{"id":"https://openalex.org/W2911630205","doi":"https://doi.org/10.1109/bigdata.2018.8622611","title":"Deep Convolutional Neural Networks for Log Event Classification on Distributed Cluster Systems","display_name":"Deep Convolutional Neural Networks for Log Event Classification on Distributed Cluster Systems","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2911630205","doi":"https://doi.org/10.1109/bigdata.2018.8622611","mag":"2911630205"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2018.8622611","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2018.8622611","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Big Data (Big Data)","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/A5101763273","display_name":"Rui Ren","orcid":"https://orcid.org/0009-0000-3542-2164"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Ren","raw_affiliation_strings":["State Key Laboratory of Computer Architecture, Institute of Computing Technology, CAS, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Computer Architecture, Institute of Computing Technology, CAS, Beijing, China","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053439227","display_name":"Jiechao Cheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiechao Cheng","raw_affiliation_strings":["Xiaomi Technology Co., Ltd., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xiaomi Technology Co., Ltd., Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090372748","display_name":"Yan Yin","orcid":"https://orcid.org/0000-0001-5481-1114"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Yin","raw_affiliation_strings":["State Key Laboratory of Computer Architecture, Institute of Computing Technology, CAS, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Computer Architecture, Institute of Computing Technology, CAS, Beijing, China","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085963553","display_name":"Jianfeng Zhan","orcid":"https://orcid.org/0000-0002-3728-6837"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianfeng Zhan","raw_affiliation_strings":["State Key Laboratory of Computer Architecture, Institute of Computing Technology, CAS, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Computer Architecture, Institute of Computing Technology, CAS, Beijing, China","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100436059","display_name":"Lei Wang","orcid":"https://orcid.org/0000-0003-0184-307X"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Wang","raw_affiliation_strings":["State Key Laboratory of Computer Architecture, Institute of Computing Technology, CAS, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Computer Architecture, Institute of Computing Technology, CAS, Beijing, China","institution_ids":["https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101751661","display_name":"Jinheng Li","orcid":"https://orcid.org/0000-0003-2279-7973"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jinheng Li","raw_affiliation_strings":["Xiaomi Technology Co., Ltd., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xiaomi Technology Co., Ltd., Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033347503","display_name":"Chunjie Luo","orcid":"https://orcid.org/0000-0002-6977-929X"},"institutions":[{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunjie Luo","raw_affiliation_strings":["State Key Laboratory of Computer Architecture, Institute of Computing Technology, CAS, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Computer Architecture, Institute of Computing Technology, CAS, Beijing, China","institution_ids":["https://openalex.org/I4210090176"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1639","last_page":"1646"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9961000084877014,"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":0.9945999979972839,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8055888414382935},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.6563866138458252},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6395159959793091},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6297470331192017},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6020551919937134},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5764045715332031},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5475455522537231},{"id":"https://openalex.org/keywords/troubleshooting","display_name":"Troubleshooting","score":0.5448645353317261},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5115941166877747},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.4795379638671875},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4410938620567322},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41859710216522217},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3412265479564667}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8055888414382935},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.6563866138458252},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6395159959793091},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6297470331192017},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6020551919937134},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5764045715332031},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5475455522537231},{"id":"https://openalex.org/C147494362","wikidata":"https://www.wikidata.org/wiki/Q2078905","display_name":"Troubleshooting","level":2,"score":0.5448645353317261},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5115941166877747},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.4795379638671875},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4410938620567322},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41859710216522217},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3412265479564667},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2018.8622611","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2018.8622611","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1488315845","https://openalex.org/W1521032781","https://openalex.org/W1647671624","https://openalex.org/W1661413208","https://openalex.org/W1930624869","https://openalex.org/W1987454953","https://openalex.org/W1995064042","https://openalex.org/W2005311689","https://openalex.org/W2047111942","https://openalex.org/W2049885667","https://openalex.org/W2095705004","https://openalex.org/W2107461003","https://openalex.org/W2107789863","https://openalex.org/W2118020653","https://openalex.org/W2121122863","https://openalex.org/W2128864022","https://openalex.org/W2130325614","https://openalex.org/W2143220335","https://openalex.org/W2143908786","https://openalex.org/W2144182447","https://openalex.org/W2164405010","https://openalex.org/W2180566385","https://openalex.org/W2271840356","https://openalex.org/W2515007666","https://openalex.org/W2585367509","https://openalex.org/W2754002858","https://openalex.org/W4254182148","https://openalex.org/W6636915900","https://openalex.org/W6640462745","https://openalex.org/W6662081087","https://openalex.org/W6674330103","https://openalex.org/W6680785567","https://openalex.org/W6694517276"],"related_works":["https://openalex.org/W3014434849","https://openalex.org/W3013479934","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W2965782936","https://openalex.org/W3034267371"],"abstract_inverted_index":{"With":[0],"the":[1,76,88,94,98,139,149,170,176,182,205,227],"widespread":[2],"development":[3],"of":[4,75,96,156,172,181,198,232,251],"cloud":[5],"computing,":[6],"cluster":[7,192],"systems":[8],"are":[9,103],"becoming":[10],"increasingly":[11],"complex,":[12],"system":[13,23,42,63,220],"logs":[14,102,221],"is":[15,39,201],"an":[16,31,59],"universal":[17],"and":[18,25,57,72,79,116,137,169,178,211,241],"effective":[19,32,117],"approach":[20,200],"for":[21,35,41,105,143,187],"automatic":[22,60],"management":[24],"troubleshooting.":[26],"Log":[27],"event":[28,101],"classification":[29,62,84,189,196],"as":[30],"preprocessing":[33,119],"method":[34],"log":[36,61,118,145,188],"analysis,":[37],"which":[38,121,203],"helpful":[40],"administrators":[43],"to":[44,82,92,217,254],"locate":[45],"or":[46,51],"predict":[47],"components\u2019":[48],"have":[49],"errors":[50],"failures.In":[52],"this":[53],"paper,":[54],"we":[55,112,152],"design":[56],"implement":[58],"based":[64],"on":[65,191],"deep":[66,109,157,184],"CNN":[67,110,158,185],"(Convolutional":[68],"Neural":[69],"Network)":[70],"models,":[71,111],"take":[73],"advantage":[74],"feature":[77,89,133,244],"engineering":[78,90,245],"learning":[80,150,209,233,256],"algorithm":[81,234],"improve":[83],"performance.":[85],"First,":[86],"in":[87,108,148,237],"step,":[91,151],"address":[93],"problem":[95],"that":[97],"original":[99],"unstructured":[100],"unsuitable":[104],"numerical":[106,131],"calculation":[107],"propose":[113],"a":[114,154],"novel":[115],"method,":[120],"include":[122],"building":[123],"categories":[124],"dictionary":[125],"libraries,":[126],"filtering":[127],"abundant":[128],"information,":[129],"generating":[130],"semantic":[132,140],"vectors":[134],"by":[135,164],"calculating":[136],"combining":[138],"similarity":[141],"values":[142],"filtered":[144],"events.":[146],"Additionally,":[147],"measure":[153],"series":[155],"algorithms":[159],"with":[160,222],"varied":[161],"hyper-parameter":[162],"combinations":[163],"using":[165],"standard":[166],"evaluation":[167],"metrics,":[168],"results":[171],"our":[173,199],"study":[174],"reveal":[175],"advantages":[177],"potential":[179],"capabilities":[180],"proposed":[183],"models":[186],"tasks":[190],"systems.":[193],"The":[194],"optimal":[195],"precision":[197],"98.14%,":[202],"surpasses":[204],"popular":[206],"traditional":[207],"machine":[208],"methods,":[210],"it":[212],"can":[213],"also":[214],"be":[215],"applied":[216],"other":[218],"large-scale":[219],"good":[223],"accuracy.":[224],"Just":[225],"like":[226],"experiment":[228],"results,":[229],"different":[230],"choices":[231],"do":[235],"result":[236],"performance":[238],"numbers":[239],"varying,":[240],"subsequently":[242],"careful":[243],"enables":[246],"promoting":[247],"performances,":[248],"thus":[249],"both":[250],"approaches":[252],"contribute":[253],"best":[255],"model":[257],"finding.":[258]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
