{"id":"https://openalex.org/W3116539649","doi":"https://doi.org/10.1145/3430984.3431027","title":"Evaluation of Causal Inference Techniques for AIOps","display_name":"Evaluation of Causal Inference Techniques for AIOps","publication_year":2020,"publication_date":"2020-12-28","ids":{"openalex":"https://openalex.org/W3116539649","doi":"https://doi.org/10.1145/3430984.3431027","mag":"3116539649"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3430984.3431027","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5056759720","display_name":"Vijay Arya","orcid":"https://orcid.org/0000-0001-8892-6761"},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vijay Arya","raw_affiliation_strings":["IBM Research AI, India"],"affiliations":[{"raw_affiliation_string":"IBM Research AI, India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021188761","display_name":"Karthikeyan Shanmugam","orcid":"https://orcid.org/0009-0008-2879-5868"},"institutions":[],"countries":["US"],"is_corresponding":false,"raw_author_name":"Karthikeyan Shanmugam","raw_affiliation_strings":["IBM Research AI, USA"],"affiliations":[{"raw_affiliation_string":"IBM Research AI, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103269540","display_name":"Pooja Aggarwal","orcid":null},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Pooja Aggarwal","raw_affiliation_strings":["IBM Research AI, India"],"affiliations":[{"raw_affiliation_string":"IBM Research AI, India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100434829","display_name":"Qing Wang","orcid":"https://orcid.org/0000-0002-4021-3372"},"institutions":[],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qing Wang","raw_affiliation_strings":["IBM Research AI, USA"],"affiliations":[{"raw_affiliation_string":"IBM Research AI, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109508156","display_name":"Prateeti Mohapatra","orcid":null},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Prateeti Mohapatra","raw_affiliation_strings":["IBM Research AI, India"],"affiliations":[{"raw_affiliation_string":"IBM Research AI, India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112259408","display_name":"Seema Nagar","orcid":null},"institutions":[{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Seema Nagar","raw_affiliation_strings":["IBM Research AI, India"],"affiliations":[{"raw_affiliation_string":"IBM Research AI, India","institution_ids":["https://openalex.org/I4210103279"]}]}],"institution_assertions":[],"countries_distinct_count":2,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.893,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.878062,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":86,"max":87},"biblio":{"volume":null,"issue":null,"first_page":"188","last_page":"192"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.9999,"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":0.9999,"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/T11719","display_name":"Data Quality and Management","score":0.988,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12423","display_name":"Software Reliability and Analysis Research","score":0.9729,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/benchmark","display_name":"Benchmark (surveying)","score":0.7061956},{"id":"https://openalex.org/keywords/independence","display_name":"Independence","score":0.45114988},{"id":"https://openalex.org/keywords/causality","display_name":"Causality","score":0.45025176}],"concepts":[{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.751042},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7061956},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6451642},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.64046806},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5996017},{"id":"https://openalex.org/C129824826","wikidata":"https://www.wikidata.org/wiki/Q2630107","display_name":"Granger causality","level":2,"score":0.54917717},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5389854},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5255574},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.45246458},{"id":"https://openalex.org/C35651441","wikidata":"https://www.wikidata.org/wiki/Q625303","display_name":"Independence (probability theory)","level":2,"score":0.45114988},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.45025176},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.42275202},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4099341},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40947077},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3657009},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.32999998},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21286842},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1145/3430984.3431027","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.57,"display_name":"Peace, justice, and strong institutions"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":28,"referenced_works":["https://openalex.org/W1975062332","https://openalex.org/W1982652137","https://openalex.org/W2009271606","https://openalex.org/W2066400502","https://openalex.org/W2116031726","https://openalex.org/W2118418963","https://openalex.org/W2137966242","https://openalex.org/W2143891888","https://openalex.org/W2155573334","https://openalex.org/W2165190832","https://openalex.org/W2178225550","https://openalex.org/W2189356200","https://openalex.org/W2270502030","https://openalex.org/W2271473378","https://openalex.org/W2400086527","https://openalex.org/W2584518841","https://openalex.org/W2767094836","https://openalex.org/W2771013155","https://openalex.org/W2803956134","https://openalex.org/W2809376319","https://openalex.org/W2884025810","https://openalex.org/W2892226239","https://openalex.org/W2903799441","https://openalex.org/W2963675110","https://openalex.org/W2964132737","https://openalex.org/W2966971704","https://openalex.org/W2981462108","https://openalex.org/W4389077320"],"related_works":["https://openalex.org/W4320159092","https://openalex.org/W4251418261","https://openalex.org/W2977645287","https://openalex.org/W2574301230","https://openalex.org/W2510029442","https://openalex.org/W2154758532","https://openalex.org/W2035792466","https://openalex.org/W1972675643","https://openalex.org/W1547624382","https://openalex.org/W126301054"],"abstract_inverted_index":{"Inferring":[0],"causality":[1],"of":[2,21,61,77,102,115],"events":[3,22],"from":[4,87],"log":[5,53,84,96],"data":[6,85,97],"is":[7],"critical":[8],"to":[9,16,25,38,57,145],"IT":[10],"operations":[11],"teams":[12],"who":[13],"continuously":[14],"strive":[15],"identify":[17],"probable":[18],"root":[19],"causes":[20],"in":[23,143],"order":[24],"quickly":[26],"resolve":[27],"incident":[28],"tickets":[29],"so":[30],"that":[31,131,137],"downtimes":[32],"and":[33,105,111,124,141,147],"service":[34],"interruptions":[35],"are":[36],"kept":[37],"a":[39,65,88,100,107],"minimum.":[40],"Although":[41],"prior":[42],"work":[43],"has":[44],"applied":[45],"some":[46],"specific":[47],"causal":[48,80,117,135],"inference":[49,81],"techniques":[50,63,82],"on":[51,64],"proprietary":[52],"data,":[54],"they":[55],"fail":[56],"benchmark":[58,91],"the":[59,75],"performance":[60,76],"different":[62],"common":[66],"system":[67],"or":[68],"dataset.":[69],"In":[70],"this":[71],"work,":[72],"we":[73],"evaluate":[74,112],"multiple":[78],"state-of-the-art":[79],"using":[83],"obtained":[86],"publicly":[89],"available":[90],"microservice":[92],"system.":[93],"We":[94],"model":[95],"both":[98],"as":[99,106],"timeseries":[101],"error":[103],"counts":[104],"temporal":[108],"event":[109,125,132],"sequence":[110],"3":[113],"families":[114],"Granger":[116,151],"techniques:":[118],"regression":[119,146],"based,":[120,123],"independence":[121,148],"testing":[122,149],"models.":[126],"Our":[127],"preliminary":[128],"results":[129],"indicate":[130],"models":[133],"yield":[134],"graphs":[136],"have":[138],"high":[139],"precision":[140],"recall":[142],"comparison":[144],"based":[150],"methods.":[152]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W3116539649","counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2}],"updated_date":"2025-03-22T15:40:11.804789","created_date":"2021-01-05"}