{"id":"https://openalex.org/W2055089253","doi":"https://doi.org/10.1109/ijcnn.2014.6889841","title":"Anomaly detection based on indicators aggregation","display_name":"Anomaly detection based on indicators aggregation","publication_year":2014,"publication_date":"2014-07-01","ids":{"openalex":"https://openalex.org/W2055089253","doi":"https://doi.org/10.1109/ijcnn.2014.6889841","mag":"2055089253"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2014.6889841","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2014.6889841","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1409.4747","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Tsirizo Rabenoro","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165303","display_name":"Safran (France)","ror":"https://ror.org/05sqf9v67","country_code":"FR","type":"company","lineage":["https://openalex.org/I4210165303"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Tsirizo Rabenoro","raw_affiliation_strings":["Health Monitoring Department, Safran Group, Moissy Cramayel, France"],"affiliations":[{"raw_affiliation_string":"Health Monitoring Department, Safran Group, Moissy Cramayel, France","institution_ids":["https://openalex.org/I4210165303"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jerome Lacaille","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165303","display_name":"Safran (France)","ror":"https://ror.org/05sqf9v67","country_code":"FR","type":"company","lineage":["https://openalex.org/I4210165303"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Jerome Lacaille","raw_affiliation_strings":["Health Monitoring Department, Safran Group, Moissy Cramayel, France"],"affiliations":[{"raw_affiliation_string":"Health Monitoring Department, Safran Group, Moissy Cramayel, France","institution_ids":["https://openalex.org/I4210165303"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Marie Cottrell","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162862","display_name":"European Society for Blood and Marrow Transplantation","ror":"https://ror.org/05gkev856","country_code":"FR","type":"nonprofit","lineage":["https://openalex.org/I4210162862"]},{"id":"https://openalex.org/I51101395","display_name":"Universit\u00e9 Paris 1 Panth\u00e9on-Sorbonne","ror":"https://ror.org/002t25c44","country_code":"FR","type":"education","lineage":["https://openalex.org/I51101395"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Marie Cottrell","raw_affiliation_strings":["SAMM (EA 4543), Universite Paris 1, Paris, France"],"affiliations":[{"raw_affiliation_string":"SAMM (EA 4543), Universite Paris 1, Paris, France","institution_ids":["https://openalex.org/I51101395","https://openalex.org/I4210162862"]}]},{"author_position":"last","author":{"id":null,"display_name":"Fabrice Rossi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162862","display_name":"European Society for Blood and Marrow Transplantation","ror":"https://ror.org/05gkev856","country_code":"FR","type":"nonprofit","lineage":["https://openalex.org/I4210162862"]},{"id":"https://openalex.org/I51101395","display_name":"Universit\u00e9 Paris 1 Panth\u00e9on-Sorbonne","ror":"https://ror.org/002t25c44","country_code":"FR","type":"education","lineage":["https://openalex.org/I51101395"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Fabrice Rossi","raw_affiliation_strings":["SAMM (EA 4543), Universite Paris 1, Paris, France"],"affiliations":[{"raw_affiliation_string":"SAMM (EA 4543), Universite Paris 1, Paris, France","institution_ids":["https://openalex.org/I51101395","https://openalex.org/I4210162862"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210165303"],"apc_list":null,"apc_paid":null,"fwci":0.8487,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.81443124,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"6","issue":null,"first_page":"2548","last_page":"2555"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9891999959945679,"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/T12391","display_name":"Artificial Immune Systems Applications","score":0.9757999777793884,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.8144000172615051},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5702999830245972},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5648000240325928},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5037000179290771},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4781999886035919},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.45649999380111694},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.4406999945640564},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4277999997138977},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4189000129699707}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.8144000172615051},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6061000227928162},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5702999830245972},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5648000240325928},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5364999771118164},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5037000179290771},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4781999886035919},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47690001130104065},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.45649999380111694},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.4406999945640564},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4277999997138977},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4189000129699707},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.3882000148296356},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.37560001015663147},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37299999594688416},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.353300005197525},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.3303999900817871},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.3292999863624573},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2994999885559082},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.28790000081062317},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.28360000252723694},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.27489998936653137},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.2728999853134155},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.2662999927997589},{"id":"https://openalex.org/C2775846686","wikidata":"https://www.wikidata.org/wiki/Q643012","display_name":"Condition monitoring","level":2,"score":0.26339998841285706},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.2590000033378601}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/ijcnn.2014.6889841","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2014.6889841","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1409.4747","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1409.4747","pdf_url":"https://arxiv.org/pdf/1409.4747","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:HAL:hal-01064529v1","is_oa":true,"landing_page_url":"https://hal.science/hal-01064529","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"International Joint Conference on Neural Networks (IJCNN 2014), Jul 2014, Beijing, China. pp.2548--2555, ⟨10.1109/IJCNN.2014.6889841⟩","raw_type":"Conference papers"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1409.4747","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1409.4747","pdf_url":"https://arxiv.org/pdf/1409.4747","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1697947569","https://openalex.org/W1941659294","https://openalex.org/W1967981049","https://openalex.org/W2119479037","https://openalex.org/W2122646361","https://openalex.org/W2133099069","https://openalex.org/W2154053567","https://openalex.org/W2325067522","https://openalex.org/W2325682359","https://openalex.org/W2911964244","https://openalex.org/W6682496738"],"related_works":[],"abstract_inverted_index":{"Automatic":[0],"anomaly":[1,24,120,125,161,187],"detection":[2],"is":[3,25,29,99,134,176],"a":[4,78,106,117,149],"major":[5],"issue":[6],"in":[7,33,190],"various":[8],"areas.":[9],"Beyond":[10],"mere":[11],"detection,":[12],"the":[13,16,19,23,31,47,53,58,61,69,139,170,186],"identification":[14],"of":[15,18,42,60,64,93,110,148,185],"source":[17,59],"problem":[20],"that":[21,81],"produced":[22],"also":[26],"essential.":[27],"This":[28,75,153],"particularly":[30],"case":[32],"aircraft":[34],"engine":[35,48],"health":[36],"monitoring":[37,85],"where":[38],"detecting":[39],"early":[40],"signs":[41],"failure":[43],"(anomalies)":[44],"and":[45,90],"helping":[46],"owner":[49],"to":[50,67,72,100,116,136,182],"implement":[51],"efficiently":[52],"adapted":[54],"maintenance":[55],"operations":[56],"(fixing":[57],"anomaly)":[62],"are":[63,144],"crucial":[65],"importance":[66],"reduce":[68],"costs":[70],"attached":[71],"unscheduled":[73],"maintenance.":[74],"paper":[76],"introduces":[77],"general":[79],"methodology":[80,175],"aims":[82],"at":[83,146],"classifying":[84],"signals":[86],"into":[87],"normal":[88],"ones":[89],"several":[91],"classes":[92],"abnormal":[94],"ones.":[95],"The":[96,173],"main":[97],"idea":[98],"leverage":[101],"expert":[102],"knowledge":[103],"by":[104,128,169],"generating":[105],"very":[107],"large":[108],"number":[109],"binary":[111],"indicators.":[112],"Each":[113],"indicator":[114],"corresponds":[115],"fully":[118],"parametrized":[119],"detector":[121],"built":[122],"from":[123],"parametric":[124],"scores":[126],"designed":[127,181],"experts.":[129],"A":[130],"feature":[131],"selection":[132,171],"method":[133],"used":[135,145],"keep":[137],"only":[138],"most":[140],"discriminant":[141],"indicators":[142],"which":[143],"inputs":[147],"Naive":[150],"Bayes":[151],"classifier.":[152],"give":[154],"an":[155],"interpretable":[156,160],"classifier":[157],"based":[158],"on":[159,178],"detectors":[162],"whose":[163],"parameters":[164],"have":[165],"been":[166],"optimized":[167],"indirectly":[168],"process.":[172],"proposed":[174],"evaluated":[177],"simulated":[179],"data":[180],"reproduce":[183],"some":[184],"types":[188],"observed":[189],"real":[191],"world":[192],"engines.":[193]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2016-06-24T00:00:00"}