{"id":"https://openalex.org/W4415708451","doi":"https://doi.org/10.1109/icme59968.2025.11209971","title":"ForeNet: Unlocking Long-Term Series Forecasting in High-Dimensional Scenario via Forest Structure","display_name":"ForeNet: Unlocking Long-Term Series Forecasting in High-Dimensional Scenario via Forest Structure","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4415708451","doi":"https://doi.org/10.1109/icme59968.2025.11209971"},"language":null,"primary_location":{"id":"doi:10.1109/icme59968.2025.11209971","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209971","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","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/A5100406103","display_name":"Xinyu Li","orcid":"https://orcid.org/0009-0009-1625-3938"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xinyu Li","raw_affiliation_strings":["Fudan University,School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing"],"affiliations":[{"raw_affiliation_string":"Fudan University,School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102748904","display_name":"Hao Xu","orcid":"https://orcid.org/0000-0003-0054-9709"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Xu","raw_affiliation_strings":["Fudan University,School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing"],"affiliations":[{"raw_affiliation_string":"Fudan University,School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101996455","display_name":"Zhiheng Yang","orcid":"https://orcid.org/0009-0005-3721-2650"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiheng Yang","raw_affiliation_strings":["Fudan University,School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing"],"affiliations":[{"raw_affiliation_string":"Fudan University,School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100932591","display_name":"Hongxiang Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongxiang Zhou","raw_affiliation_strings":["Fudan University,School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing"],"affiliations":[{"raw_affiliation_string":"Fudan University,School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111215839","display_name":"Hong Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Lu","raw_affiliation_strings":["Fudan University,School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing"],"affiliations":[{"raw_affiliation_string":"Fudan University,School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086468050","display_name":"Xuejun Wang","orcid":"https://orcid.org/0000-0001-9267-1343"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Wang","raw_affiliation_strings":["Fudan University,School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing"],"affiliations":[{"raw_affiliation_string":"Fudan University,School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003998216","display_name":"Jin Zhao","orcid":"https://orcid.org/0000-0002-9807-2648"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Zhao","raw_affiliation_strings":["Fudan University,School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing"],"affiliations":[{"raw_affiliation_string":"Fudan University,School of Computer Science, Shanghai Key Laboratory of Intelligent Information Processing","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100406103"],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.3613963,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.36489999294281006,"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"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.36489999294281006,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.17489999532699585,"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"}},{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.10920000076293945,"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/construct","display_name":"Construct (python library)","score":0.6430000066757202},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.6317999958992004},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5837000012397766},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5354999899864197},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5289999842643738},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4966999888420105},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.48649999499320984},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.44920000433921814},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.43799999356269836}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6535000205039978},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.6430000066757202},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6317999958992004},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5837000012397766},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5354999899864197},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5289999842643738},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5073999762535095},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4966999888420105},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.48649999499320984},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.44920000433921814},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44429999589920044},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.43799999356269836},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.42179998755455017},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.4196000099182129},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.4065000116825104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3499000072479248},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.3402000069618225},{"id":"https://openalex.org/C163797641","wikidata":"https://www.wikidata.org/wiki/Q2067937","display_name":"Tree structure","level":3,"score":0.3278999924659729},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.32440000772476196},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3125999867916107},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.29660001397132874},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28999999165534973},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.2840000092983246},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.2777000069618225},{"id":"https://openalex.org/C137345334","wikidata":"https://www.wikidata.org/wiki/Q7303350","display_name":"Recursive partitioning","level":2,"score":0.26589998602867126},{"id":"https://openalex.org/C104122410","wikidata":"https://www.wikidata.org/wiki/Q1416406","display_name":"Network model","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C47822265","wikidata":"https://www.wikidata.org/wiki/Q854457","display_name":"Complex system","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C34947359","wikidata":"https://www.wikidata.org/wiki/Q665189","display_name":"Complex network","level":2,"score":0.25870001316070557},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25060001015663147},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.25}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme59968.2025.11209971","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209971","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W2604847698","https://openalex.org/W3177318507","https://openalex.org/W4382203079","https://openalex.org/W4385245566","https://openalex.org/W4393147362"],"related_works":[],"abstract_inverted_index":{"Facing":[0],"the":[1,12,43,48,53,65,97,132,137,146,155,159],"key":[2,133],"challenge":[3,134],"in":[4],"multivariate":[5],"long-term":[6,13,85],"series":[7],"prediction,":[8],"namely":[9],"effectively":[10,130],"modeling":[11],"dependencies":[14,49],"among":[15,50],"high-dimensional":[16,121],"variables,":[17],"we":[18,26,88],"propose":[19],"an":[20,111],"innovative":[21],"forest":[22],"network":[23],"(ForeNet).":[24],"Firstly,":[25],"construct":[27,89],"a":[28,57,107],"polytree,":[29],"which":[30,157],"takes":[31],"variable":[32],"as":[33,37,42,68],"leaf":[34],"node,":[35],"convolution":[36],"edge,":[38],"and":[39,103,125],"progressive":[40,59,124],"fusion":[41],"root":[44],"node.":[45],"Polytree":[46],"models":[47],"variables":[51],"from":[52],"bottom":[54],"up,":[55],"adopting":[56],"local-to-global":[58],"learning":[60,113],"strategy.":[61],"Moreover,":[62],"polytree":[63,82],"embeds":[64],"entire":[66],"sequence":[67],"input":[69],"channels":[70],"for":[71],"convolution,":[72],"allowing":[73],"interactions":[74],"across":[75],"arbitrary":[76],"time":[77],"steps":[78],"between":[79],"variables.":[80,122],"Thereby,":[81],"could":[83,129,144],"model":[84],"dependencies.":[86],"Then,":[87],"multiple":[90],"polytrees":[91,105],"with":[92],"varying":[93],"branching":[94],"factors,":[95],"utilizing":[96],"self-attention":[98],"mechanism":[99],"to":[100,115,151,154],"assign":[101],"weights":[102],"combine":[104],"into":[106],"forest.":[108],"Forest":[109],"adopts":[110],"ensemble":[112,126],"strategy":[114],"capture":[116],"complex":[117],"patterns":[118],"hidden":[119],"under":[120],"Combining":[123],"strategies,":[127],"ForeNet":[128,143],"address":[131],"mentioned":[135],"at":[136],"beginning.":[138],"Extensive":[139],"experiments":[140],"show":[141],"that":[142],"reduce":[145],"average":[147],"MSE":[148],"by":[149],"up":[150],"11.53%":[152],"compared":[153],"baseline,":[156],"verifies":[158],"effectiveness":[160],"of":[161],"ForeNet.":[162],"Source":[163],"code":[164],"is":[165],"available":[166],"at:":[167],"https://github.com/lxy-PhD2022/ForeNet":[168]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-30T00:00:00"}