{"id":"https://openalex.org/W4372262423","doi":"https://doi.org/10.1109/icassp49357.2023.10095241","title":"Robust Dominant Periodicity Detection for Time Series with Missing Data","display_name":"Robust Dominant Periodicity Detection for Time Series with Missing Data","publication_year":2023,"publication_date":"2023-05-05","ids":{"openalex":"https://openalex.org/W4372262423","doi":"https://doi.org/10.1109/icassp49357.2023.10095241"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49357.2023.10095241","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10095241","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5048346353","display_name":"Qingsong Wen","orcid":"https://orcid.org/0000-0003-4516-2524"},"institutions":[{"id":"https://openalex.org/I4210095624","display_name":"Alibaba Group (United States)","ror":"https://ror.org/00rn0m335","country_code":"US","type":"company","lineage":["https://openalex.org/I4210095624","https://openalex.org/I45928872"]},{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Qingsong Wen","raw_affiliation_strings":["DAMO Academy,Alibaba Group,Bellevue,USA","Alibaba Group, DAMO Academy, Bellevue, USA"],"affiliations":[{"raw_affiliation_string":"DAMO Academy,Alibaba Group,Bellevue,USA","institution_ids":["https://openalex.org/I4210095624","https://openalex.org/I4210108985"]},{"raw_affiliation_string":"Alibaba Group, DAMO Academy, Bellevue, USA","institution_ids":["https://openalex.org/I4210095624","https://openalex.org/I4210108985"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072947305","display_name":"Linxiao Yang","orcid":"https://orcid.org/0000-0001-9558-7163"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linxiao Yang","raw_affiliation_strings":["DAMO Academy,Alibaba Group,Hangzhou,China","Alibaba Group, DAMO Academy, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"DAMO Academy,Alibaba Group,Hangzhou,China","institution_ids":["https://openalex.org/I45928872"]},{"raw_affiliation_string":"Alibaba Group, DAMO Academy, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054846625","display_name":"Liang Sun","orcid":"https://orcid.org/0009-0002-5835-7259"},"institutions":[{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]},{"id":"https://openalex.org/I4210095624","display_name":"Alibaba Group (United States)","ror":"https://ror.org/00rn0m335","country_code":"US","type":"company","lineage":["https://openalex.org/I4210095624","https://openalex.org/I45928872"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liang Sun","raw_affiliation_strings":["DAMO Academy,Alibaba Group,Bellevue,USA","Alibaba Group, DAMO Academy, Bellevue, USA"],"affiliations":[{"raw_affiliation_string":"DAMO Academy,Alibaba Group,Bellevue,USA","institution_ids":["https://openalex.org/I4210095624","https://openalex.org/I4210108985"]},{"raw_affiliation_string":"Alibaba Group, DAMO Academy, Bellevue, USA","institution_ids":["https://openalex.org/I4210095624","https://openalex.org/I4210108985"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5048346353"],"corresponding_institution_ids":["https://openalex.org/I4210095624","https://openalex.org/I4210108985"],"apc_list":null,"apc_paid":null,"fwci":1.6266,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.84014521,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9993000030517578,"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":0.9993000030517578,"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/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10282","display_name":"Financial Risk and Volatility Modeling","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/2003","display_name":"Finance"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.8527963161468506},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.7898712158203125},{"id":"https://openalex.org/keywords/autocorrelation","display_name":"Autocorrelation","score":0.7527820467948914},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6802275776863098},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6439393758773804},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6012958884239197},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5970569252967834},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5806609392166138},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.537310004234314},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4560747742652893},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4514743387699127},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4319826662540436},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3731483221054077},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2803219258785248},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22089970111846924},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1725243330001831},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.14054012298583984},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07754918932914734}],"concepts":[{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.8527963161468506},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7898712158203125},{"id":"https://openalex.org/C5297727","wikidata":"https://www.wikidata.org/wiki/Q786970","display_name":"Autocorrelation","level":2,"score":0.7527820467948914},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6802275776863098},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6439393758773804},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6012958884239197},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5970569252967834},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5806609392166138},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.537310004234314},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4560747742652893},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4514743387699127},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4319826662540436},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3731483221054077},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2803219258785248},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22089970111846924},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1725243330001831},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.14054012298583984},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07754918932914734},{"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/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49357.2023.10095241","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49357.2023.10095241","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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":35,"referenced_works":["https://openalex.org/W27994497","https://openalex.org/W1536447791","https://openalex.org/W1974618482","https://openalex.org/W1989280111","https://openalex.org/W2032929521","https://openalex.org/W2041442343","https://openalex.org/W2044722977","https://openalex.org/W2057714964","https://openalex.org/W2075715210","https://openalex.org/W2088563154","https://openalex.org/W2135657996","https://openalex.org/W2137810258","https://openalex.org/W2154136024","https://openalex.org/W2157173448","https://openalex.org/W2469618837","https://openalex.org/W2964758013","https://openalex.org/W2964938828","https://openalex.org/W2965206958","https://openalex.org/W2997000181","https://openalex.org/W3007098654","https://openalex.org/W3007103823","https://openalex.org/W3097515580","https://openalex.org/W3131918926","https://openalex.org/W3134859316","https://openalex.org/W3163701409","https://openalex.org/W3198720945","https://openalex.org/W4225494949","https://openalex.org/W4290876049","https://openalex.org/W4292363360","https://openalex.org/W4306317275","https://openalex.org/W6632102171","https://openalex.org/W6680046297","https://openalex.org/W6720065314","https://openalex.org/W6773950905","https://openalex.org/W6810637551"],"related_works":["https://openalex.org/W3024870410","https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W3107369729","https://openalex.org/W2998615029","https://openalex.org/W2937099569","https://openalex.org/W3005992387","https://openalex.org/W4387250752"],"abstract_inverted_index":{"Periodicity":[0],"detection":[1,45,139],"is":[2,107],"an":[3],"important":[4],"task":[5],"in":[6],"time":[7,21,48,143],"series":[8,22,49,144],"analysis,":[9],"but":[10],"still":[11,97],"a":[12,40,57,75],"challenging":[13],"problem":[14],"due":[15],"to":[16,61],"the":[17,63,92,101,104,112,118,125],"diverse":[18],"characteristics":[19],"of":[20,65,103,111],"data":[23],"like":[24],"abrupt":[25],"trend":[26,59,67],"change,":[27],"outlier,":[28],"noise,":[29],"and":[30,42,85],"especially":[31],"block":[32,51,106],"missing":[33,52,70,83,105],"data.":[34,53,71],"In":[35],"this":[36],"paper,":[37],"we":[38,73],"propose":[39,74],"robust":[41,58,76,94],"effective":[43],"periodicity":[44,138],"algorithm":[46,122,135],"for":[47],"with":[50],"We":[54,88],"first":[55],"design":[56],"filter":[60],"remove":[62],"interference":[64],"complicated":[66],"patterns":[68],"under":[69],"Then,":[72],"autocorrelation":[77],"function":[78],"(ACF)":[79],"that":[80,91,133],"can":[81,96,123],"handle":[82],"values":[84],"outliers":[86],"effectively.":[87],"rigorously":[89],"prove":[90],"proposed":[93],"ACF":[95],"work":[98],"well":[99],"when":[100],"length":[102,127],"less":[108],"than":[109],"1/3":[110],"period":[113,126],"length.":[114],"Last,":[115],"by":[116],"combining":[117],"time-frequency":[119],"information,":[120],"our":[121,134],"generate":[124],"accurately.":[128],"The":[129],"experimental":[130],"results":[131],"demonstrate":[132],"outperforms":[136],"existing":[137],"algorithms":[140],"on":[141],"real-world":[142],"datasets.":[145]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
