{"id":"https://openalex.org/W4224329784","doi":"https://doi.org/10.1145/3534678.3539109","title":"CMMD: Cross-Metric Multi-Dimensional Root Cause Analysis","display_name":"CMMD: Cross-Metric Multi-Dimensional Root Cause Analysis","publication_year":2022,"publication_date":"2022-08-12","ids":{"openalex":"https://openalex.org/W4224329784","doi":"https://doi.org/10.1145/3534678.3539109"},"language":"en","primary_location":{"id":"doi:10.1145/3534678.3539109","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3534678.3539109","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","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":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2203.16280","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062609303","display_name":"Shifu Yan","orcid":"https://orcid.org/0000-0002-3540-4756"},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shifu Yan","raw_affiliation_strings":["East China University of Science and Technology, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"East China University of Science and Technology, Shanghai, China","institution_ids":["https://openalex.org/I143593769"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043558899","display_name":"Caihua Shan","orcid":"https://orcid.org/0000-0001-9012-7088"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Caihua Shan","raw_affiliation_strings":["Microsoft Research Asia, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Shanghai, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087648305","display_name":"Wen\u2010Yi Yang","orcid":"https://orcid.org/0000-0003-1279-0866"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenyi Yang","raw_affiliation_strings":["Microsoft Inc., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Inc., Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064924392","display_name":"Bixiong Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bixiong Xu","raw_affiliation_strings":["Microsoft Inc., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Inc., Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100440914","display_name":"Dongsheng Li","orcid":"https://orcid.org/0000-0002-5135-0778"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongsheng Li","raw_affiliation_strings":["Microsoft Research Asia, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Shanghai, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026749943","display_name":"Lili Qiu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lili Qiu","raw_affiliation_strings":["Microsoft Research Asia, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Shanghai, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101627093","display_name":"Jie Tong","orcid":"https://orcid.org/0009-0009-8036-2901"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Tong","raw_affiliation_strings":["Microsoft Inc., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Inc., Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100784844","display_name":"Qi Zhang","orcid":"https://orcid.org/0000-0002-1037-1361"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Zhang","raw_affiliation_strings":["Microsoft Inc., Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Inc., Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4310","last_page":"4320"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.9990000128746033,"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":0.9990000128746033,"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/T10679","display_name":"Service-Oriented Architecture and Web Services","score":0.9825999736785889,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.9779000282287598,"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/troubleshooting","display_name":"Troubleshooting","score":0.7218320369720459},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7068714499473572},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6757301092147827},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6725127696990967},{"id":"https://openalex.org/keywords/performance-indicator","display_name":"Performance indicator","score":0.6723604798316956},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5671934485435486},{"id":"https://openalex.org/keywords/root-cause-analysis","display_name":"Root cause analysis","score":0.5306557416915894},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.5050223469734192},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5026471614837646},{"id":"https://openalex.org/keywords/performance-metric","display_name":"Performance metric","score":0.48489266633987427},{"id":"https://openalex.org/keywords/root-cause","display_name":"Root cause","score":0.46806374192237854},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41765904426574707},{"id":"https://openalex.org/keywords/root","display_name":"Root (linguistics)","score":0.4144516587257385},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3233235478401184},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17662736773490906},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.1717231571674347},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13899514079093933}],"concepts":[{"id":"https://openalex.org/C147494362","wikidata":"https://www.wikidata.org/wiki/Q2078905","display_name":"Troubleshooting","level":2,"score":0.7218320369720459},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7068714499473572},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6757301092147827},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6725127696990967},{"id":"https://openalex.org/C135510737","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance indicator","level":2,"score":0.6723604798316956},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5671934485435486},{"id":"https://openalex.org/C130963320","wikidata":"https://www.wikidata.org/wiki/Q1401207","display_name":"Root cause analysis","level":2,"score":0.5306557416915894},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.5050223469734192},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5026471614837646},{"id":"https://openalex.org/C2780898871","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance metric","level":2,"score":0.48489266633987427},{"id":"https://openalex.org/C84945661","wikidata":"https://www.wikidata.org/wiki/Q7366567","display_name":"Root cause","level":2,"score":0.46806374192237854},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41765904426574707},{"id":"https://openalex.org/C171078966","wikidata":"https://www.wikidata.org/wiki/Q111029","display_name":"Root (linguistics)","level":2,"score":0.4144516587257385},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3233235478401184},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17662736773490906},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.1717231571674347},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13899514079093933},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3534678.3539109","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3534678.3539109","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","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":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2203.16280","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2203.16280","pdf_url":"https://arxiv.org/pdf/2203.16280","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:2203.16280","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2203.16280","pdf_url":"https://arxiv.org/pdf/2203.16280","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/9","display_name":"Industry, innovation and infrastructure","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1865437296","https://openalex.org/W2047094503","https://openalex.org/W2054526494","https://openalex.org/W2391120767","https://openalex.org/W2794090615","https://openalex.org/W2906498146","https://openalex.org/W2962736999","https://openalex.org/W2963166639","https://openalex.org/W3005725164","https://openalex.org/W3037590075","https://openalex.org/W3080253043","https://openalex.org/W3105115285","https://openalex.org/W3121912665","https://openalex.org/W3163057523","https://openalex.org/W3163635305","https://openalex.org/W3169450514","https://openalex.org/W4246587917","https://openalex.org/W4285723986","https://openalex.org/W4287270621"],"related_works":["https://openalex.org/W2030594396","https://openalex.org/W2754538212","https://openalex.org/W317486986","https://openalex.org/W2490884653","https://openalex.org/W4200610016","https://openalex.org/W2183996497","https://openalex.org/W129587375","https://openalex.org/W2110363179","https://openalex.org/W2056250485","https://openalex.org/W2096582536"],"abstract_inverted_index":{"In":[0],"large-scale":[1],"online":[2,199,219],"services,":[3],"crucial":[4],"metrics,":[5],"a.k.a.,":[6],"key":[7,136],"performance":[8],"indicators":[9],"(KPIs),":[10],"are":[11,21,42,87,104,190],"monitored":[12],"periodically":[13],"to":[14,51,70,80,89,107,111,147,172],"check":[15],"the":[16,35,53,72,82,90,93,98,108,149,169,178,183,187,203],"running":[17,216],"statuses.":[18],"Generally,":[19],"KPIs":[20],"aggregated":[22],"along":[23],"multiple":[24],"dimensions":[25,74,159],"and":[26,96,155,174,181,198],"derived":[27],"by":[28],"complex":[29,151],"calculations":[30],"among":[31,153,158],"fundamental":[32],"metrics":[33,102,154],"from":[34,160],"raw":[36,179],"data.":[37],"Once":[38],"abnormal":[39,94,184],"KPI":[40,188],"values":[41],"observed,":[43],"root":[44,116,126,164],"cause":[45,127,165],"analysis":[46,128],"(RCA)":[47],"can":[48,60],"be":[49],"applied":[50],"identify":[52],"reasons":[54],"for":[55],"anomalies,":[56,109],"so":[57],"that":[58],"we":[59,121],"troubleshoot":[61],"quickly.":[62],"Recently,":[63],"several":[64],"automatic":[65],"RCA":[66],"techniques":[67],"were":[68],"proposed":[69,207],"localize":[71,182],"related":[73,106],"(or":[75],"a":[76,123],"combination":[77],"of":[78,100,134,205],"dimensions)":[79],"explain":[81],"anomalies.":[83],"However,":[84],"their":[85],"analyses":[86],"limited":[88],"data":[91,99,180],"on":[92,193],"metric":[95],"ignore":[97],"other":[101],"which":[103,132,141,167],"also":[105],"leading":[110],"imprecise":[112],"or":[113],"even":[114],"incorrect":[115],"causes.":[117],"To":[118],"this":[119],"end,":[120],"propose":[122],"cross-metric":[124],"multi-dimensional":[125],"method,":[129],"named":[130],"CMMD,":[131],"consists":[133],"two":[135],"components:":[137],"1)":[138],"relationship":[139],"modeling,":[140],"utilizes":[142],"graph":[143],"neural":[144],"network":[145],"(GNN)":[146],"model":[148],"unknown":[150],"calculation":[152],"aggregation":[156],"function":[157],"historical":[161],"data;":[162],"2)":[163],"localization,":[166],"adopts":[168],"genetic":[170],"algorithm":[171],"efficiently":[173],"effectively":[175],"dive":[176],"into":[177],"dimension(s)":[185],"once":[186],"anomalies":[189],"detected.":[191],"Experiments":[192],"synthetic":[194],"datasets,":[195],"real-world":[196],"datasets":[197],"production":[200],"environments":[201],"demonstrate":[202],"superiority":[204],"our":[206],"CMMD":[208,214],"method":[209],"compared":[210],"with":[211],"baselines.":[212],"Currently,":[213],"is":[215],"as":[217],"an":[218],"service":[220],"in":[221],"Microsoft":[222],"Azure.":[223]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}