,41],"various":[19,58],"datasets.":[20],"The":[21],"use":[22],"has":[27,53],"increased":[28],"significantly":[29],"recent":[31],"years":[32],"due":[33],"growing":[36],"need":[37],"detect":[39,78],"complex":[42],"data":[43],"traditional":[45],"methods":[46],"struggle":[47],"handle.":[49],"potential":[55],"transform":[57],"industries,":[59],"including,":[60],"e.g.,":[61],"healthcare,":[62],"finance,":[63],"and":[64,70,77,104,124],"cybersecurity,":[65],"by":[66],"providing":[67],"valuable":[68],"insights":[69],"helping":[71],"diagnose":[73],"diseases,":[74],"prevent":[75],"fraud,":[76],"cyber":[79],"threats.":[80],"However,":[81],"there":[82],"are":[83],"also":[84],"many":[85],"challenges":[86,109],"associated":[87],"with":[88],"analytics.":[91],"This":[92],"editorial":[93],"provides":[94],"an":[95,132],"overview":[96],"analytics,":[103],"highlights":[105],"few":[107],"key":[108],"facing":[110],"this":[111,135],"field,":[112],"i.e.,":[113],"time":[114],"series":[115],"detection,":[117,120],"graph":[118],"efficiency":[121],"(of":[122],"models),":[123],"solving":[125],"real-world":[126],"problems.":[127],"Additionally,":[128],"it":[129],"serves":[130],"as":[131],"introduction":[133],"special":[136],"issue":[137],"delves":[139],"further":[140],"into":[141],"these":[142],"topics.":[143]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}