{"id":"https://openalex.org/W4306317670","doi":"https://doi.org/10.1145/3511808.3557386","title":"MARINA","display_name":"MARINA","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4306317670","doi":"https://doi.org/10.1145/3511808.3557386"},"language":"en","primary_location":{"id":"doi:10.1145/3511808.3557386","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557386","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-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/A5016327059","display_name":"Jiandong Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiandong Xie","raw_affiliation_strings":["Huawei Cloud Database Innovation Lab, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Cloud Database Innovation Lab, Chengdu, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055065511","display_name":"Yue Cui","orcid":"https://orcid.org/0000-0002-1656-5407"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yue Cui","raw_affiliation_strings":["The Hong Kong University of Science and Technology, Hong Kong, Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Hong Kong University of Science and Technology, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045107485","display_name":"Feiteng Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feiteng Huang","raw_affiliation_strings":["Huawei Cloud Database Innovation Lab, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Cloud Database Innovation Lab, Chengdu, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100362891","display_name":"Chao Liu","orcid":"https://orcid.org/0000-0001-7363-1987"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Liu","raw_affiliation_strings":["Huawei Cloud Database Innovation Lab, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huawei Cloud Database Innovation Lab, Chengdu, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101619839","display_name":"Kai Zheng","orcid":"https://orcid.org/0000-0003-1996-1699"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Zheng","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.21,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.81680831,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2230","last_page":"2239"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9993000030517578,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9921000003814697,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7593123912811279},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.7040208578109741},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6795669794082642},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6503521203994751},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6302624940872192},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5954557657241821},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5483359694480896},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5254499316215515},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4492741823196411},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35717087984085083},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.23637762665748596}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7593123912811279},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.7040208578109741},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6795669794082642},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6503521203994751},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6302624940872192},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5954557657241821},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5483359694480896},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5254499316215515},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4492741823196411},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35717087984085083},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.23637762665748596},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3511808.3557386","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3511808.3557386","pdf_url":null,"source":{"id":"https://openalex.org/S4363608762","display_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-123749","is_oa":false,"landing_page_url":"http://www.scopus.com/record/display.url?eid=2-s2.0-85140834815&origin=inward","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G964926443","display_name":"\u7a7a\u95f4\u4f17\u5305\u4e2d\u7684\u4efb\u52a1\u9884\u6d4b\u4e0e\u5206\u914d\u6280\u672f\u7814\u7a76","funder_award_id":"61972069","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":18,"referenced_works":["https://openalex.org/W197787652","https://openalex.org/W2026453187","https://openalex.org/W2093606067","https://openalex.org/W2116341502","https://openalex.org/W2132782512","https://openalex.org/W2747599906","https://openalex.org/W2765308781","https://openalex.org/W2785362611","https://openalex.org/W2786827964","https://openalex.org/W2903871660","https://openalex.org/W2963166639","https://openalex.org/W2963507686","https://openalex.org/W2965433388","https://openalex.org/W2996847713","https://openalex.org/W3098957257","https://openalex.org/W3106543020","https://openalex.org/W4300874750","https://openalex.org/W6608049307"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W3210364259","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W2912112202","https://openalex.org/W2667207928","https://openalex.org/W4300558037","https://openalex.org/W4377864969","https://openalex.org/W3030345572"],"abstract_inverted_index":{"The":[0],"proliferation":[1],"of":[2,17,25,29,37,50],"real-time":[3],"monitoring":[4],"applications":[5],"such":[6,105],"as":[7,106],"Artificial":[8],"Intelligence":[9],"for":[10,55,100],"IT":[11],"Operations":[12],"(AIOps)":[13],"and":[14,43,52,84,108,120,135],"the":[15,23,34,38,41,44,82,91,115],"Internet":[16],"Things":[18],"(IoT)":[19],"has":[20],"led":[21],"to":[22,79,127],"generation":[24],"a":[26,66],"vast":[27],"amount":[28],"time-series":[30,56,102,118],"data.":[31],"To":[32,58],"extract":[33],"underlying":[35],"value":[36],"data,":[39],"both":[40,133],"industry":[42],"academia":[45],"are":[46],"in":[47,61,95,132],"dire":[48],"need":[49],"efficient":[51],"effective":[53],"methods":[54],"analysis.":[57],"this":[59,62],"end,":[60],"paper,":[63],"we":[64],"propose":[65],"Multi-layer":[67],"perceptron":[68],"(<u>M</u>LP)-<u>a</u>ttention":[69],"based":[70],"multivariate":[71,88,117],"time-se<u>ri</u>es":[72],"a<u>na</u>lysis":[73],"model":[74,92],"MARINA.":[75],"MARINA":[76,124],"is":[77,93,98,125],"designed":[78],"simultaneously":[80],"learn":[81],"temporal":[83],"spatial":[85],"correlations":[86],"among":[87],"time-series.":[89],"Also,":[90],"versatile":[94],"that":[96],"it":[97],"suitable":[99],"major":[101],"analysis":[103],"tasks":[104],"forecasting":[107,119,134],"anomaly":[109,121,136],"detection.":[110],"Through":[111],"extensive":[112],"comparisons":[113],"with":[114],"representative":[116],"detection":[122,137],"algorithms,":[123],"shown":[126],"achieve":[128],"state-of-the-art":[129],"(SOTA)":[130],"performance":[131],"tasks.":[138]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2022-10-16T00:00:00"}
