{"id":"https://openalex.org/W4401326695","doi":"https://doi.org/10.1109/tkde.2024.3438259","title":"Online Learning of Temporal Association Rule on Dynamic Multivariate Time Series Data","display_name":"Online Learning of Temporal Association Rule on Dynamic Multivariate Time Series Data","publication_year":2024,"publication_date":"2024-08-05","ids":{"openalex":"https://openalex.org/W4401326695","doi":"https://doi.org/10.1109/tkde.2024.3438259"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2024.3438259","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2024.3438259","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/A5060931310","display_name":"Guoliang He","orcid":"https://orcid.org/0000-0002-9637-2006"},"institutions":[{"id":"https://openalex.org/I158934434","display_name":"Zhongnan University of Economics and Law","ror":"https://ror.org/04yqxxq63","country_code":"CN","type":"education","lineage":["https://openalex.org/I158934434"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guoliang He","raw_affiliation_strings":["School of Information Engineering, Zhongnan University of Economics and Law, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Zhongnan University of Economics and Law, Wuhan, China","institution_ids":["https://openalex.org/I158934434"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016193325","display_name":"Dawei Jin","orcid":"https://orcid.org/0000-0002-5922-2746"},"institutions":[{"id":"https://openalex.org/I158934434","display_name":"Zhongnan University of Economics and Law","ror":"https://ror.org/04yqxxq63","country_code":"CN","type":"education","lineage":["https://openalex.org/I158934434"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dawei Jin","raw_affiliation_strings":["School of Information Engineering, Zhongnan University of Economics and Law, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Zhongnan University of Economics and Law, Wuhan, China","institution_ids":["https://openalex.org/I158934434"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101088954","display_name":"Lifang Dai","orcid":null},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lifang Dai","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100393251","display_name":"Xin Xin","orcid":"https://orcid.org/0000-0003-2662-5087"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Xin","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100701158","display_name":"Zhiwen Yu","orcid":"https://orcid.org/0000-0002-0935-5890"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiwen Yu","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100643265","display_name":"C. L. Philip Chen","orcid":"https://orcid.org/0000-0001-5451-7230"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"C. L. Philip Chen","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5060931310"],"corresponding_institution_ids":["https://openalex.org/I158934434"],"apc_list":null,"apc_paid":null,"fwci":1.8191,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.85682575,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"36","issue":"12","first_page":"8954","last_page":"8966"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9991999864578247,"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":0.9991999864578247,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9904999732971191,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9775000214576721,"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":0.7857184410095215},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6510908007621765},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.6207953691482544},{"id":"https://openalex.org/keywords/association-rule-learning","display_name":"Association rule learning","score":0.5911288857460022},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5720421075820923},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4995880126953125},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43350738286972046},{"id":"https://openalex.org/keywords/association","display_name":"Association (psychology)","score":0.41495904326438904},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38715076446533203}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7857184410095215},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6510908007621765},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.6207953691482544},{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.5911288857460022},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5720421075820923},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4995880126953125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43350738286972046},{"id":"https://openalex.org/C142853389","wikidata":"https://www.wikidata.org/wiki/Q744778","display_name":"Association (psychology)","level":2,"score":0.41495904326438904},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38715076446533203},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2024.3438259","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2024.3438259","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":[],"awards":[{"id":"https://openalex.org/G2377544513","display_name":null,"funder_award_id":"62276194","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W2030441459","https://openalex.org/W2572767459","https://openalex.org/W2592873974","https://openalex.org/W2730647291","https://openalex.org/W2760494456","https://openalex.org/W2765810025","https://openalex.org/W2771076441","https://openalex.org/W2775582110","https://openalex.org/W2791944991","https://openalex.org/W2796157539","https://openalex.org/W2799590445","https://openalex.org/W2806596078","https://openalex.org/W2890248913","https://openalex.org/W2905470952","https://openalex.org/W2912241484","https://openalex.org/W2920971266","https://openalex.org/W2938764606","https://openalex.org/W2940108991","https://openalex.org/W2941399075","https://openalex.org/W2963122061","https://openalex.org/W2963919481","https://openalex.org/W2969974905","https://openalex.org/W2978873084","https://openalex.org/W2988873313","https://openalex.org/W2998109735","https://openalex.org/W3003614699","https://openalex.org/W3003716813","https://openalex.org/W3004342364","https://openalex.org/W3006387314","https://openalex.org/W3009327741","https://openalex.org/W3013371665","https://openalex.org/W3015645915","https://openalex.org/W3028571058","https://openalex.org/W3034196639","https://openalex.org/W3037724880","https://openalex.org/W3040166285","https://openalex.org/W3042591854","https://openalex.org/W3048352656","https://openalex.org/W3048624083","https://openalex.org/W3049085523","https://openalex.org/W3089030408","https://openalex.org/W3089117462","https://openalex.org/W3103904664","https://openalex.org/W3104004122","https://openalex.org/W3108781044","https://openalex.org/W3109653641","https://openalex.org/W3120740533","https://openalex.org/W3132834202","https://openalex.org/W3173748501","https://openalex.org/W3196313451","https://openalex.org/W4283815760","https://openalex.org/W4285607140","https://openalex.org/W4318823538"],"related_works":["https://openalex.org/W2415164632","https://openalex.org/W2751920613","https://openalex.org/W2238349241","https://openalex.org/W2392697706","https://openalex.org/W366033468","https://openalex.org/W2118640767","https://openalex.org/W2119012848","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"Recently,":[0],"rule-based":[1],"classification":[2,173,185],"on":[3,114,165,176,190],"multivariate":[4],"time":[5,59],"series":[6],"(MTS)":[7],"data":[8,89,118],"has":[9],"gained":[10],"lots":[11],"of":[12,19,49,61,71,87,97,124,161,200],"attention,":[13],"which":[14,41],"could":[15,42,66,79],"improve":[16],"the":[17,46,55,158,184,196],"interpretability":[18],"classification.":[20],"However,":[21],"state-of-the-art":[22],"approaches":[23],"suffer":[24],"from":[25],"three":[26],"major":[27],"issues.":[28],"1)":[29],"few":[30],"existing":[31,75],"studies":[32],"consider":[33],"temporal":[34,84,93,111,127,136,162],"relations":[35],"among":[36,95,138],"features":[37,96,139],"in":[38,140],"a":[39,121,141,149],"rule,":[40],"not":[43,67,80],"adequately":[44],"express":[45],"essential":[47,69],"characteristics":[48,70],"MTS":[50,62,72,88,117,168],"data.":[51,73,169],"2)":[52],"due":[53,90],"to":[54,91,134,156,181,194],"concept":[56],"drift":[57],"and":[58,132,198],"warping":[60],"data,":[63],"traditional":[64],"methods":[65],"mine":[68],"3)":[74],"online":[76,107,145,159],"learning":[77,108,146,160],"algorithms":[78],"effectively":[81],"update":[82],"shapelet-based":[83],"association":[85,112,128,163],"rules":[86,164],"its":[92],"relationships":[94,137],"different":[98],"variables.":[99],"To":[100],"handle":[101],"these":[102],"issues,":[103],"we":[104],"propose":[105],"an":[106,144,171],"method":[109],"for":[110],"rule":[113,125,129],"dynamically":[115,166],"collected":[116,167],"(OTARL).":[119],"First,":[120],"new":[122],"type":[123],"named":[126],"is":[130,154,179],"defined":[131],"mined":[133],"represent":[135],"rule.":[142],"Second,":[143],"mechanism":[147],"with":[148],"probability":[150],"correlation-based":[151],"evaluation":[152],"criterion":[153],"proposed":[155],"realize":[157],"Finally,":[170],"ensemble":[172],"approach":[174],"based":[175],"maximum-likelihood":[177],"estimation":[178],"advanced":[180],"further":[182],"enhance":[183],"performance.":[186],"We":[187],"conduct":[188],"experiments":[189],"ten":[191],"real-world":[192],"datasets":[193],"verify":[195],"effectiveness":[197],"efficiency":[199],"our":[201],"approach.":[202]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}
