{"id":"https://openalex.org/W2923623744","doi":"https://doi.org/10.1109/access.2019.2906644","title":"Knowledge Reused Outlier Detection","display_name":"Knowledge Reused Outlier Detection","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2923623744","doi":"https://doi.org/10.1109/access.2019.2906644","mag":"2923623744"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2906644","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2906644","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":null,"license_id":null,"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.2019.2906644","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013764706","display_name":"Weiren Yu","orcid":"https://orcid.org/0000-0002-5846-441X"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weiren Yu","raw_affiliation_strings":["School of Computer Science, Beihang University, Beijing, China","ORCiD"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083458247","display_name":"Zhengming Ding","orcid":"https://orcid.org/0000-0002-6994-5278"},"institutions":[{"id":"https://openalex.org/I135191193","display_name":"University of Indianapolis","ror":"https://ror.org/052133d12","country_code":"US","type":"education","lineage":["https://openalex.org/I135191193"]},{"id":"https://openalex.org/I55769427","display_name":"Indiana University \u2013 Purdue University Indianapolis","ror":"https://ror.org/05gxnyn08","country_code":"US","type":"education","lineage":["https://openalex.org/I55769427","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhengming Ding","raw_affiliation_strings":["Department of Computer, Information, and Technology, Indiana University-Purdue University Indianapolis, Indianapolis, IN, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer, Information, and Technology, Indiana University-Purdue University Indianapolis, Indianapolis, IN, USA","institution_ids":["https://openalex.org/I135191193","https://openalex.org/I55769427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086470621","display_name":"Chunming Hu","orcid":"https://orcid.org/0000-0002-9502-3955"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunming Hu","raw_affiliation_strings":["School of Computer Science, Beihang University, Beijing, China","ORCiD"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086089915","display_name":"Hongfu Liu","orcid":"https://orcid.org/0000-0002-4261-8154"},"institutions":[{"id":"https://openalex.org/I6902469","display_name":"Brandeis University","ror":"https://ror.org/05abbep66","country_code":"US","type":"education","lineage":["https://openalex.org/I6902469"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongfu Liu","raw_affiliation_strings":["Department of Computer Science, Brandeis University, Waltham, MA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Brandeis University, Waltham, MA, USA","institution_ids":["https://openalex.org/I6902469"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5013764706"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.1577,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.83880108,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"7","issue":null,"first_page":"43763","last_page":"43772"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9970999956130981,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9828000068664551,"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":0.7484011650085449},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5282838940620422},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3843981623649597},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.348823606967926},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3286832571029663}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7484011650085449},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5282838940620422},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3843981623649597},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.348823606967926},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3286832571029663}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/access.2019.2906644","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2906644","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:920defc57ecf45d48b9663dab4ee0c75","is_oa":true,"landing_page_url":"https://doaj.org/article/920defc57ecf45d48b9663dab4ee0c75","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 43763-43772 (2019)","raw_type":"article"},{"id":"pmh:oai:scholarworks.indianapolis.iu.edu:1805/23546","is_oa":false,"landing_page_url":"https://hdl.handle.net/1805/23546","pdf_url":null,"source":{"id":"https://openalex.org/S4306400987","display_name":"IUScholarWorks (Indiana University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I592451","host_organization_name":"Indiana University","host_organization_lineage":["https://openalex.org/I592451"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Publisher","raw_type":"Article"},{"id":"pmh:oai:scholarworks.iupui.edu:1805/23546","is_oa":false,"landing_page_url":"http://hdl.handle.net/1805/23546","pdf_url":null,"source":{"id":"https://openalex.org/S4306400987","display_name":"IUScholarWorks (Indiana University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I592451","host_organization_name":"Indiana University","host_organization_lineage":["https://openalex.org/I592451"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Publisher","raw_type":"Article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2906644","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2906644","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":null,"license_id":null,"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/G2081254357","display_name":null,"funder_award_id":"61472022","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2409080664","display_name":null,"funder_award_id":"SKLSDE-2016ZX-11","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W113242008","https://openalex.org/W1576445103","https://openalex.org/W1584412742","https://openalex.org/W1686810756","https://openalex.org/W1873229052","https://openalex.org/W1905307128","https://openalex.org/W1916279783","https://openalex.org/W1985967702","https://openalex.org/W1986332411","https://openalex.org/W1990063425","https://openalex.org/W2003719999","https://openalex.org/W2011494630","https://openalex.org/W2026493302","https://openalex.org/W2041559880","https://openalex.org/W2048974928","https://openalex.org/W2079557269","https://openalex.org/W2107250100","https://openalex.org/W2117839996","https://openalex.org/W2120149881","https://openalex.org/W2129630294","https://openalex.org/W2132175002","https://openalex.org/W2135748228","https://openalex.org/W2143077131","https://openalex.org/W2147331788","https://openalex.org/W2148820067","https://openalex.org/W2148966043","https://openalex.org/W2159570078","https://openalex.org/W2165698076","https://openalex.org/W2296719434","https://openalex.org/W2395916081","https://openalex.org/W2399386490","https://openalex.org/W2551643663","https://openalex.org/W2568618480","https://openalex.org/W2583497309","https://openalex.org/W2613480438","https://openalex.org/W2622411536","https://openalex.org/W2766176203","https://openalex.org/W3143107425","https://openalex.org/W4254182148","https://openalex.org/W4294375521","https://openalex.org/W6604586687","https://openalex.org/W6634343353","https://openalex.org/W6634956364","https://openalex.org/W6639835855","https://openalex.org/W6651275828","https://openalex.org/W6662586080","https://openalex.org/W6676141320","https://openalex.org/W6677408153","https://openalex.org/W6681368692","https://openalex.org/W6682133854","https://openalex.org/W6682778277","https://openalex.org/W6729761961","https://openalex.org/W6732597175","https://openalex.org/W6739262788"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Tremendous":[0],"efforts":[1],"have":[2,131],"been":[3],"invested":[4],"in":[5,162],"the":[6,33,36,42,55,58,74,85,93,109,122,153,159,172,188],"unsupervised":[7,43],"outlier":[8,44,71,139,165],"detection":[9,45,72,140,166],"research,":[10],"which":[11],"is":[12,89,111,175],"conducted":[13],"on":[14,46],"unlabeled":[15],"data":[16,25,39,48,60,63,76,97,103,135],"set":[17],"with":[18,101,121],"abnormality":[19],"assumptions.":[20],"With":[21,105],"abundant":[22],"related":[23],"labeled":[24,37],"available":[26],"as":[27,79,177],"auxiliary":[28],"information,":[29],"we":[30],"consider":[31],"transferring":[32],"knowledge":[34],"from":[35],"source":[38,56,59,75,102,183,196],"to":[40,91,98],"facilitate":[41],"target":[47,62,96],"set.":[49],"To":[50,82],"fully":[51],"make":[52],"use":[53],"of":[54,95,142,158,164],"knowledge,":[57],"and":[61,70,126,137,148,155,167,181],"are":[64],"put":[65],"together":[66],"for":[67,145],"joint":[68],"clustering":[69],"using":[73],"cluster":[77,168],"structure":[78],"a":[80,115,118,178],"constraint.":[81],"achieve":[83],"this,":[84],"categorical":[86],"utility":[87],"function":[88],"employed":[90],"regularize":[92],"partitions":[94],"be":[99,199],"consistent":[100],"labels.":[104],"an":[106],"augmented":[107],"matrix,":[108],"problem":[110],"completely":[112],"solved":[113],"by":[114],"K-means":[116],"-":[117],"based":[119],"method":[120,190],"rigid":[123],"mathematical":[124],"formulation":[125],"theoretical":[127],"convergence":[128],"guarantee.":[129],"We":[130],"used":[132],"four":[133],"real-world":[134],"sets":[136],"eight":[138],"methods":[141,161],"different":[143],"kinds":[144],"extensive":[146],"experiments":[147],"comparison.":[149],"The":[150],"results":[151],"demonstrate":[152],"effectiveness":[154],"significant":[156],"improvements":[157],"proposed":[160,189],"terms":[163],"validity":[169],"metrics.":[170],"Moreover,":[171],"parameter":[173],"analysis":[174,185],"provided":[176],"practical":[179],"guide,":[180],"noisy":[182],"label":[184],"proves":[186],"that":[187],"can":[191,198],"handle":[192],"real":[193],"applications":[194],"where":[195],"labels":[197],"noisy.":[200]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}