{"id":"https://openalex.org/W3197109700","doi":"https://doi.org/10.1007/s41019-021-00169-x","title":"FairLOF: Fairness in Outlier Detection","display_name":"FairLOF: Fairness in Outlier Detection","publication_year":2021,"publication_date":"2021-08-29","ids":{"openalex":"https://openalex.org/W3197109700","doi":"https://doi.org/10.1007/s41019-021-00169-x","mag":"3197109700"},"language":"en","primary_location":{"id":"doi:10.1007/s41019-021-00169-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41019-021-00169-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41019-021-00169-x.pdf","source":{"id":"https://openalex.org/S2486411021","display_name":"Data Science and Engineering","issn_l":"2364-1185","issn":["2364-1185","2364-1541"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Science and Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://link.springer.com/content/pdf/10.1007/s41019-021-00169-x.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113740386","display_name":"P Deepak","orcid":null},"institutions":[{"id":"https://openalex.org/I126231945","display_name":"Queen's University Belfast","ror":"https://ror.org/00hswnk62","country_code":"GB","type":"education","lineage":["https://openalex.org/I126231945"]},{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"facility","lineage":["https://openalex.org/I24676775"]}],"countries":["GB","IN"],"is_corresponding":true,"raw_author_name":"Deepak P","raw_affiliation_strings":["Indian Institute of Technology Madras, Chennai, India","Queen\u2019s University Belfast, Belfast, UK","Queen's University Belfast, Belfast, UK"],"raw_orcid":"https://orcid.org/0000-0002-1336-2356","affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]},{"raw_affiliation_string":"Queen\u2019s University Belfast, Belfast, UK","institution_ids":["https://openalex.org/I126231945"]},{"raw_affiliation_string":"Queen's University Belfast, Belfast, UK","institution_ids":["https://openalex.org/I126231945"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002631025","display_name":"Savitha Sam Abraham","orcid":"https://orcid.org/0000-0003-3902-2867"},"institutions":[{"id":"https://openalex.org/I26437253","display_name":"\u00d6rebro University","ror":"https://ror.org/05kytsw45","country_code":"SE","type":"education","lineage":["https://openalex.org/I26437253"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Savitha Sam Abraham","raw_affiliation_strings":["School of Science and Technology, \u00d6rebro University, 701 82, \u00d6rebro, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Science and Technology, \u00d6rebro University, 701 82, \u00d6rebro, Sweden","institution_ids":["https://openalex.org/I26437253"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5113740386"],"corresponding_institution_ids":["https://openalex.org/I126231945","https://openalex.org/I24676775"],"apc_list":null,"apc_paid":null,"fwci":0.9534,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.79963561,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"6","issue":"4","first_page":"485","last_page":"499"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9954000115394592,"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":0.9954000115394592,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9409999847412109,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9340000152587891,"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":0.8310378789901733},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.7851488590240479},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7833448052406311},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6042429208755493},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5705816149711609},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5433446168899536},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5042127370834351},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.456236332654953},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36914652585983276},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36747175455093384},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09989491105079651}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8310378789901733},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7851488590240479},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7833448052406311},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6042429208755493},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5705816149711609},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5433446168899536},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5042127370834351},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.456236332654953},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36914652585983276},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36747175455093384},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09989491105079651},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/s41019-021-00169-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41019-021-00169-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41019-021-00169-x.pdf","source":{"id":"https://openalex.org/S2486411021","display_name":"Data Science and Engineering","issn_l":"2364-1185","issn":["2364-1185","2364-1541"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Science and Engineering","raw_type":"journal-article"},{"id":"pmh:oai:pure.qub.ac.uk/portal:publications/bad6d5a5-cd5d-4e61-9ce9-c17c75fa5647","is_oa":true,"landing_page_url":"https://pure.qub.ac.uk/en/publications/bad6d5a5-cd5d-4e61-9ce9-c17c75fa5647","pdf_url":null,"source":{"id":"https://openalex.org/S4306402319","display_name":"Research Portal (Queen's University Belfast)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I126231945","host_organization_name":"Queen's University Belfast","host_organization_lineage":["https://openalex.org/I126231945"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"P, D & Abraham, S S 2021, 'FairLOF: fairness in outlier detection', Data Science and Engineering, vol. 6, no. 4, pp. 485-499. https://doi.org/10.1007/s41019-021-00169-x","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:openaccess.city.ac.uk:36027","is_oa":false,"landing_page_url":"https://openaccess.city.ac.uk/view/creators_id/savitha=2Esam-abraham.html>","pdf_url":null,"source":{"id":"https://openalex.org/S4306401940","display_name":"City Research Online (City University London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I180825142","host_organization_name":"City, University of London","host_organization_lineage":["https://openalex.org/I180825142"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":{"id":"doi:10.1007/s41019-021-00169-x","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41019-021-00169-x","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41019-021-00169-x.pdf","source":{"id":"https://openalex.org/S2486411021","display_name":"Data Science and Engineering","issn_l":"2364-1185","issn":["2364-1185","2364-1541"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Data Science and Engineering","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6200000047683716,"id":"https://metadata.un.org/sdg/5","display_name":"Gender equality"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3197109700.pdf","grobid_xml":"https://content.openalex.org/works/W3197109700.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W82678928","https://openalex.org/W353413754","https://openalex.org/W1819662813","https://openalex.org/W2036887984","https://openalex.org/W2041184937","https://openalex.org/W2049058890","https://openalex.org/W2070983531","https://openalex.org/W2075949491","https://openalex.org/W2100200066","https://openalex.org/W2111937426","https://openalex.org/W2117839996","https://openalex.org/W2133350412","https://openalex.org/W2144182447","https://openalex.org/W2319745077","https://openalex.org/W2621614835","https://openalex.org/W2704480242","https://openalex.org/W2760451156","https://openalex.org/W2908709484","https://openalex.org/W2950104108","https://openalex.org/W2962762307","https://openalex.org/W2963992001","https://openalex.org/W2964249987","https://openalex.org/W2970788251","https://openalex.org/W2973459221","https://openalex.org/W2979932536","https://openalex.org/W2987299728","https://openalex.org/W2997606354","https://openalex.org/W3007065191","https://openalex.org/W3033733989","https://openalex.org/W3038091217","https://openalex.org/W3090138545","https://openalex.org/W3102092462","https://openalex.org/W3111791155","https://openalex.org/W3123374861","https://openalex.org/W3183371972","https://openalex.org/W4213439731","https://openalex.org/W4235091326","https://openalex.org/W6600060591","https://openalex.org/W6600605178","https://openalex.org/W6600651459","https://openalex.org/W6821542688"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W4283314094","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W3107369729"],"abstract_inverted_index":{"Abstract":[0],"An":[1],"outlier":[2,17,39,49,79,94,134,204],"detection":[3,18,50,80,205],"method":[4],"may":[5],"be":[6,103],"considered":[7],"fair":[8,38,48,78,133],"over":[9,51,153],"specified":[10],"sensitive":[11,28,54],"attributes":[12,55],"if":[13],"the":[14,35,45,88,117,120,178],"results":[15],"of":[16,37,47,119,146,188,199],"are":[19],"not":[20],"skewed":[21],"toward":[22],"particular":[23],"groups":[24],"defined":[25],"on":[26,44,142,172],"such":[27],"attributes.":[29],"In":[30],"this":[31],"paper,":[32],"we":[33,127,156],"consider":[34],"task":[36,46],"detection.":[40,95],"Our":[41],"focus":[42],"is":[43,85,160,194,208],"multiple":[52],"multi-valued":[53],"(e.g.,":[56],"gender,":[57],"race,":[58],"religion,":[59],"nationality":[60],"and":[61,107,136,144],"marital":[62],"status,":[63],"among":[64],"others),":[65],"one":[66],"that":[67,84,138,158,185],"has":[68],"broad":[69],"applications":[70],"across":[71],"modern":[72],"data":[73],"scenarios.":[74],"We":[75,96,182],"propose":[76],"a":[77,124,186],"method,":[81,190],"FairLOF":[82,121,141,159,211],",":[83,193],"inspired":[86],"by":[87,210],"popular":[89],"LOF":[90,106,180],"formulation":[91],"for":[92,132],"neighborhood-based":[93],"outline":[97],"ways":[98],"in":[99,166,203],"which":[100,115],"unfairness":[101],"could":[102],"induced":[104],"within":[105],"develop":[108,128],"three":[109],"heuristic":[110],"principles":[111],"to":[112,139,162,196],"enhance":[113],"fairness,":[114],"form":[116],"basis":[118],"method.":[122,181],"Being":[123],"novel":[125],"task,":[126],"an":[129,149],"evaluation":[130,152],"framework":[131],"detection,":[135],"use":[137],"benchmark":[140],"quality":[143,174],"fairness":[145,167,202],"results.":[147],"Through":[148],"extensive":[150],"empirical":[151],"real-world":[154],"datasets,":[155],"illustrate":[157],"able":[161,195],"achieve":[163],"significant":[164],"improvements":[165],"at":[168],"sometimes":[169],"marginal":[170],"degradations":[171],"result":[173],"as":[175],"measured":[176],"against":[177],"fairness-agnostic":[179],"also":[183],"show":[184],"generalization":[187],"our":[189],"named":[191],"FairLOF-Flex":[192],"open":[197],"possibilities":[198],"further":[200],"deepening":[201],"beyond":[206],"what":[207],"offered":[209],".":[212]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2021-09-13T00:00:00"}