{"id":"https://openalex.org/W2003787915","doi":"https://doi.org/10.1109/tkde.2014.2310219","title":"Discovery of Temporal Associations in Multivariate Time Series","display_name":"Discovery of Temporal Associations in Multivariate Time Series","publication_year":2014,"publication_date":"2014-03-11","ids":{"openalex":"https://openalex.org/W2003787915","doi":"https://doi.org/10.1109/tkde.2014.2310219","mag":"2003787915"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2014.2310219","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2014.2310219","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-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/A5072016362","display_name":"Dennis Zhuang","orcid":null},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Dennis E.H. Zhuang","raw_affiliation_strings":["Systems Design Engineering Department, University of Waterloo, Waterloo, ON, Canada","Systems Design Engineering Department, University of Waterloo, Waterloo, Canada#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Systems Design Engineering Department, University of Waterloo, Waterloo, ON, Canada","institution_ids":["https://openalex.org/I151746483"]},{"raw_affiliation_string":"Systems Design Engineering Department, University of Waterloo, Waterloo, Canada#TAB#","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015733852","display_name":"Gary C.L. Li","orcid":null},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Gary C.L. Li","raw_affiliation_strings":["Systems Design Engineering Department, University of Waterloo, Waterloo, ON, Canada","Systems Design Engineering Department, University of Waterloo, Waterloo, Canada#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Systems Design Engineering Department, University of Waterloo, Waterloo, ON, Canada","institution_ids":["https://openalex.org/I151746483"]},{"raw_affiliation_string":"Systems Design Engineering Department, University of Waterloo, Waterloo, Canada#TAB#","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051841038","display_name":"Andrew K. C. Wong","orcid":"https://orcid.org/0000-0002-0019-7152"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Andrew K. C. Wong","raw_affiliation_strings":["Systems Design Engineering Department, University of Waterloo, Waterloo, ON, Canada","Systems Design Engineering Department, University of Waterloo, Waterloo, Canada#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Systems Design Engineering Department, University of Waterloo, Waterloo, ON, Canada","institution_ids":["https://openalex.org/I151746483"]},{"raw_affiliation_string":"Systems Design Engineering Department, University of Waterloo, Waterloo, Canada#TAB#","institution_ids":["https://openalex.org/I151746483"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.128,"has_fulltext":false,"cited_by_count":47,"citation_normalized_percentile":{"value":0.94571608,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"26","issue":"12","first_page":"2969","last_page":"2982"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9717000126838684,"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/T11106","display_name":"Data Management and Algorithms","score":0.9488999843597412,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.7701176404953003},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.723089337348938},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.6157234907150269},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5625466108322144},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.5605413913726807},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5500999689102173},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.5215161442756653},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5087524056434631},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35310420393943787},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32939279079437256}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7701176404953003},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.723089337348938},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.6157234907150269},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5625466108322144},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.5605413913726807},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5500999689102173},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.5215161442756653},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5087524056434631},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35310420393943787},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32939279079437256},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2014.2310219","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2014.2310219","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.4300000071525574,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W34835763","https://openalex.org/W87191022","https://openalex.org/W132159265","https://openalex.org/W151863654","https://openalex.org/W1486996222","https://openalex.org/W1505947825","https://openalex.org/W1554137149","https://openalex.org/W1984052046","https://openalex.org/W1995093154","https://openalex.org/W2006761268","https://openalex.org/W2007033345","https://openalex.org/W2015287930","https://openalex.org/W2030132106","https://openalex.org/W2049704739","https://openalex.org/W2051664277","https://openalex.org/W2106595237","https://openalex.org/W2109227373","https://openalex.org/W2120905266","https://openalex.org/W2160119185","https://openalex.org/W2164274563","https://openalex.org/W2164755273","https://openalex.org/W2166488058","https://openalex.org/W4213009331","https://openalex.org/W6601369054","https://openalex.org/W6603498666","https://openalex.org/W6606194391","https://openalex.org/W6630265910"],"related_works":["https://openalex.org/W2389214306","https://openalex.org/W2373300491","https://openalex.org/W2406638334","https://openalex.org/W2965083567","https://openalex.org/W4235240664","https://openalex.org/W2378744544","https://openalex.org/W2757182831","https://openalex.org/W2594301978","https://openalex.org/W1838576100","https://openalex.org/W2295196644"],"abstract_inverted_index":{"Multivariate":[0],"time":[1,44,82,137,169],"series":[2,83,138,170],"are":[3,154],"common":[4],"in":[5,10,42,80,167],"many":[6],"application":[7],"domains,":[8],"particularly":[9],"industrial":[11],"processes":[12],"with":[13],"a":[14,37,53,129,144,150],"large":[15,145,179],"number":[16],"of":[17,40,56,78,93,103],"sensors":[18],"installed":[19],"for":[20,114],"process":[21],"monitoring":[22],"and":[23,60,84,100,116,128,171],"control.":[24],"Often,":[25],"such":[26],"data":[27,126,132,146,180],"encapsulate":[28],"complex":[29],"relations":[30,58,166],"among":[31],"individual":[32,62],"series.":[33,63],"This":[34],"paper":[35],"presents":[36],"new":[38],"type":[39],"patterns":[41,79],"multivariate":[43],"series,":[45],"referred":[46],"to":[47,51,69,88,178],"as":[48,141,143],"temporal":[49],"associations,":[50,94],"capture":[52,163],"wide":[54],"range":[55],"local":[57,165],"along":[59],"across":[61],"A":[64,107],"scalable":[65,177],"algorithm":[66],"is":[67,111,176],"developed":[68],"discover":[70],"frequent":[71],"associations":[72,162],"by":[73],"incorporating":[74],"(1)":[75],"redundancy":[76],"pruning":[77],"single":[81],"(2)":[85],"two":[86],"conditions":[87],"avoid":[89],"over-counting":[90],"the":[91,98,104,122,136,160,164,173],"occurrences":[92],"thus":[95],"greatly":[96],"reducing":[97],"space":[99],"runtime":[101],"complexity":[102],"discovery":[105],"process.":[106],"statistical":[108],"significance":[109],"measure":[110],"also":[112],"introduced":[113],"ranking":[115],"post-pruning":[117],"discovered":[118,161],"associations.":[119],"To":[120],"evaluate":[121],"proposed":[123,174],"method,":[124],"synthetic":[125],"sets":[127],"real":[130],"world":[131],"set":[133,147],"taken":[134],"from":[135,149],"mining":[139],"repository":[140],"well":[142],"obtained":[148],"delayed":[151],"coking":[152],"plant":[153],"used.":[155],"The":[156],"experiments":[157],"demonstrated":[158],"that":[159,172],"multiple":[168],"method":[175],"sets.":[181]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}