{"id":"https://openalex.org/W3104959188","doi":"https://doi.org/10.1109/tsipn.2020.3038475","title":"Graph Learning for Spatiotemporal Signals With Long- and Short-Term Characterization","display_name":"Graph Learning for Spatiotemporal Signals With Long- and Short-Term Characterization","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3104959188","doi":"https://doi.org/10.1109/tsipn.2020.3038475","mag":"3104959188"},"language":"en","primary_location":{"id":"doi:10.1109/tsipn.2020.3038475","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsipn.2020.3038475","pdf_url":null,"source":{"id":"https://openalex.org/S4306422866","display_name":"IEEE Transactions on Signal and Information Processing over Networks","issn_l":"2373-776X","issn":["2373-776X","2373-7778"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Signal and Information Processing over Networks","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1911.08018","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Yueliang Liu","orcid":"https://orcid.org/0000-0002-8997-7023"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]},{"id":"https://openalex.org/I4210164386","display_name":"Hebei Science and Technology Department","ror":"https://ror.org/05k812a28","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210164386"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yueliang Liu","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","Science and Technology on Information Transmission and Dissemination in Communication Networks Laboratory, Shijiazhuang, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Science and Technology on Information Transmission and Dissemination in Communication Networks Laboratory, Shijiazhuang, China","institution_ids":["https://openalex.org/I4210164386"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wenbin Guo","orcid":"https://orcid.org/0000-0002-0706-4192"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]},{"id":"https://openalex.org/I4210164386","display_name":"Hebei Science and Technology Department","ror":"https://ror.org/05k812a28","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210164386"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenbin Guo","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","Science and Technology on Information Transmission and Dissemination in Communication Networks Laboratory, Shijiazhuang, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Science and Technology on Information Transmission and Dissemination in Communication Networks Laboratory, Shijiazhuang, China","institution_ids":["https://openalex.org/I4210164386"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Kangyong You","orcid":"https://orcid.org/0000-0003-0314-2533"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kangyong You","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lei Zhao","orcid":"https://orcid.org/0000-0002-3470-7544"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Zhao","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Tao Peng","orcid":"https://orcid.org/0000-0003-1701-6255"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Peng","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":null,"display_name":"Wenbo Wang","orcid":"https://orcid.org/0000-0002-0911-3189"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenbo Wang","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139759216","https://openalex.org/I4210164386"],"apc_list":null,"apc_paid":null,"fwci":0.6797,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.77509944,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"6","issue":null,"first_page":"699","last_page":"713"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.22869999706745148,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.22869999706745148,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.2053000032901764,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.06019999831914902,"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/graph","display_name":"Graph","score":0.6128000020980835},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4851999878883362},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.45249998569488525},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4429999887943268},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4228000044822693},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.38830000162124634},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.37599998712539673},{"id":"https://openalex.org/keywords/laplacian-matrix","display_name":"Laplacian matrix","score":0.3732999861240387},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.36649999022483826}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6800000071525574},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6128000020980835},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5716999769210815},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4851999878883362},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.45249998569488525},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4429999887943268},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4228000044822693},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4205000102519989},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.38830000162124634},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.37599998712539673},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.3732999861240387},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.36649999022483826},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.35690000653266907},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.3521000146865845},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.33570000529289246},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.335099995136261},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.3172000050544739},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3172000050544739},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.31349998712539673},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.3100999891757965},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.30889999866485596},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29429998993873596},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.2863999903202057},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28189998865127563},{"id":"https://openalex.org/C51432778","wikidata":"https://www.wikidata.org/wiki/Q1259145","display_name":"Independent component analysis","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.2603999972343445},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.25130000710487366}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tsipn.2020.3038475","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsipn.2020.3038475","pdf_url":null,"source":{"id":"https://openalex.org/S4306422866","display_name":"IEEE Transactions on Signal and Information Processing over Networks","issn_l":"2373-776X","issn":["2373-776X","2373-7778"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Signal and Information Processing over Networks","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1911.08018","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1911.08018","pdf_url":"https://arxiv.org/pdf/1911.08018","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1911.08018","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1911.08018","pdf_url":"https://arxiv.org/pdf/1911.08018","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4248265164","display_name":null,"funder_award_id":"61571054","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4536483767","display_name":null,"funder_award_id":"62071063","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5037589777","display_name":null,"funder_award_id":"61271181","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1643717297","https://openalex.org/W1890623278","https://openalex.org/W1990488619","https://openalex.org/W1999870684","https://openalex.org/W2010408890","https://openalex.org/W2013315566","https://openalex.org/W2038366894","https://openalex.org/W2053014853","https://openalex.org/W2068000292","https://openalex.org/W2077318038","https://openalex.org/W2101491865","https://openalex.org/W2103351706","https://openalex.org/W2103972604","https://openalex.org/W2106210113","https://openalex.org/W2132555912","https://openalex.org/W2132914434","https://openalex.org/W2145962650","https://openalex.org/W2147392828","https://openalex.org/W2149532724","https://openalex.org/W2161041254","https://openalex.org/W2404087539","https://openalex.org/W2463327569","https://openalex.org/W2520179645","https://openalex.org/W2585019672","https://openalex.org/W2615556757","https://openalex.org/W2627924202","https://openalex.org/W2631776726","https://openalex.org/W2781888589","https://openalex.org/W2897453016","https://openalex.org/W2936036845","https://openalex.org/W2946123091","https://openalex.org/W2962759781","https://openalex.org/W2962886701","https://openalex.org/W2963384510","https://openalex.org/W2963545270","https://openalex.org/W2963702033","https://openalex.org/W2964012239","https://openalex.org/W2964171990","https://openalex.org/W2994097903","https://openalex.org/W4213009331","https://openalex.org/W4244030505","https://openalex.org/W4250589301","https://openalex.org/W4292363360","https://openalex.org/W6674632333","https://openalex.org/W6676051941","https://openalex.org/W6679272984","https://openalex.org/W6689213722"],"related_works":[],"abstract_inverted_index":{"Mining":[0],"natural":[1],"associations":[2],"from":[3],"high-dimensional":[4],"spatiotemporal":[5,34,61,65,118,127],"signals":[6,28,35],"plays":[7],"an":[8],"important":[9],"role":[10],"in":[11,167],"various":[12],"fields":[13],"including":[14],"biology,":[15],"climatology,":[16],"and":[17,57,74,84,107,117,143,161,181],"financial":[18],"analysis.":[19,133],"However,":[20],"most":[21],"existing":[22],"works":[23],"have":[24],"mainly":[25],"studied":[26],"time-independent":[27],"without":[29],"considering":[30],"the":[31,55,91,95,137,144,149,168,172,176],"correlations":[32],"of":[33,60,140,146,171],"that":[36,47,70],"achieve":[37],"high":[38],"learning":[39,97,121,151,169,183],"accuracy.":[40],"This":[41],"paper":[42],"aims":[43],"to":[44,89],"learn":[45],"graphs":[46],"better":[48],"reflect":[49],"underlying":[50],"data":[51],"relations":[52],"by":[53],"leveraging":[54],"long-":[56],"short-term":[58],"characteristics":[59],"signals.":[62],"First,":[63],"a":[64,81,85,102,114,126],"signal":[66,132],"model":[67],"is":[68,99],"presented":[69],"considers":[71],"both":[72,159],"spatial":[73],"temporal":[75,92],"relations.":[76],"In":[77],"particular,":[78],"we":[79,112],"integrate":[80],"low-rank":[82,104,178],"representation":[83],"Gaussian":[86],"Markov":[87],"process":[88],"describe":[90],"correlations.":[93],"Then,":[94],"graph":[96,108,120,182],"problem":[98],"formulated":[100],"as":[101],"joint":[103],"component":[105,179],"estimation":[106,180],"Laplacian":[109],"inference.":[110],"Accordingly,":[111],"propose":[113],"low":[115,138],"rank":[116,139],"smoothness-based":[119],"method":[122,174],"(GL-LRSS),":[123],"which":[124],"introduces":[125],"smoothness":[128,145],"prior":[129],"into":[130],"time-vertex":[131],"By":[134],"jointly":[135],"exploiting":[136],"long-time":[141],"observations":[142],"short-time":[147],"observations,":[148],"overall":[150],"performance":[152],"can":[153],"be":[154],"effectively":[155],"improved.":[156],"Experiments":[157],"on":[158],"synthetic":[160],"real-world":[162],"datasets":[163],"demonstrate":[164],"substantial":[165],"improvements":[166],"accuracy":[170],"proposed":[173],"over":[175],"state-of-the-art":[177],"methods.":[184]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2020-11-23T00:00:00"}