{"id":"https://openalex.org/W4403413399","doi":"https://doi.org/10.1145/3674805.3695403","title":"Reducing Events to Augment Log-based Anomaly Detection Models: An Empirical Study","display_name":"Reducing Events to Augment Log-based Anomaly Detection Models: An Empirical Study","publication_year":2024,"publication_date":"2024-10-15","ids":{"openalex":"https://openalex.org/W4403413399","doi":"https://doi.org/10.1145/3674805.3695403"},"language":"en","primary_location":{"id":"doi:10.1145/3674805.3695403","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3674805.3695403","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2409.04834","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028483464","display_name":"Lingzhe Zhang","orcid":"https://orcid.org/0009-0005-9500-4489"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lingzhe Zhang","raw_affiliation_strings":["Peking University, China"],"affiliations":[{"raw_affiliation_string":"Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069358025","display_name":"Tong Jia","orcid":"https://orcid.org/0000-0002-5946-9829"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Jia","raw_affiliation_strings":["Peking University, China"],"affiliations":[{"raw_affiliation_string":"Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Kangjin Wang","orcid":"https://orcid.org/0000-0001-9540-6502"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kangjin Wang","raw_affiliation_strings":["Alibaba Group, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074366979","display_name":"Mengxi Jia","orcid":"https://orcid.org/0000-0002-0979-9803"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengxi Jia","raw_affiliation_strings":["Peking University, China"],"affiliations":[{"raw_affiliation_string":"Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100670362","display_name":"Yong Yang","orcid":"https://orcid.org/0000-0001-9667-2423"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yong Yang","raw_affiliation_strings":["Peking Univerity, China"],"affiliations":[{"raw_affiliation_string":"Peking Univerity, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100414277","display_name":"Ying Li","orcid":"https://orcid.org/0000-0002-6278-2357"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Li","raw_affiliation_strings":["Peking University, China"],"affiliations":[{"raw_affiliation_string":"Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5028483464"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":2.0579,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.88031096,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"538","last_page":"548"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.9998999834060669,"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/T12127","display_name":"Software System Performance and Reliability","score":0.9998999834060669,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9907000064849854,"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":0.9800000190734863,"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/augment","display_name":"Augment","score":0.8057023286819458},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6148608922958374},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6010862588882446},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5016841888427734},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3547899127006531},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33221691846847534}],"concepts":[{"id":"https://openalex.org/C2779070825","wikidata":"https://www.wikidata.org/wiki/Q760434","display_name":"Augment","level":2,"score":0.8057023286819458},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6148608922958374},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6010862588882446},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5016841888427734},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3547899127006531},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33221691846847534},{"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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3674805.3695403","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3674805.3695403","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 18th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2409.04834","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2409.04834","pdf_url":"https://arxiv.org/pdf/2409.04834","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2409.04834","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2409.04834","pdf_url":"https://arxiv.org/pdf/2409.04834","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.6399999856948853}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403413399.pdf","grobid_xml":"https://content.openalex.org/works/W4403413399.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1972020324","https://openalex.org/W1994625872","https://openalex.org/W2015979301","https://openalex.org/W2115056012","https://openalex.org/W2153470728","https://openalex.org/W2536393303","https://openalex.org/W2560021099","https://openalex.org/W2734941459","https://openalex.org/W2754665629","https://openalex.org/W2763526563","https://openalex.org/W2767094836","https://openalex.org/W2947815220","https://openalex.org/W2963999143","https://openalex.org/W2965838158","https://openalex.org/W2999013495","https://openalex.org/W3089589468","https://openalex.org/W3097861059","https://openalex.org/W3134079112","https://openalex.org/W3210131940","https://openalex.org/W4211008139","https://openalex.org/W4221079409","https://openalex.org/W4226065059","https://openalex.org/W4226128225","https://openalex.org/W4255845613","https://openalex.org/W4289533942","https://openalex.org/W4290878423","https://openalex.org/W4367146761","https://openalex.org/W4376288669","https://openalex.org/W4388679869","https://openalex.org/W4399657288"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2912112202","https://openalex.org/W2667207928","https://openalex.org/W4377864969","https://openalex.org/W2972971679"],"abstract_inverted_index":{"As":[0],"software":[1,123],"systems":[2,124],"grow":[3],"increasingly":[4],"intricate,":[5],"the":[6,41,48,70,72,107,114,136,156,166],"precise":[7],"detection":[8,20,52],"of":[9,27,44,50,74,110,116,149,168],"anomalies":[10,82],"have":[11],"become":[12],"both":[13],"essential":[14],"and":[15,34,77,125,130,133,163],"challenging.":[16],"Current":[17],"log-based":[18],"anomaly":[19,51,117,153,171],"methods":[21],"depend":[22],"heavily":[23],"on":[24,47,62],"vast":[25],"amounts":[26],"log":[28,45,75,88,111,150],"data":[29],"leading":[30],"to":[31,145],"inefficient":[32],"inference":[33,158],"potential":[35],"misguidance":[36],"by":[37,160],"noise":[38],"logs.":[39,139],"However,":[40],"quantitative":[42],"effects":[43],"reduction":[46,109],"effectiveness":[49,79],"remain":[53],"unexplored.":[54],"Therefore,":[55],"we":[56,100],"first":[57],"conduct":[58],"a":[59],"comprehensive":[60],"study":[61],"six":[63],"distinct":[64],"models":[65,169],"spanning":[66],"three":[67,86],"datasets.":[68],"Through":[69],"study,":[71],"impact":[73],"quantity":[76],"their":[78],"in":[80,113,135,152],"representing":[81],"is":[83],"qualifies,":[84],"uncovering":[85],"distinctive":[87],"event":[89],"types":[90],"that":[91],"differently":[92],"influence":[93],"model":[94],"performance.":[95],"Drawing":[96],"from":[97],"these":[98],"insights,":[99],"propose":[101],"LogCleaner:":[102],"an":[103],"efficient":[104],"methodology":[105],"for":[106,170],"automatic":[108],"events":[112,151],"context":[115],"detection.":[118,172],"Serving":[119],"as":[120],"middleware":[121],"between":[122],"models,":[126],"LogCleaner":[127],"continuously":[128],"updates":[129],"filters":[131],"anti-events":[132],"duplicative-events":[134],"raw":[137],"generated":[138],"Experimental":[140],"outcomes":[141],"highlight":[142],"LogCleaner\u2019s":[143],"capability":[144],"reduce":[146],"over":[147],"70%":[148],"detection,":[154],"accelerating":[155],"model\u2019s":[157],"speed":[159],"approximately":[161],"300%,":[162],"universally":[164],"improving":[165],"performance":[167]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2024-10-16T00:00:00"}