{"id":"https://openalex.org/W4313492087","doi":"https://doi.org/10.1145/3570991.3570998","title":"Global Explanations for Multivariate time series models","display_name":"Global Explanations for Multivariate time series models","publication_year":2023,"publication_date":"2023-01-04","ids":{"openalex":"https://openalex.org/W4313492087","doi":"https://doi.org/10.1145/3570991.3570998"},"language":"en","primary_location":{"id":"doi:10.1145/3570991.3570998","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3570991.3570998","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th Joint International Conference on Data Science & Management of Data (10th ACM IKDD CODS and 28th COMAD)","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/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, India"],"raw_orcid":"https://orcid.org/0000-0001-8892-6761","affiliations":[{"raw_affiliation_string":"IBM Research, India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010368277","display_name":"Diptikalyan Saha","orcid":"https://orcid.org/0000-0002-1583-5479"},"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":"Diptikalyan Saha","raw_affiliation_strings":["IBM Research, India"],"raw_orcid":"https://orcid.org/0000-0002-1583-5479","affiliations":[{"raw_affiliation_string":"IBM Research, India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039554087","display_name":"Sandeep Hans","orcid":"https://orcid.org/0000-0003-4986-0688"},"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":"Sandeep Hans","raw_affiliation_strings":["IBM Research, India"],"raw_orcid":"https://orcid.org/0000-0003-4986-0688","affiliations":[{"raw_affiliation_string":"IBM Research, India","institution_ids":["https://openalex.org/I4210103279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034124899","display_name":"Amaresh Rajasekharan","orcid":"https://orcid.org/0000-0002-6408-259X"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amaresh Rajasekharan","raw_affiliation_strings":["IBM Software, USA"],"raw_orcid":"https://orcid.org/0000-0002-6408-259X","affiliations":[{"raw_affiliation_string":"IBM Software, USA","institution_ids":["https://openalex.org/I1341412227"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009996443","display_name":"Tony Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tony Tang","raw_affiliation_strings":["IBM Software, USA"],"raw_orcid":"https://orcid.org/0000-0002-9564-5690","affiliations":[{"raw_affiliation_string":"IBM Software, USA","institution_ids":["https://openalex.org/I1341412227"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"149","last_page":"157"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9962999820709229,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9962999820709229,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.977400004863739,"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/T14351","display_name":"Statistical and Computational Modeling","score":0.9675999879837036,"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/multivariate-statistics","display_name":"Multivariate statistics","score":0.703167200088501},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6610276699066162},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6342670321464539},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5738610029220581},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3275168538093567},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2373267412185669},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.10701096057891846}],"concepts":[{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.703167200088501},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6610276699066162},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6342670321464539},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5738610029220581},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3275168538093567},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2373267412185669},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.10701096057891846},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3570991.3570998","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3570991.3570998","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th Joint International Conference on Data Science & Management of Data (10th ACM IKDD CODS and 28th COMAD)","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":24,"referenced_works":["https://openalex.org/W1670263352","https://openalex.org/W2048231652","https://openalex.org/W2064675550","https://openalex.org/W2120841219","https://openalex.org/W2142561902","https://openalex.org/W2282821441","https://openalex.org/W2367397349","https://openalex.org/W2417749301","https://openalex.org/W2618851150","https://openalex.org/W2914304175","https://openalex.org/W2962862931","https://openalex.org/W2963847595","https://openalex.org/W2964010366","https://openalex.org/W2964716450","https://openalex.org/W2981731882","https://openalex.org/W3013149459","https://openalex.org/W3048102985","https://openalex.org/W3081435493","https://openalex.org/W3116286104","https://openalex.org/W3116868303","https://openalex.org/W3121603028","https://openalex.org/W3138819813","https://openalex.org/W4240187149","https://openalex.org/W4295827631"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2118640767","https://openalex.org/W2119012848","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"Several":[0],"explainable":[1],"AI":[2,50,109],"algorithms":[3],"have":[4],"been":[5],"proposed":[6,149],"to":[7,44,75,101,158],"help":[8],"make":[9],"machine":[10],"learning":[11],"models":[12,110],"more":[13],"interpretable":[14,131],"and":[15,34,161,171],"trustworthy.":[16],"However":[17],"in":[18,84],"spite":[19],"of":[20,58,88,168,174,181],"numerous":[21],"methodological":[22],"advancements,":[23],"there":[24],"is":[25],"still":[26],"a":[27,72,103,120,129,172],"persistent":[28],"gap":[29,47],"between":[30],"what":[31,35],"researchers":[32],"develop":[33],"business":[36,159],"users":[37,160],"seek.":[38],"In":[39],"this":[40,46,99],"work,":[41],"we":[42],"aim":[43],"bridge":[45],"for":[48,108],"an":[49,59,169,182],"system":[51],"that":[52,111,123,133,147,155],"predicts":[53],"the":[54,89,95,142,148,166,177],"remaining":[55,178],"useful":[56,179],"life":[57,180],"aircraft\u2019s":[60,183],"engine":[61],"using":[62],"time":[63,114],"series":[64,115],"data":[65],"collected":[66],"from":[67],"multiple":[68],"sensors.":[69],"We":[70,97],"propose":[71],"novel":[73],"approach":[74,100,118],"compute":[76],"easily":[77],"understandable":[78],"explanations":[79,87,154],"by":[80,94],"fusing":[81],"two":[82],"explainers":[83],"sequence":[85],"wherein":[86],"first":[90],"explainer":[91,107,122,151],"are":[92,156],"explained":[93],"second.":[96],"use":[98],"build":[102],"global":[104,135,153],"post-hoc":[105],"model-agnostic":[106],"ingest":[112],"multivariate":[113],"data.":[116],"Our":[117,137],"fuses":[119],"local":[121],"yields":[124],"feature":[125],"importance":[126],"weights,":[127],"with":[128],"directly":[130],"model":[132],"outputs":[134],"rules.":[136],"experimental":[138],"results":[139],"based":[140],"on":[141,164],"C-MAPSS":[143],"open-source":[144],"dataset":[145],"demonstrate":[146],"two-stage":[150],"computes":[152],"amenable":[157],"sheds":[162],"light":[163],"how":[165],"behavior":[167],"individual":[170],"group":[173],"sensors":[175],"impacts":[176],"engine.":[184]},"counts_by_year":[{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}