{"id":"https://openalex.org/W4390045636","doi":"https://doi.org/10.1109/idaacs58523.2023.10348896","title":"Dynamic Graph Learning with Long and Short-Term for Multivariate Time Series Anomaly Detection","display_name":"Dynamic Graph Learning with Long and Short-Term for Multivariate Time Series Anomaly Detection","publication_year":2023,"publication_date":"2023-09-07","ids":{"openalex":"https://openalex.org/W4390045636","doi":"https://doi.org/10.1109/idaacs58523.2023.10348896"},"language":"en","primary_location":{"id":"doi:10.1109/idaacs58523.2023.10348896","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/idaacs58523.2023.10348896","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 12th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","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/A5064803182","display_name":"Yuyin Tian","orcid":"https://orcid.org/0009-0009-2770-5514"},"institutions":[{"id":"https://openalex.org/I74525822","display_name":"Hubei University of Technology","ror":"https://ror.org/02d3fj342","country_code":"CN","type":"education","lineage":["https://openalex.org/I74525822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuyin Tian","raw_affiliation_strings":["School of Computer Science, Hubei University of Technology,Wuhan,China,430068"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Hubei University of Technology,Wuhan,China,430068","institution_ids":["https://openalex.org/I74525822"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052869008","display_name":"Rong Gao","orcid":"https://orcid.org/0000-0001-7935-7173"},"institutions":[{"id":"https://openalex.org/I74525822","display_name":"Hubei University of Technology","ror":"https://ror.org/02d3fj342","country_code":"CN","type":"education","lineage":["https://openalex.org/I74525822"]},{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rong Gao","raw_affiliation_strings":["School of Computer Science, Hubei University of Technology,Wuhan,China,430068","State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Hubei University of Technology,Wuhan,China,430068","institution_ids":["https://openalex.org/I74525822"]},{"raw_affiliation_string":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037591175","display_name":"Lingyu Yan","orcid":"https://orcid.org/0000-0003-2468-3881"},"institutions":[{"id":"https://openalex.org/I74525822","display_name":"Hubei University of Technology","ror":"https://ror.org/02d3fj342","country_code":"CN","type":"education","lineage":["https://openalex.org/I74525822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingyu Yan","raw_affiliation_strings":["School of Computer Science, Hubei University of Technology,Wuhan,China,430068"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Hubei University of Technology,Wuhan,China,430068","institution_ids":["https://openalex.org/I74525822"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101700523","display_name":"Donghua Liu","orcid":"https://orcid.org/0000-0002-8098-7655"},"institutions":[{"id":"https://openalex.org/I4210100221","display_name":"China Waterborne Transport Research Institute","ror":"https://ror.org/013kb0k13","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210100221"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Donghua Liu","raw_affiliation_strings":["China Waterborne Transport Research Institue,Information Center,Beijing,China,100080"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Waterborne Transport Research Institue,Information Center,Beijing,China,100080","institution_ids":["https://openalex.org/I4210100221"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100670242","display_name":"Zhiwei Ye","orcid":"https://orcid.org/0000-0001-6668-4634"},"institutions":[{"id":"https://openalex.org/I74525822","display_name":"Hubei University of Technology","ror":"https://ror.org/02d3fj342","country_code":"CN","type":"education","lineage":["https://openalex.org/I74525822"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiwei Ye","raw_affiliation_strings":["School of Computer Science, Hubei University of Technology,Wuhan,China,430068"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Hubei University of Technology,Wuhan,China,430068","institution_ids":["https://openalex.org/I74525822"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6534,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.70976952,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1065","last_page":"1070"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9997000098228455,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9997000098228455,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9986000061035156,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7412189245223999},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6100020408630371},{"id":"https://openalex.org/keywords/adjacency-matrix","display_name":"Adjacency matrix","score":0.606324315071106},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.58159339427948},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5760082006454468},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.513515055179596},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4693613648414612},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4509994387626648},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.31702351570129395},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.29940980672836304}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7412189245223999},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6100020408630371},{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.606324315071106},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.58159339427948},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5760082006454468},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.513515055179596},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4693613648414612},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4509994387626648},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31702351570129395},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.29940980672836304}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/idaacs58523.2023.10348896","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/idaacs58523.2023.10348896","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 12th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1087430107","display_name":"\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u975e\u7ed3\u6784\u5316\u5927\u6570\u636e\u5206\u6790\u7b97\u6cd5\u7814\u7a76","funder_award_id":"61772180","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1853998911","display_name":null,"funder_award_id":"KFKT2021B12","funder_id":"https://openalex.org/F4320326895","funder_display_name":"State Key Laboratory of Novel Software Technology"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326895","display_name":"State Key Laboratory of Novel Software Technology","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2604247107","https://openalex.org/W2786827964","https://openalex.org/W2911200746","https://openalex.org/W2950361482","https://openalex.org/W2965341826","https://openalex.org/W3080253043","https://openalex.org/W3081497074","https://openalex.org/W3094643814","https://openalex.org/W3106543020","https://openalex.org/W3128634608","https://openalex.org/W3169450514","https://openalex.org/W3184127157","https://openalex.org/W3190748826","https://openalex.org/W4237491156","https://openalex.org/W4283315029","https://openalex.org/W4283318673"],"related_works":["https://openalex.org/W2406638334","https://openalex.org/W1991765889","https://openalex.org/W1990068454","https://openalex.org/W2472172556","https://openalex.org/W1570805059","https://openalex.org/W2357266745","https://openalex.org/W1578824628","https://openalex.org/W4390961098","https://openalex.org/W2324780611","https://openalex.org/W3122321533"],"abstract_inverted_index":{"Existing":[0],"multivariate":[1,91,122],"time":[2,49,55,87,92,123,141,178,190],"series":[3,93,124,159],"anomaly":[4,94],"detection":[5],"methods":[6,21,202],"utilize":[7],"graph":[8,32,60,101,169],"neural":[9],"networks":[10],"to":[11,67,117,150,180],"model":[12,88],"inter-sensor":[13,40],"dependencies":[14,41,187],"and":[15,50,85,110,112,143,156,184],"achieve":[16],"satisfactory":[17],"results.":[18],"However,":[19],"these":[20,75],"often":[22],"employ":[23],"a":[24,79,99,128,158,176],"predefined":[25],"or":[26],"self-learning":[27],"static":[28],"adjacency":[29,161],"matrix":[30],"for":[31,90,130],"information":[33,116],"aggregation,":[34],"disregarding":[35],"the":[36,43,119,152,165,182,189,194],"dynamic":[37,58,100,132,154,166],"characteristics":[38],"of":[39,121,160,196],"in":[42,107,168],"real":[44],"world,":[45],"which":[46],"change":[47],"over":[48,171,199],"are":[51],"observable":[52],"at":[53,139],"different":[54],"scales":[56],"as":[57],"changing":[59],"structure":[61,102,170],"information.":[62],"Furthermore,":[63],"existing":[64],"techniques":[65],"struggle":[66],"capture":[68,181],"long-term":[69,183],"temporal":[70,114,186],"contextual":[71],"relationships.":[72],"To":[73],"address":[74],"issues,":[76],"we":[77,174],"propose":[78,127],"Dynamic":[80],"Graph":[81],"Learning":[82],"with":[83],"Long":[84],"Short-term":[86],"(DGL-LS)":[89],"detection.":[95],"The":[96],"network":[97],"integrates":[98],"learning":[103,131],"method":[104],"among":[105],"sensors":[106],"multi-time":[108],"mode":[109],"long-":[111],"short-term":[113,185],"context":[115],"enhance":[118],"prediction":[120],"anomalies.":[125],"We":[126,192],"strategy":[129],"graphs":[133],"that":[134,163],"aggregates":[135],"sensor":[136],"node":[137,153],"representations":[138],"various":[140],"intervals,":[142],"then":[144],"uses":[145],"an":[146],"attention-based":[147],"gating":[148],"unit":[149],"evolve":[151],"characterization":[155],"construct":[157],"matrices":[162],"describe":[164],"changes":[167],"time.":[172],"Moreover,":[173],"formulate":[175],"long-short":[177],"convolution":[179],"within":[188],"series.":[191],"demonstrate":[193],"superiority":[195],"our":[197],"approach":[198],"other":[200],"state-of-the-art":[201],"by":[203],"conducting":[204],"extensive":[205],"experiments":[206],"on":[207],"three":[208],"publicly":[209],"available":[210],"datasets.":[211]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
