{"id":"https://openalex.org/W4399563561","doi":"https://doi.org/10.1109/ssd61670.2024.10548429","title":"Exploring High-Dimensional Outlier Detection: A Comprehensive Study on Methods and Applications Using PCA and k-NN Algorithm","display_name":"Exploring High-Dimensional Outlier Detection: A Comprehensive Study on Methods and Applications Using PCA and k-NN Algorithm","publication_year":2024,"publication_date":"2024-04-22","ids":{"openalex":"https://openalex.org/W4399563561","doi":"https://doi.org/10.1109/ssd61670.2024.10548429"},"language":"en","primary_location":{"id":"doi:10.1109/ssd61670.2024.10548429","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssd61670.2024.10548429","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 21st International Multi-Conference on Systems, Signals & Devices (SSD)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5092836161","display_name":"Wasan Abd Majeed","orcid":null},"institutions":[{"id":"https://openalex.org/I27768575","display_name":"University of Anbar","ror":"https://ror.org/055a6gk50","country_code":"IQ","type":"education","lineage":["https://openalex.org/I27768575"]}],"countries":["IQ"],"is_corresponding":false,"raw_author_name":"Wasan Abd Majeed","raw_affiliation_strings":["Al-Anbar University,Computer Science Department,Ramady,Iraq","Computer Science Department, Al-Anbar University, Ramady, Iraq"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Al-Anbar University,Computer Science Department,Ramady,Iraq","institution_ids":["https://openalex.org/I27768575"]},{"raw_affiliation_string":"Computer Science Department, Al-Anbar University, Ramady, Iraq","institution_ids":["https://openalex.org/I27768575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057933083","display_name":"Murtadha M. Hamad","orcid":"https://orcid.org/0000-0001-9919-3217"},"institutions":[{"id":"https://openalex.org/I27768575","display_name":"University of Anbar","ror":"https://ror.org/055a6gk50","country_code":"IQ","type":"education","lineage":["https://openalex.org/I27768575"]}],"countries":["IQ"],"is_corresponding":false,"raw_author_name":"Murtadha M. Hamad","raw_affiliation_strings":["Al-Anbar University,Computer Science Department,Ramady,Iraq","Computer Science Department, Al-Anbar University, Ramady, Iraq"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Al-Anbar University,Computer Science Department,Ramady,Iraq","institution_ids":["https://openalex.org/I27768575"]},{"raw_affiliation_string":"Computer Science Department, Al-Anbar University, Ramady, Iraq","institution_ids":["https://openalex.org/I27768575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I27768575"],"apc_list":null,"apc_paid":null,"fwci":0.7112,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.67538858,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"699","last_page":"704"},"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/T10876","display_name":"Fault Detection and Control Systems","score":0.9909999966621399,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9789000153541565,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6407502293586731},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6336938738822937},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5714809894561768},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4642413854598999},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41925501823425293},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3894261419773102},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37763479351997375}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6407502293586731},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6336938738822937},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5714809894561768},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4642413854598999},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41925501823425293},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3894261419773102},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37763479351997375}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssd61670.2024.10548429","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssd61670.2024.10548429","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 21st International Multi-Conference on Systems, Signals & Devices (SSD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1892979790","https://openalex.org/W1935884779","https://openalex.org/W1982672081","https://openalex.org/W1988073563","https://openalex.org/W2028678069","https://openalex.org/W2052164429","https://openalex.org/W2095713606","https://openalex.org/W2333568743","https://openalex.org/W2340896621","https://openalex.org/W2500517591","https://openalex.org/W2585713683","https://openalex.org/W2607261387","https://openalex.org/W2613480438","https://openalex.org/W2625814963","https://openalex.org/W2732947513","https://openalex.org/W2790882791","https://openalex.org/W2807373698","https://openalex.org/W2807955733","https://openalex.org/W2899640049","https://openalex.org/W2911627187","https://openalex.org/W2956545777","https://openalex.org/W2977728051","https://openalex.org/W3003323003","https://openalex.org/W3039222472","https://openalex.org/W3117098906","https://openalex.org/W3175925604","https://openalex.org/W3217270075","https://openalex.org/W4210536668","https://openalex.org/W4224080106","https://openalex.org/W4226505547","https://openalex.org/W4234384890","https://openalex.org/W4254182148","https://openalex.org/W4254420769","https://openalex.org/W4312729928","https://openalex.org/W4313590336","https://openalex.org/W4320498080","https://openalex.org/W4385626654","https://openalex.org/W4385697512","https://openalex.org/W6678723600","https://openalex.org/W6744977159","https://openalex.org/W6752375211","https://openalex.org/W6771318613","https://openalex.org/W6852994821","https://openalex.org/W6861287798","https://openalex.org/W6886048326"],"related_works":["https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W3006513224","https://openalex.org/W2046456988","https://openalex.org/W2357409937","https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W3107369729"],"abstract_inverted_index":{"This":[0],"study":[1],"addresses":[2],"the":[3,59,72,94,100,115,124,169],"challenge":[4],"of":[5,61,99,126,139],"outlier":[6,25,110,158],"detection":[7,26,111,159],"in":[8,14],"high-dimensional":[9],"data,":[10],"emphasizing":[11],"its":[12],"significance":[13],"various":[15],"applications.":[16],"The":[17,52,133,164],"research":[18],"involves":[19],"a":[20,29,75,137],"comprehensive":[21],"literature":[22],"review":[23],"on":[24,32,123],"methods,":[27],"with":[28,105,120],"specific":[30],"focus":[31],"Angle-based":[33],"Outlier":[34,43],"Detection":[35],"(ABOD),":[36],"One-class":[37],"Support":[38],"Vector":[39],"Machine":[40],"(OSVM),":[41],"Local":[42],"Factor":[44],"(LOF),":[45],"Isolation":[46],"Forest":[47],"(IF),":[48],"and":[49,58,130,146,157,176],"AutoEncoder":[50],"(AE).":[51],"high":[53],"dimensionality":[54,67,155],"problem":[55],"is":[56,69,80,89,112,151,162],"discussed,":[57],"use":[60],"Principal":[62],"Component":[63],"Analysis":[64],"(PCA)":[65],"for":[66,82,154],"reduction":[68],"highlighted.":[70],"In":[71],"experimental":[73],"phase,":[74],"dataset":[76,138],"comprising":[77],"standardized":[78],"features":[79],"scaled":[81],"further":[83],"analysis,":[84],"excluding":[85],"certain":[86],"identifiers.":[87],"PCA":[88,150],"then":[90],"applied":[91],"to":[92,136],"reduce":[93],"dimensionality,":[95],"revealing":[96],"that":[97],"90%":[98],"variance":[101],"can":[102],"be":[103],"retained":[104],"12":[106],"principal":[107],"components.":[108],"Subsequently,":[109],"performed":[113],"using":[114,160],"k-Nearest":[116],"Neighbors":[117],"(k-NN)":[118],"algorithm,":[119],"an":[121],"emphasis":[122],"impact":[125],"different":[127],"k":[128],"values":[129],"distance":[131],"metrics.":[132],"analysis":[134],"extends":[135],"20,058":[140],"chess":[141],"matches,":[142],"incorporating":[143],"descriptive":[144],"statistics":[145],"exploratory":[147],"data":[148],"analysis.":[149],"again":[152],"employed":[153],"reduction,":[156],"k-NN":[161],"executed.":[163],"findings":[165],"provide":[166],"insights":[167],"into":[168],"dataset's":[170],"characteristics,":[171],"including":[172],"key":[173],"statistical":[174],"metrics":[175],"potential":[177],"outliers.":[178]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}