{"id":"https://openalex.org/W4308086137","doi":"https://doi.org/10.23919/apnoms56106.2022.9919908","title":"Probability Correlation Learning for Anomaly Detection based on Distribution-Constrained Autoencoder","display_name":"Probability Correlation Learning for Anomaly Detection based on Distribution-Constrained Autoencoder","publication_year":2022,"publication_date":"2022-09-28","ids":{"openalex":"https://openalex.org/W4308086137","doi":"https://doi.org/10.23919/apnoms56106.2022.9919908"},"language":"en","primary_location":{"id":"doi:10.23919/apnoms56106.2022.9919908","is_oa":false,"landing_page_url":"https://doi.org/10.23919/apnoms56106.2022.9919908","pdf_url":null,"source":{"id":"https://openalex.org/S4363607423","display_name":"2022 23rd Asia-Pacific Network Operations and Management Symposium (APNOMS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 23rd Asia-Pacific Network Operations and Management Symposium (APNOMS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5068879196","display_name":"Jihua Wu","orcid":"https://orcid.org/0000-0001-8623-8519"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]},{"id":"https://openalex.org/I4392021250","display_name":"State Key Laboratory of Networking and Switching Technology","ror":"https://ror.org/00qtv5q45","country_code":null,"type":"facility","lineage":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jihua Wu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China","State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China","institution_ids":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]},{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100433867","display_name":"Lei Zhang","orcid":"https://orcid.org/0000-0002-0235-8642"},"institutions":[{"id":"https://openalex.org/I4210136246","display_name":"China Telecom (China)","ror":"https://ror.org/03jgnzt20","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210136246"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Zhang","raw_affiliation_strings":["China United Telecommunications Co. Ltd,Beijing,China","China United Telecommunications Co. Ltd, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China United Telecommunications Co. Ltd,Beijing,China","institution_ids":["https://openalex.org/I4210136246"]},{"raw_affiliation_string":"China United Telecommunications Co. Ltd, Beijing, China","institution_ids":["https://openalex.org/I4210136246"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100331624","display_name":"Cong Liu","orcid":"https://orcid.org/0000-0002-9796-1371"},"institutions":[{"id":"https://openalex.org/I180662265","display_name":"China Mobile (China)","ror":"https://ror.org/05gftfe97","country_code":"CN","type":"company","lineage":["https://openalex.org/I180662265"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cong Liu","raw_affiliation_strings":["China Mobile Research Institute,Beijing,China","China Mobile Research Institute, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Mobile Research Institute,Beijing,China","institution_ids":["https://openalex.org/I180662265"]},{"raw_affiliation_string":"China Mobile Research Institute, Beijing, China","institution_ids":["https://openalex.org/I180662265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100406584","display_name":"Qi Qi","orcid":"https://orcid.org/0000-0003-0829-4624"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]},{"id":"https://openalex.org/I4392021250","display_name":"State Key Laboratory of Networking and Switching Technology","ror":"https://ror.org/00qtv5q45","country_code":null,"type":"facility","lineage":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Qi","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China","State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China","institution_ids":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]},{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100432460","display_name":"Jingyu Wang","orcid":"https://orcid.org/0000-0002-2182-2228"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]},{"id":"https://openalex.org/I4392021250","display_name":"State Key Laboratory of Networking and Switching Technology","ror":"https://ror.org/00qtv5q45","country_code":null,"type":"facility","lineage":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyu Wang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China","State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China","institution_ids":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]},{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059152781","display_name":"Tong Xu","orcid":"https://orcid.org/0000-0001-7017-1858"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]},{"id":"https://openalex.org/I4392021250","display_name":"State Key Laboratory of Networking and Switching Technology","ror":"https://ror.org/00qtv5q45","country_code":null,"type":"facility","lineage":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Xu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China","State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China","institution_ids":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]},{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055685073","display_name":"Jianxin Liao","orcid":"https://orcid.org/0000-0003-1486-0573"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]},{"id":"https://openalex.org/I4392021250","display_name":"State Key Laboratory of Networking and Switching Technology","ror":"https://ror.org/00qtv5q45","country_code":null,"type":"facility","lineage":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianxin Liao","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China","State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China","institution_ids":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]},{"raw_affiliation_string":"State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14191015,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9994000196456909,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9983000159263611,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9301999807357788,"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/autoencoder","display_name":"Autoencoder","score":0.8872842192649841},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7346582412719727},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7320349216461182},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.7049224376678467},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6746006608009338},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6665887832641602},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6154016256332397},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.5495034456253052},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49947237968444824},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.49188923835754395},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4817804992198944},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47635865211486816},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4650576710700989},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4459790885448456},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4442984461784363},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.4120088517665863},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35714834928512573},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3336796164512634},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1389145851135254},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07644906640052795}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8872842192649841},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7346582412719727},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7320349216461182},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.7049224376678467},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6746006608009338},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6665887832641602},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6154016256332397},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.5495034456253052},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49947237968444824},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.49188923835754395},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4817804992198944},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47635865211486816},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4650576710700989},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4459790885448456},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4442984461784363},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.4120088517665863},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35714834928512573},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3336796164512634},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1389145851135254},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07644906640052795},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/apnoms56106.2022.9919908","is_oa":false,"landing_page_url":"https://doi.org/10.23919/apnoms56106.2022.9919908","pdf_url":null,"source":{"id":"https://openalex.org/S4363607423","display_name":"2022 23rd Asia-Pacific Network Operations and Management Symposium (APNOMS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 23rd Asia-Pacific Network Operations and Management Symposium (APNOMS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7599999904632568,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G4249793757","display_name":null,"funder_award_id":"2020YFB1807800","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G7444792572","display_name":null,"funder_award_id":"2022M710468","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2983142544","https://openalex.org/W2891059443","https://openalex.org/W4281663961","https://openalex.org/W3208888551","https://openalex.org/W4313561566","https://openalex.org/W3208386644","https://openalex.org/W4389832810","https://openalex.org/W4220682630","https://openalex.org/W3181622257","https://openalex.org/W3163146846"],"abstract_inverted_index":{"Network":[0],"anomaly":[1,33,85,148],"detection":[2,19],"provides":[3],"a":[4,45,67,77,146,217],"reliable":[5],"and":[6,12,38,134,159,184,197,211],"stable":[7],"service":[8],"to":[9,40,107,125,139,168],"detect":[10],"faults":[11],"prevent":[13],"security":[14],"attacks":[15],"effectively.":[16],"However,":[17],"existing":[18],"methods":[20],"still":[21],"encounter":[22],"many":[23],"challenges.":[24],"The":[25,153],"supervised":[26,204],"learning":[27,71,79,205],"method":[28],"is":[29,48,100,123],"unsuitable":[30],"because":[31],"the":[32,52,60,84,89,95,109,119,127,136,156,160,170,188,195,209,213],"samples":[34,86],"are":[35,55,176],"seriously":[36],"sparse":[37],"hard":[39],"label.":[41],"Unsupervised":[42],"learning,":[43],"as":[44,102,216],"promising":[46],"method,":[47],"widely":[49],"used":[50,167],"while":[51],"discriminative":[53,110],"features":[54],"ignored":[56],"when":[57],"reconstructing":[58],"from":[59,88,131],"normal":[61,92],"feature":[62,129],"space.":[63],"This":[64],"paper":[65],"proposes":[66],"novel":[68],"probability":[69,171],"correlation":[70,154],"based":[72,144],"on":[73,145,178],"autoencoder":[74],"called":[75],"PCDetect,":[76],"semi-supervised":[78],"method.":[80],"Since":[81],"we":[82],"assumed":[83],"deviate":[87],"distribution":[90,96,158],"of":[91,97,155,162,172],"samples,":[93],"approximating":[94],"original":[98],"data":[99,133],"proposed":[101,120,189],"an":[103,113],"efficient":[104],"preprocessing":[105],"methodology":[106],"capture":[108],"features.":[111],"Moreover,":[112],"encoder-decoder":[114],"neural":[115],"network":[116],"associated":[117],"with":[118,194,201,220],"loss":[121],"function":[122],"designed":[124],"learn":[126],"low-dimensional":[128],"representation":[130,138,164],"raw":[132],"constrain":[135],"latent":[137,163],"follow":[140],"different":[141],"referenced":[142,157],"distributions":[143],"few":[147],"labels.":[149],"In":[150],"this":[151],"way,":[152],"reconstruction":[161],"will":[165],"be":[166],"quantify":[169],"anomaly.":[173],"Extensive":[174],"experiments":[175],"conducted":[177],"two":[179],"public":[180],"real-world":[181],"datasets,":[182],"NSL-KDD":[183],"UNSW-NB15.":[185],"Results":[186],"show":[187],"PCDetect":[190],"can":[191],"efficiently":[192],"cope":[193],"imbalance":[196],"high-dimensional":[198],"issues":[199],"compared":[200,219],"several":[202],"popular":[203],"methods,":[206],"significantly":[207],"improve":[208],"accuracy,":[210],"reduce":[212],"false":[214],"rate":[215],"whole":[218],"unsupervised":[221],"learning.":[222]},"counts_by_year":[],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}