{"id":"https://openalex.org/W2761705761","doi":"https://doi.org/10.1504/ijwmc.2017.10008211","title":"A hybrid algorithm for mining local outliers in categorical data","display_name":"A hybrid algorithm for mining local outliers in categorical data","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2761705761","doi":"https://doi.org/10.1504/ijwmc.2017.10008211","mag":"2761705761"},"language":"en","primary_location":{"id":"doi:10.1504/ijwmc.2017.10008211","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijwmc.2017.10008211","pdf_url":null,"source":{"id":"https://openalex.org/S168395412","display_name":"International Journal of Wireless and Mobile Computing","issn_l":"1741-1084","issn":["1741-1084","1741-1092"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317825","host_organization_name":"Inderscience Publishers","host_organization_lineage":["https://openalex.org/P4310317825"],"host_organization_lineage_names":["Inderscience Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Wireless and Mobile Computing","raw_type":"journal-article"},"type":"article","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/A5100694693","display_name":"Meiling Liu","orcid":"https://orcid.org/0000-0003-4208-7274"},"institutions":[{"id":"https://openalex.org/I167274908","display_name":"Guangxi University for Nationalities","ror":"https://ror.org/0495efn48","country_code":"CN","type":"education","lineage":["https://openalex.org/I167274908"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Meiling Liu","raw_affiliation_strings":["College of Software and Information Security, Guangxi University for Nationalities, Nanning 530006, China; Science Computing and Intelligent Information Processing of Guangxi Higher Education Key Laboratory, Nanning 530023, China","College of Software and Information Security, Guangxi University for Nationalities, Nanning 530006, China","Science Computing and Intelligent Information Processing of Guangxi Higher Education Key Laboratory, Nanning 530023, China"],"affiliations":[{"raw_affiliation_string":"College of Software and Information Security, Guangxi University for Nationalities, Nanning 530006, China; Science Computing and Intelligent Information Processing of Guangxi Higher Education Key Laboratory, Nanning 530023, China","institution_ids":["https://openalex.org/I167274908"]},{"raw_affiliation_string":"College of Software and Information Security, Guangxi University for Nationalities, Nanning 530006, China","institution_ids":["https://openalex.org/I167274908"]},{"raw_affiliation_string":"Science Computing and Intelligent Information Processing of Guangxi Higher Education Key Laboratory, Nanning 530023, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058832301","display_name":"Mingxuan Huang","orcid":"https://orcid.org/0009-0008-2383-9446"},"institutions":[{"id":"https://openalex.org/I163732180","display_name":"Guangxi University of Finance and Economics","ror":"https://ror.org/02ayg6516","country_code":"CN","type":"education","lineage":["https://openalex.org/I163732180"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingxuan Huang","raw_affiliation_strings":["College of Information and Statistics, Guangxi University of Finance and Economics, Nanning 530003, China"],"affiliations":[{"raw_affiliation_string":"College of Information and Statistics, Guangxi University of Finance and Economics, Nanning 530003, China","institution_ids":["https://openalex.org/I163732180"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066281595","display_name":"Weidong Tang","orcid":"https://orcid.org/0000-0002-1263-1964"},"institutions":[{"id":"https://openalex.org/I167274908","display_name":"Guangxi University for Nationalities","ror":"https://ror.org/0495efn48","country_code":"CN","type":"education","lineage":["https://openalex.org/I167274908"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weidong Tang","raw_affiliation_strings":["College of Information Science and Engineering, Guangxi University for Nationalities, Nanning 530006, China"],"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Guangxi University for Nationalities, Nanning 530006, China","institution_ids":["https://openalex.org/I167274908"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100694693"],"corresponding_institution_ids":["https://openalex.org/I167274908"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.13388164,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":"13","issue":"1","first_page":"78","last_page":"78"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9832000136375427,"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":0.9832000136375427,"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/T13882","display_name":"Research studies in Vietnam","score":0.9648000001907349,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.9045000076293945,"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/outlier","display_name":"Outlier","score":0.9081007242202759},{"id":"https://openalex.org/keywords/local-outlier-factor","display_name":"Local outlier factor","score":0.8872859477996826},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.8239036202430725},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7467882037162781},{"id":"https://openalex.org/keywords/categorical-variable","display_name":"Categorical variable","score":0.7424091100692749},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6163550615310669},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5510334968566895},{"id":"https://openalex.org/keywords/standard-deviation","display_name":"Standard deviation","score":0.548025369644165},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48917892575263977},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41425469517707825},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36308300495147705},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2072957456111908},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1803916096687317},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1779833734035492}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.9081007242202759},{"id":"https://openalex.org/C169029474","wikidata":"https://www.wikidata.org/wiki/Q387942","display_name":"Local outlier factor","level":3,"score":0.8872859477996826},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.8239036202430725},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7467882037162781},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.7424091100692749},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6163550615310669},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5510334968566895},{"id":"https://openalex.org/C22679943","wikidata":"https://www.wikidata.org/wiki/Q159375","display_name":"Standard deviation","level":2,"score":0.548025369644165},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48917892575263977},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41425469517707825},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36308300495147705},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2072957456111908},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1803916096687317},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1779833734035492}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1504/ijwmc.2017.10008211","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijwmc.2017.10008211","pdf_url":null,"source":{"id":"https://openalex.org/S168395412","display_name":"International Journal of Wireless and Mobile Computing","issn_l":"1741-1084","issn":["1741-1084","1741-1092"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317825","host_organization_name":"Inderscience Publishers","host_organization_lineage":["https://openalex.org/P4310317825"],"host_organization_lineage_names":["Inderscience Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Wireless and Mobile Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2499612753","https://openalex.org/W2770832849","https://openalex.org/W3111802945","https://openalex.org/W205872183","https://openalex.org/W114119537","https://openalex.org/W4240627425","https://openalex.org/W2761705761","https://openalex.org/W2904893831","https://openalex.org/W2122407924","https://openalex.org/W2946096271"],"abstract_inverted_index":{"Outlier":[0],"detection":[1,31,48],"is":[2,32,72,75,139],"an":[3,98],"important":[4],"task":[5],"in":[6,83,100],"data":[7],"mining.":[8],"Many":[9],"approaches":[10],"have":[11,114],"been":[12],"developed":[13],"to":[14],"detect":[15],"outliers.":[16,128,146],"However,":[17],"most":[18],"researches":[19],"focus":[20],"on":[21,77,131],"global":[22,37],"outlier":[23,30,38,47,58,71,95,122],"detection.":[24,39],"In":[25,40],"many":[26],"situations,":[27],"the":[28,36,43,54,87,101,107,117,136],"local":[29,57,70,94,121,145],"more":[33],"valuable":[34],"than":[35],"this":[41],"paper,":[42],"existing":[44],"methods":[45],"for":[46,68,143],"are":[49,62],"discussed":[50],"firstly,":[51],"and":[52,59,80,93,116,141],"then":[53],"definition":[55],"of":[56,90,97],"some":[60],"formulas":[61],"given.":[63],"Also":[64],"a":[65,91],"hybrid":[66],"algorithm":[67,79,138],"mining":[69,144],"proposed":[73,137],"which":[74],"based":[76],"clustering":[78],"standard":[81,88,111],"deviation":[82,89,112],"statistics.":[84],"By":[85],"calculating":[86],"cluster":[92],"factor":[96,123],"object":[99],"cluster,":[102],"we":[103],"can":[104,124],"identify":[105],"that":[106,135],"clusters":[108],"with":[109,119],"higher":[110,120],"may":[113],"outliers,":[115],"objects":[118],"be":[125],"recognised":[126],"as":[127],"Experimental":[129],"results":[130],"real":[132],"datasets":[133],"show":[134],"correct":[140],"effective":[142]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}