{"id":"https://openalex.org/W4412836855","doi":"https://doi.org/10.1109/access.2025.3594986","title":"Novel Evaluation Techniques for Outlier Detection Methods: A Case Study With RCOD","display_name":"Novel Evaluation Techniques for Outlier Detection Methods: A Case Study With RCOD","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412836855","doi":"https://doi.org/10.1109/access.2025.3594986"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3594986","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3594986","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3594986","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5029390512","display_name":"Adam Kiersztyn","orcid":"https://orcid.org/0000-0001-5222-8101"},"institutions":[{"id":"https://openalex.org/I8264552","display_name":"Lublin University of Technology","ror":"https://ror.org/024zjzd49","country_code":"PL","type":"education","lineage":["https://openalex.org/I8264552"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Adam Kiersztyn","raw_affiliation_strings":["Department of Computational Intelligence, Lublin University of Technology, Lublin, Poland","Department of Computational Intelligence, Lublin University of Technology, ul. Nadbystrzycka 38, Lublin, Poland"],"affiliations":[{"raw_affiliation_string":"Department of Computational Intelligence, Lublin University of Technology, Lublin, Poland","institution_ids":["https://openalex.org/I8264552"]},{"raw_affiliation_string":"Department of Computational Intelligence, Lublin University of Technology, ul. Nadbystrzycka 38, Lublin, Poland","institution_ids":["https://openalex.org/I8264552"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000205092","display_name":"Krystyna Kiersztyn","orcid":"https://orcid.org/0000-0003-1957-1797"},"institutions":[{"id":"https://openalex.org/I8264552","display_name":"Lublin University of Technology","ror":"https://ror.org/024zjzd49","country_code":"PL","type":"education","lineage":["https://openalex.org/I8264552"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Krystyna Kiersztyn","raw_affiliation_strings":["Department of Computational Intelligence, Lublin University of Technology, Lublin, Poland","Department of Computational Intelligence, Lublin University of Technology, ul. Nadbystrzycka 38, Lublin, Poland"],"affiliations":[{"raw_affiliation_string":"Department of Computational Intelligence, Lublin University of Technology, Lublin, Poland","institution_ids":["https://openalex.org/I8264552"]},{"raw_affiliation_string":"Department of Computational Intelligence, Lublin University of Technology, ul. Nadbystrzycka 38, Lublin, Poland","institution_ids":["https://openalex.org/I8264552"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053353725","display_name":"Micha\u0142 Horodelski","orcid":null},"institutions":[{"id":"https://openalex.org/I8264552","display_name":"Lublin University of Technology","ror":"https://ror.org/024zjzd49","country_code":"PL","type":"education","lineage":["https://openalex.org/I8264552"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Micha\u0142 Horodelski","raw_affiliation_strings":["Department of Computational Intelligence, Lublin University of Technology, Lublin, Poland","Department of Computational Intelligence, Lublin University of Technology, ul. Nadbystrzycka 38, Lublin, Poland"],"affiliations":[{"raw_affiliation_string":"Department of Computational Intelligence, Lublin University of Technology, Lublin, Poland","institution_ids":["https://openalex.org/I8264552"]},{"raw_affiliation_string":"Department of Computational Intelligence, Lublin University of Technology, ul. Nadbystrzycka 38, Lublin, Poland","institution_ids":["https://openalex.org/I8264552"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5094208722","display_name":"Dorota Pylak","orcid":"https://orcid.org/0000-0003-3220-3841"},"institutions":[{"id":"https://openalex.org/I111702420","display_name":"John Paul II Catholic University of Lublin","ror":"https://ror.org/04qyefj88","country_code":"PL","type":"education","lineage":["https://openalex.org/I111702420"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Dorota Pylak","raw_affiliation_strings":["Department of Mathematical Modelling, John Paul II Catholic University of Lublin, Lublin, Poland","Department of Mathematical Modelling, The John Paul II Catholic University of Lublin, ul. Konstantynów 1H, Lublin, Poland"],"affiliations":[{"raw_affiliation_string":"Department of Mathematical Modelling, John Paul II Catholic University of Lublin, Lublin, Poland","institution_ids":["https://openalex.org/I111702420"]},{"raw_affiliation_string":"Department of Mathematical Modelling, The John Paul II Catholic University of Lublin, ul. Konstantynów 1H, Lublin, Poland","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5029390512"],"corresponding_institution_ids":["https://openalex.org/I8264552"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.8599,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.92064673,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"13","issue":null,"first_page":"139719","last_page":"139731"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9980999827384949,"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":0.9980999827384949,"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":0.9625999927520752,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6847838163375854},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5389891266822815},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.47476792335510254},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4213629961013794},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3996883034706116},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36063307523727417}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6847838163375854},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5389891266822815},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.47476792335510254},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4213629961013794},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3996883034706116},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36063307523727417}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3594986","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3594986","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:7b24a95aa1544acfa816f3935b256b9f","is_oa":true,"landing_page_url":"https://doaj.org/article/7b24a95aa1544acfa816f3935b256b9f","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 139719-139731 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3594986","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3594986","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G742688527","display_name":null,"funder_award_id":"FD-20/IT-3/002","funder_id":"https://openalex.org/F4320316854","funder_display_name":"Politechnika Lubelska"}],"funders":[{"id":"https://openalex.org/F4320316854","display_name":"Politechnika Lubelska","ror":"https://ror.org/024zjzd49"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W845124934","https://openalex.org/W1548161163","https://openalex.org/W1652242680","https://openalex.org/W1868203821","https://openalex.org/W1989352541","https://openalex.org/W1990352893","https://openalex.org/W1995443851","https://openalex.org/W2006862475","https://openalex.org/W2009284788","https://openalex.org/W2016006067","https://openalex.org/W2019014808","https://openalex.org/W2026948419","https://openalex.org/W2038869050","https://openalex.org/W2049068327","https://openalex.org/W2049559208","https://openalex.org/W2061122559","https://openalex.org/W2061240327","https://openalex.org/W2063729131","https://openalex.org/W2073703998","https://openalex.org/W2090197195","https://openalex.org/W2114834796","https://openalex.org/W2128510565","https://openalex.org/W2132870739","https://openalex.org/W2140413822","https://openalex.org/W2144182447","https://openalex.org/W2149703646","https://openalex.org/W2168408108","https://openalex.org/W2296719434","https://openalex.org/W2316225045","https://openalex.org/W2676890506","https://openalex.org/W2743138268","https://openalex.org/W2769133265","https://openalex.org/W2783205364","https://openalex.org/W2809438551","https://openalex.org/W2907598569","https://openalex.org/W2920079995","https://openalex.org/W2934672175","https://openalex.org/W2954508354","https://openalex.org/W2973442392","https://openalex.org/W2995619225","https://openalex.org/W3006123093","https://openalex.org/W3025371672","https://openalex.org/W3082117105","https://openalex.org/W3128465814","https://openalex.org/W3128944770","https://openalex.org/W3134257270","https://openalex.org/W3140288472","https://openalex.org/W3178381772","https://openalex.org/W3197262264","https://openalex.org/W3201054704","https://openalex.org/W3213140656","https://openalex.org/W4224254843","https://openalex.org/W4226060502","https://openalex.org/W4231975640","https://openalex.org/W4253461361","https://openalex.org/W4282980030","https://openalex.org/W4283009062","https://openalex.org/W4283810514","https://openalex.org/W4295768095","https://openalex.org/W4313254234","https://openalex.org/W4367016885","https://openalex.org/W4389459488","https://openalex.org/W4391742969","https://openalex.org/W4393029505"],"related_works":["https://openalex.org/W3006513224","https://openalex.org/W2046456988","https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W1598471830","https://openalex.org/W3107369729","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Outlier":[0,33],"detection":[1,27,94],"remains":[2],"a":[3,20,37,113],"key":[4],"challenge":[5],"in":[6],"data":[7,42,142],"analysis,":[8],"with":[9],"applications":[10],"spanning":[11],"cybersecurity,":[12],"finance,":[13],"medicine,":[14],"and":[15,49,56,80,92,100,105,138],"more.":[16],"This":[17],"paper":[18],"introduces":[19],"comprehensive":[21],"evaluation":[22,66,110],"framework":[23],"for":[24],"comparing":[25],"outlier":[26,120],"methods,":[28],"using":[29],"the":[30,75,117,130],"Random":[31],"Clustering-based":[32],"Detector":[34],"(RCOD)":[35],"as":[36],"case":[38],"study.":[39],"RCOD":[40],"groups":[41],"points":[43],"around":[44],"randomly":[45],"selected":[46],"cluster":[47],"centers":[48],"identifies":[50],"outliers":[51],"based":[52,71,82],"on":[53,72,83,88],"distance-based":[54],"criteria":[55],"statistical":[57],"thresholds.":[58],"To":[59],"enable":[60],"more":[61],"reliable":[62],"assessment,":[63],"two":[64],"novel":[65],"strategies":[67],"are":[68],"proposed:":[69],"one":[70],"deviations":[73],"from":[74],"best-performing":[76],"method":[77],"per":[78],"dataset,":[79],"another":[81],"rank-based":[84],"comparison.":[85],"Experiments":[86],"conducted":[87],"30":[89],"benchmark":[90],"datasets":[91],"13":[93],"methods":[95],"demonstrate":[96],"RCOD\u2019s":[97,133],"superior":[98],"performance":[99,124],"stability":[101],"across":[102],"accuracy,":[103],"precision,":[104],"F1-score":[106],"metrics.":[107],"The":[108],"proposed":[109],"techniques":[111],"provide":[112],"deeper":[114],"insight":[115],"into":[116],"effectiveness":[118],"of":[119,132],"detectors":[121],"than":[122],"traditional":[123],"metrics":[125],"alone.":[126],"Statistical":[127],"validation":[128],"confirms":[129],"significance":[131],"advantage,":[134],"highlighting":[135],"its":[136],"robustness":[137],"applicability":[139],"to":[140],"diverse":[141],"environments.":[143]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}