{"id":"https://openalex.org/W2026453187","doi":"https://doi.org/10.1145/2815675.2815679","title":"Opprentice","display_name":"Opprentice","publication_year":2015,"publication_date":"2015-10-27","ids":{"openalex":"https://openalex.org/W2026453187","doi":"https://doi.org/10.1145/2815675.2815679","mag":"2026453187"},"language":"en","primary_location":{"id":"doi:10.1145/2815675.2815679","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2815675.2815679","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2015 Internet Measurement Conference","raw_type":"proceedings-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/A5103325848","display_name":"Dapeng Liu","orcid":"https://orcid.org/0009-0003-2973-9167"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dapeng Liu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101491459","display_name":"Youjian Zhao","orcid":"https://orcid.org/0000-0001-9841-1796"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youjian Zhao","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075634052","display_name":"Haowen Xu","orcid":"https://orcid.org/0000-0003-2841-5788"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haowen Xu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027731066","display_name":"Yongqian Sun","orcid":"https://orcid.org/0000-0003-0266-7899"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongqian Sun","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046419834","display_name":"Dan Pei","orcid":"https://orcid.org/0000-0002-5113-838X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dan Pei","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032782350","display_name":"Jiao Luo","orcid":"https://orcid.org/0000-0001-5349-9675"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiao Luo","raw_affiliation_strings":["Baidu, Beijing, China","Baidu, Beijing, China#TAB#"],"affiliations":[{"raw_affiliation_string":"Baidu, Beijing, China","institution_ids":["https://openalex.org/I98301712"]},{"raw_affiliation_string":"Baidu, Beijing, China#TAB#","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008586170","display_name":"Xiaowei Jing","orcid":"https://orcid.org/0000-0002-6899-3411"},"institutions":[{"id":"https://openalex.org/I130541836","display_name":"Beijing Institute of Petrochemical Technology","ror":"https://ror.org/025s55q11","country_code":"CN","type":"education","lineage":["https://openalex.org/I130541836"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaowei Jing","raw_affiliation_strings":["PetroChina, Beijing, China","PetroChina, Beijing, China#TAB#"],"affiliations":[{"raw_affiliation_string":"PetroChina, Beijing, China","institution_ids":["https://openalex.org/I130541836"]},{"raw_affiliation_string":"PetroChina, Beijing, China#TAB#","institution_ids":["https://openalex.org/I130541836"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101288743","display_name":"Feng Mei","orcid":"https://orcid.org/0000-0002-9042-6632"},"institutions":[{"id":"https://openalex.org/I130541836","display_name":"Beijing Institute of Petrochemical Technology","ror":"https://ror.org/025s55q11","country_code":"CN","type":"education","lineage":["https://openalex.org/I130541836"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mei Feng","raw_affiliation_strings":["PetroChina, Beijing, China","PetroChina, Beijing, China#TAB#"],"affiliations":[{"raw_affiliation_string":"PetroChina, Beijing, China","institution_ids":["https://openalex.org/I130541836"]},{"raw_affiliation_string":"PetroChina, Beijing, China#TAB#","institution_ids":["https://openalex.org/I130541836"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5103325848"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":13.3747,"has_fulltext":false,"cited_by_count":246,"citation_normalized_percentile":{"value":0.98741229,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"211","last_page":"224"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9995999932289124,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.996399998664856,"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":0.7729085087776184},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.6734129786491394},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.5767682790756226},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5531290769577026},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5529070496559143},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4954148530960083},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4656321406364441},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45557019114494324}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7729085087776184},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.6734129786491394},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.5767682790756226},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5531290769577026},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5529070496559143},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4954148530960083},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4656321406364441},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45557019114494324},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2815675.2815679","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2815675.2815679","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2015 Internet Measurement Conference","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":61,"referenced_works":["https://openalex.org/W139044672","https://openalex.org/W273955616","https://openalex.org/W1520812622","https://openalex.org/W1523762189","https://openalex.org/W1594031697","https://openalex.org/W1680392829","https://openalex.org/W1966266075","https://openalex.org/W1968439359","https://openalex.org/W1969384713","https://openalex.org/W1976526581","https://openalex.org/W1980931819","https://openalex.org/W2007562169","https://openalex.org/W2017337590","https://openalex.org/W2017787659","https://openalex.org/W2024760831","https://openalex.org/W2029332168","https://openalex.org/W2029449924","https://openalex.org/W2030553727","https://openalex.org/W2032395777","https://openalex.org/W2040333627","https://openalex.org/W2101234009","https://openalex.org/W2102481563","https://openalex.org/W2117352205","https://openalex.org/W2118978333","https://openalex.org/W2120664731","https://openalex.org/W2121511513","https://openalex.org/W2122646361","https://openalex.org/W2123865948","https://openalex.org/W2127084909","https://openalex.org/W2129976399","https://openalex.org/W2134673568","https://openalex.org/W2136457015","https://openalex.org/W2145073242","https://openalex.org/W2150219914","https://openalex.org/W2154053567","https://openalex.org/W2157578436","https://openalex.org/W2160003408","https://openalex.org/W2161695290","https://openalex.org/W2162344247","https://openalex.org/W2164210932","https://openalex.org/W2165723722","https://openalex.org/W2166858086","https://openalex.org/W2169700960","https://openalex.org/W2216268987","https://openalex.org/W2293322640","https://openalex.org/W2313953460","https://openalex.org/W2404909341","https://openalex.org/W2475730566","https://openalex.org/W2798058877","https://openalex.org/W2901355203","https://openalex.org/W2911964244","https://openalex.org/W2997591727","https://openalex.org/W2998216295","https://openalex.org/W3085162807","https://openalex.org/W4230715394","https://openalex.org/W4246413330","https://openalex.org/W4285719527","https://openalex.org/W4313784310","https://openalex.org/W6610017368","https://openalex.org/W6681651645","https://openalex.org/W6843735874"],"related_works":["https://openalex.org/W2366906938","https://openalex.org/W2349391998","https://openalex.org/W4205655149","https://openalex.org/W2000775715","https://openalex.org/W2074467390","https://openalex.org/W2795393339","https://openalex.org/W2626393719","https://openalex.org/W4390618967","https://openalex.org/W2174745845","https://openalex.org/W2063058012"],"abstract_inverted_index":{"Closely":[0],"monitoring":[1],"service":[2,30,125],"performance":[3,77,90],"and":[4,37,42,101,119,146,173],"detecting":[5],"anomalies":[6,74],"are":[7,86,104],"critical":[8],"for":[9],"Internet-based":[10],"services.":[11],"However,":[12],"even":[13],"though":[14],"dozens":[15],"of":[16,160],"anomaly":[17,96],"detectors":[18,85],"have":[19,165],"been":[20],"proposed":[21,60],"over":[22],"the":[23,73,76,89,99,102,115,120,185],"years,":[24],"deploying":[25],"them":[26],"to":[27,70,88,94,106,112,154,166,182],"a":[28,32,50,80,108,128,139],"given":[29],"remains":[31],"great":[33],"challenge,":[34],"requiring":[35],"manually":[36],"iteratively":[38],"tuning":[39,174],"detector":[40],"parameters":[41],"thresholds.":[43,121],"This":[44],"paper":[45],"tackles":[46],"this":[47],"challenge":[48],"through":[49],"novel":[51],"approach":[52],"based":[53],"on":[54],"supervised":[55],"machine":[56],"learning.":[57],"With":[58],"our":[59],"system,":[61],"Opprentice":[62,133,151],"(Operators'":[63],"apprentice),":[64],"operators'":[65],"only":[66,158],"manual":[67],"work":[68,183],"is":[69],"periodically":[71],"label":[72,155],"in":[75,92,127,157,184],"data":[78,91,156],"with":[79],"convenient":[81],"tool.":[82],"Multiple":[83],"existing":[84],"applied":[87],"parallel":[93],"extract":[95],"features.":[97],"Then":[98],"features":[100],"labels":[103],"used":[105],"train":[107],"random":[109],"forest":[110],"classifier":[111],"automatically":[113,135],"select":[114],"appropriate":[116],"detector-parameter":[117],"combinations":[118],"For":[122],"three":[123],"different":[124],"KPIs":[126],"top":[129],"global":[130],"search":[131],"engine,":[132],"can":[134],"satisfy":[136],"or":[137],"approximate":[138],"reasonable":[140],"accuracy":[141],"preference":[142],"(recall":[143],">=":[144],"0.66":[145],"precision>=":[147],"0.66).":[148],"More":[149],"importantly,":[150],"allows":[152],"operators":[153,163],"tens":[159],"minutes,":[161],"while":[162],"traditionally":[164],"spend":[167],"more":[168],"than":[169],"ten":[170],"days":[171],"selecting":[172],"detectors,":[175],"which":[176],"may":[177],"still":[178],"turn":[179],"out":[180],"not":[181],"end.":[186]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":29},{"year":2023,"cited_by_count":31},{"year":2022,"cited_by_count":47},{"year":2021,"cited_by_count":41},{"year":2020,"cited_by_count":24},{"year":2019,"cited_by_count":26},{"year":2018,"cited_by_count":22},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2016-06-24T00:00:00"}
