{"id":"https://openalex.org/W4308796807","doi":"https://doi.org/10.3233/jcm-226537","title":"Clustering mining method of large-scale network abnormal data based on selective collaborative learning","display_name":"Clustering mining method of large-scale network abnormal data based on selective collaborative learning","publication_year":2022,"publication_date":"2022-11-11","ids":{"openalex":"https://openalex.org/W4308796807","doi":"https://doi.org/10.3233/jcm-226537"},"language":"en","primary_location":{"id":"doi:10.3233/jcm-226537","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jcm-226537","pdf_url":null,"source":{"id":"https://openalex.org/S2765058733","display_name":"Journal of Computational Methods in Sciences and Engineering","issn_l":"1472-7978","issn":["1472-7978","1875-8983"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational Methods in Sciences and Engineering","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/A5101647976","display_name":"Haiou Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Hai\u2019ou Zhang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5101647976"],"corresponding_institution_ids":[],"apc_list":{"value":4150,"currency":"USD","value_usd":4150},"apc_paid":null,"fwci":0.1243,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.56783992,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"23","issue":"1","first_page":"9","last_page":"21"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9995999932289124,"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":0.9995999932289124,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11819","display_name":"Data-Driven Disease Surveillance","score":0.968999981880188,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8312309980392456},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.7455434799194336},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7115395069122314},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.6274093985557556},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.6266798973083496},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.579501748085022},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.5616729259490967},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.541513979434967},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.4834902882575989},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.461141437292099},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.4210607409477234},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34323230385780334},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33346614241600037}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8312309980392456},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.7455434799194336},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7115395069122314},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.6274093985557556},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.6266798973083496},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.579501748085022},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.5616729259490967},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.541513979434967},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.4834902882575989},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.461141437292099},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.4210607409477234},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34323230385780334},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33346614241600037}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jcm-226537","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jcm-226537","pdf_url":null,"source":{"id":"https://openalex.org/S2765058733","display_name":"Journal of Computational Methods in Sciences and Engineering","issn_l":"1472-7978","issn":["1472-7978","1875-8983"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational Methods in Sciences and Engineering","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":8,"referenced_works":["https://openalex.org/W2766761849","https://openalex.org/W2998788668","https://openalex.org/W3007395614","https://openalex.org/W3088611441","https://openalex.org/W3102387010","https://openalex.org/W3149467830","https://openalex.org/W6764817826","https://openalex.org/W6774607112"],"related_works":["https://openalex.org/W2559422900","https://openalex.org/W3144143113","https://openalex.org/W2491448268","https://openalex.org/W2892323093","https://openalex.org/W4306940721","https://openalex.org/W2181939267","https://openalex.org/W3174322327","https://openalex.org/W2160785859","https://openalex.org/W2394193399","https://openalex.org/W4301002638"],"abstract_inverted_index":{"In":[0],"order":[1],"to":[2,75,98,139],"improve":[3,146],"the":[4,10,21,68,77,92,100,119,130,147],"accuracy":[5,113],"and":[6,19,47,57,67,91,129],"recall":[7,131],"rate":[8,132],"of":[9,14,23,80,103,114,121,133,149],"clustering":[11,24,34,101,111,123,135,154],"mining":[12,35,102,112,124,136],"process":[13],"large-scale":[15,30,62,150],"network":[16,31,63,83,106,151],"abnormal":[17],"data":[18,33,64,85,110,122,134,153],"shorten":[20],"time":[22,120],"mining,":[25],"in":[26],"this":[27,115,143],"study,":[28],"a":[29,51,58],"anomaly":[32,54,84,107,152],"method":[36,72,116,144],"based":[37],"on":[38],"selective":[39,48],"collaborative":[40],"learning":[41,53],"is":[42,73,86,96,125,137],"proposed.":[43],"Through":[44],"cooperative":[45],"training":[46],"ensemble":[49],"learning,":[50],"machine":[52],"detection":[55],"model":[56],"strong":[59],"classifier":[60],"for":[61],"are":[65],"designed,":[66],"correlation":[69],"variable":[70],"analysis":[71],"used":[74,97],"obtain":[76],"dissimilarity":[78],"measure":[79],"data.":[81,108],"The":[82,109],"processed":[87],"by":[88],"fuzzy":[89],"fusion,":[90],"nearest":[93],"neighbor":[94],"algorithm":[95],"realize":[99],"large":[104],"scale":[105],"reaches":[117],"98.16%,":[118],"only":[126],"2.5":[127],"s,":[128],"up":[138],"98.38%,":[140],"indicating":[141],"that":[142],"can":[145],"effect":[148],"mining.":[155]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}