{"id":"https://openalex.org/W3136145627","doi":"https://doi.org/10.1109/tcyb.2021.3058780","title":"Outlier Detection Based on Fuzzy Rough Granules in Mixed Attribute Data","display_name":"Outlier Detection Based on Fuzzy Rough Granules in Mixed Attribute Data","publication_year":2021,"publication_date":"2021-03-22","ids":{"openalex":"https://openalex.org/W3136145627","doi":"https://doi.org/10.1109/tcyb.2021.3058780","mag":"3136145627","pmid":"https://pubmed.ncbi.nlm.nih.gov/33750721"},"language":"en","primary_location":{"id":"doi:10.1109/tcyb.2021.3058780","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2021.3058780","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"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 Transactions on Cybernetics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5008041028","display_name":"Zhong Yuan","orcid":"https://orcid.org/0000-0002-7456-4445"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhong Yuan","raw_affiliation_strings":["School of Information Science and Technology, Institute of Artificial Intelligence, Southwest Jiaotong University, Chengdu, China","National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-7456-4445","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Institute of Artificial Intelligence, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]},{"raw_affiliation_string":"National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100358460","display_name":"Hongmei Chen","orcid":"https://orcid.org/0000-0002-7225-5577"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongmei Chen","raw_affiliation_strings":["School of Information Science and Technology, Institute of Artificial Intelligence, Southwest Jiaotong University, Chengdu, China","National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-7225-5577","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Institute of Artificial Intelligence, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]},{"raw_affiliation_string":"National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070559820","display_name":"Tianrui Li","orcid":"https://orcid.org/0000-0001-7780-104X"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianrui Li","raw_affiliation_strings":["School of Information Science and Technology, Institute of Artificial Intelligence, Southwest Jiaotong University, Chengdu, China","National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0001-7780-104X","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Institute of Artificial Intelligence, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]},{"raw_affiliation_string":"National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060587388","display_name":"Binbin Sang","orcid":null},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Binbin Sang","raw_affiliation_strings":["School of Information Science and Technology, Institute of Artificial Intelligence, Southwest Jiaotong University, Chengdu, China","National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Institute of Artificial Intelligence, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]},{"raw_affiliation_string":"National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100335449","display_name":"Shu Wang","orcid":"https://orcid.org/0000-0001-8781-2535"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shu Wang","raw_affiliation_strings":["School of Information Science and Technology, Institute of Artificial Intelligence, Southwest Jiaotong University, Chengdu, China","National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Institute of Artificial Intelligence, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]},{"raw_affiliation_string":"National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4800084"],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":6.8604,"has_fulltext":false,"cited_by_count":103,"citation_normalized_percentile":{"value":0.97271087,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"52","issue":"8","first_page":"8399","last_page":"8412"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9975000023841858,"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":0.9975000023841858,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.9842000007629395,"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/categorical-variable","display_name":"Categorical variable","score":0.8205781579017639},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.7995033264160156},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7638698220252991},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.623197078704834},{"id":"https://openalex.org/keywords/rough-set","display_name":"Rough set","score":0.5140005946159363},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5054795742034912},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4954415559768677},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.49390989542007446},{"id":"https://openalex.org/keywords/local-outlier-factor","display_name":"Local outlier factor","score":0.4915221631526947},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4378727972507477},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.43193143606185913},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1555522382259369}],"concepts":[{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.8205781579017639},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7995033264160156},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7638698220252991},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.623197078704834},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.5140005946159363},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5054795742034912},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4954415559768677},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.49390989542007446},{"id":"https://openalex.org/C169029474","wikidata":"https://www.wikidata.org/wiki/Q387942","display_name":"Local outlier factor","level":3,"score":0.4915221631526947},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4378727972507477},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.43193143606185913},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1555522382259369}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D017143","descriptor_name":"Fuzzy Logic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D017143","descriptor_name":"Fuzzy Logic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D017143","descriptor_name":"Fuzzy Logic","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D057225","descriptor_name":"Data Mining","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/tcyb.2021.3058780","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2021.3058780","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"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 Transactions on Cybernetics","raw_type":"journal-article"},{"id":"pmid:33750721","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33750721","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on cybernetics","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1814726428","display_name":null,"funder_award_id":"62076171","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7385129332","display_name":null,"funder_award_id":"(61976182)","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7889951188","display_name":"\u7c97\u7cd9\u96c6\u4e2d\u5e26\u7ea6\u675f\u7684\u7279\u5f81\u9009\u62e9\u9ad8\u6548\u7b97\u6cd5\u7814\u7a76","funder_award_id":"61572406","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W101345952","https://openalex.org/W1494402569","https://openalex.org/W1590946452","https://openalex.org/W1868203821","https://openalex.org/W1987004515","https://openalex.org/W1988907639","https://openalex.org/W2006138243","https://openalex.org/W2007810691","https://openalex.org/W2016006067","https://openalex.org/W2019014808","https://openalex.org/W2021680742","https://openalex.org/W2027654459","https://openalex.org/W2041193317","https://openalex.org/W2043051613","https://openalex.org/W2049058890","https://openalex.org/W2057245489","https://openalex.org/W2059429344","https://openalex.org/W2073411490","https://openalex.org/W2083047046","https://openalex.org/W2084744288","https://openalex.org/W2111011053","https://openalex.org/W2127891163","https://openalex.org/W2129281431","https://openalex.org/W2137396323","https://openalex.org/W2141375575","https://openalex.org/W2141741236","https://openalex.org/W2144182447","https://openalex.org/W2147597050","https://openalex.org/W2153166477","https://openalex.org/W2282861635","https://openalex.org/W2342915065","https://openalex.org/W2416404380","https://openalex.org/W2473601878","https://openalex.org/W2498631646","https://openalex.org/W2561208659","https://openalex.org/W2568086521","https://openalex.org/W2807198477","https://openalex.org/W2883355296","https://openalex.org/W2901560888","https://openalex.org/W2942240431","https://openalex.org/W2956917852","https://openalex.org/W3120740533","https://openalex.org/W4205659258","https://openalex.org/W4245050711","https://openalex.org/W4255833381","https://openalex.org/W6608289497","https://openalex.org/W6632829031"],"related_works":["https://openalex.org/W2499612753","https://openalex.org/W2770832849","https://openalex.org/W3111802945","https://openalex.org/W114119537","https://openalex.org/W2912112202","https://openalex.org/W4240627425","https://openalex.org/W2761705761","https://openalex.org/W205872183","https://openalex.org/W2122407924","https://openalex.org/W2946096271"],"abstract_inverted_index":{"Outlier":[0],"detection":[1,22,36,57,65,87,94,157],"is":[2,72,107,133,160,168,183,190],"one":[3],"of":[4,15,37,55,67,114,148,164],"the":[5,16,34,53,63,68,76,85,102,111,120,125,137,140,145,151,165,181],"most":[6,14],"important":[7],"research":[8,18],"directions":[9],"in":[10,58],"data":[11],"mining.":[12],"However,":[13],"current":[17],"focuses":[19],"on":[20,33,97,129,172],"outlier":[21,35,56,64,86,93,104,112,126,146,156],"for":[23,186,192],"categorical":[24,77],"or":[25],"numerical":[26],"attribute":[27,39,60,78,197],"data.":[28,40,61,198],"There":[29],"are":[30],"few":[31],"studies":[32],"mixed":[38,59,196],"In":[41],"this":[42],"article,":[43],"we":[44,80],"introduce":[45],"fuzzy":[46,98,115,121,130,153],"rough":[47,70,99,116,131,154],"sets":[48],"(FRSs)":[49],"to":[50,75,83,109,143],"deal":[51],"with":[52],"problem":[54],"Since":[62],"model":[66,88,95],"classical":[69],"set":[71],"only":[73],"applicable":[74],"data,":[79],"use":[81],"FRS":[82],"generalize":[84],"and":[89,139,189,195],"construct":[90],"a":[91],"generalized":[92],"based":[96,128],"granules.":[100],"First,":[101],"granule":[103],"degree":[105,113,147],"(GOD)":[106],"defined":[108],"characterize":[110,144],"granules":[117,132],"by":[118,135],"employing":[119],"approximation":[122],"accuracy.":[123],"Then,":[124],"factor":[127],"constructed":[134],"integrating":[136],"GOD":[138],"corresponding":[141,152],"weights":[142],"objects.":[149],"Furthermore,":[150],"granules-based":[155],"(FRGOD)":[158],"algorithm":[159,167,182],"designed.":[161],"The":[162,176],"effectiveness":[163],"FRGOD":[166],"evaluated":[169],"through":[170],"experiments":[171],"16":[173],"real-world":[174],"datasets.":[175],"experimental":[177],"results":[178],"show":[179],"that":[180],"more":[184],"flexible":[185],"detecting":[187],"outliers":[188],"suitable":[191],"numerical,":[193],"categorical,":[194]},"counts_by_year":[{"year":2026,"cited_by_count":23},{"year":2025,"cited_by_count":29},{"year":2024,"cited_by_count":25},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":4}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}