{"id":"https://openalex.org/W4407601709","doi":"https://doi.org/10.1145/3709026.3709103","title":"KIE-STCformer: Key Information Enhanced Spatio-Temporal Correction Transformer for Time Series Forecasting","display_name":"KIE-STCformer: Key Information Enhanced Spatio-Temporal Correction Transformer for Time Series Forecasting","publication_year":2024,"publication_date":"2024-12-06","ids":{"openalex":"https://openalex.org/W4407601709","doi":"https://doi.org/10.1145/3709026.3709103"},"language":"en","primary_location":{"id":"doi:10.1145/3709026.3709103","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3709026.3709103","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3709026.3709103?download=true","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 8th International Conference on Computer Science and Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3709026.3709103?download=true","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5104441713","display_name":"Shuolin Cui","orcid":null},"institutions":[{"id":"https://openalex.org/I7882870","display_name":"University of Glasgow","ror":"https://ror.org/00vtgdb53","country_code":"GB","type":"education","lineage":["https://openalex.org/I7882870"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Shuolin Cui","raw_affiliation_strings":["School of Computer Science, University of Glasgow, Glasgow, United Kingdom"],"raw_orcid":"https://orcid.org/0009-0000-7573-0268","affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Glasgow, Glasgow, United Kingdom","institution_ids":["https://openalex.org/I7882870"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021432357","display_name":"Penglan Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I12615008","display_name":"Beijing Normal-Hong Kong Baptist University","ror":"https://ror.org/04snvc712","country_code":"CN","type":"education","lineage":["https://openalex.org/I12615008"]},{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Penglan Liu","raw_affiliation_strings":["Hongkong Baptist University United International College, Beijing Normal University, Zhuhai, China"],"raw_orcid":"https://orcid.org/0009-0000-6581-8100","affiliations":[{"raw_affiliation_string":"Hongkong Baptist University United International College, Beijing Normal University, Zhuhai, China","institution_ids":["https://openalex.org/I12615008","https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109736856","display_name":"Haoyuan Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I176808543","display_name":"Liaoning Technical University","ror":"https://ror.org/01n2bd587","country_code":"CN","type":"education","lineage":["https://openalex.org/I176808543"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoyuan Shi","raw_affiliation_strings":["School of Electronic and Information Engineering, Liaoning Techinaical University, HuLudao, LiaoNing, China"],"raw_orcid":"https://orcid.org/0009-0005-7651-0714","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Liaoning Techinaical University, HuLudao, LiaoNing, China","institution_ids":["https://openalex.org/I176808543"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101630444","display_name":"Xiangfu Meng","orcid":"https://orcid.org/0000-0001-7879-2368"},"institutions":[{"id":"https://openalex.org/I176808543","display_name":"Liaoning Technical University","ror":"https://ror.org/01n2bd587","country_code":"CN","type":"education","lineage":["https://openalex.org/I176808543"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangfu Meng","raw_affiliation_strings":["School of Electronic and Information Engineering, Liaoning Techinaical University, HuLudao, LiaoNing, China"],"raw_orcid":"https://orcid.org/0000-0001-7879-2368","affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Liaoning Techinaical University, HuLudao, LiaoNing, China","institution_ids":["https://openalex.org/I176808543"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5104441713"],"corresponding_institution_ids":["https://openalex.org/I7882870"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2922881,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"238","last_page":"244"},"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/T10320","display_name":"Neural Networks and Applications","score":0.9847999811172485,"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/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9832000136375427,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.6502493023872375},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6228539347648621},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5269395112991333},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5058071613311768},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5000452995300293},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.330913245677948},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.18531745672225952},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1250879466533661},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.12403422594070435},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.11260378360748291},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.10460004210472107},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.06526967883110046}],"concepts":[{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6502493023872375},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6228539347648621},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5269395112991333},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5058071613311768},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5000452995300293},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.330913245677948},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.18531745672225952},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1250879466533661},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.12403422594070435},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.11260378360748291},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.10460004210472107},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.06526967883110046},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3709026.3709103","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3709026.3709103","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3709026.3709103?download=true","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 8th International Conference on Computer Science and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3709026.3709103","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3709026.3709103","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3709026.3709103?download=true","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 8th International Conference on Computer Science and Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Climate action","score":0.4699999988079071,"id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4407601709.pdf","grobid_xml":"https://content.openalex.org/works/W4407601709.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W2112796928","https://openalex.org/W2131774270","https://openalex.org/W2607045400","https://openalex.org/W2889928394","https://openalex.org/W2890096158","https://openalex.org/W2954731415","https://openalex.org/W2980994438","https://openalex.org/W3097294131","https://openalex.org/W3111507638","https://openalex.org/W3171884590","https://openalex.org/W3173539742","https://openalex.org/W3212890323","https://openalex.org/W4289236785","https://openalex.org/W4382203079","https://openalex.org/W4385245566","https://openalex.org/W6603143895","https://openalex.org/W6603242443","https://openalex.org/W6604896550","https://openalex.org/W6726027185","https://openalex.org/W6739901393","https://openalex.org/W6757036248"],"related_works":["https://openalex.org/W1919101720","https://openalex.org/W2140798747","https://openalex.org/W2948169060","https://openalex.org/W2730112582","https://openalex.org/W4390822878","https://openalex.org/W2110696645","https://openalex.org/W2119012848","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":{"Many":[0],"existing":[1,27],"time":[2,10,123],"series":[3,11],"forecasting":[4,52,61,139],"models":[5],"primarily":[6],"rely":[7],"on":[8,179],"past":[9],"points":[12,43,124],"to":[13,76,96,132,195],"directly":[14],"forecast":[15],"future":[16],"multi-step":[17,51,85],"sequences.":[18],"However,":[19],"two":[20],"key":[21,109],"problems":[22],"are":[23,177],"confronted":[24],"with":[25,156,168],"the":[26,31,38,49,56,102,128,143,185],"approaches.":[28],"First,":[29,87],"within":[30],"fixed":[32],"input":[33,78,92,103],"space":[34],"of":[35],"size":[36],"N,":[37],"initial":[39],"N":[40],"sequence":[41],"data":[42,93],"may":[44],"include":[45],"redundant":[46,99],"information.":[47],"Second,":[48,112],"direct":[50],"strategy":[53,95],"often":[54],"overlooks":[55],"temporal":[57,164],"dependencies":[58],"between":[59],"consecutive":[60],"steps.":[62],"To":[63,141],"address":[64],"these":[65],"issues,":[66],"we":[67,88],"propose":[68],"an":[69,113,169],"enhanced":[70],"Transformer-based":[71],"model":[72],"named":[73],"KIE-STCformer,":[74],"designed":[75],"tackle":[77],"redundancy":[79],"and":[80,108,162,184],"weak":[81,144],"temporal-spatial":[82],"correlations":[83,120,146],"in":[84,149],"forecasting.":[86],"introduce":[89],"a":[90,152,157,163],"novel":[91],"selection":[94],"filter":[97],"out":[98],"information,":[100],"ensuring":[101],"samples":[104],"contain":[105],"more":[106],"relevant":[107],"predictive":[110],"signals.":[111],"external":[114,134],"attention":[115,171],"mechanism":[116,172],"that":[117,136,189],"captures":[118],"inter-sample":[119],"across":[121],"different":[122],"is":[125,160,173],"integrated":[126],"into":[127],"model,":[129],"enabling":[130],"it":[131],"leverage":[133],"relationships":[135],"significantly":[137],"impact":[138],"outcomes.":[140],"mitigate":[142],"spatial-temporal":[145],"typically":[147],"observed":[148],"forecasted":[150],"sequences,":[151],"spatial":[153],"correction":[154,165],"network":[155,166],"mask":[158],"matrix":[159],"designed,":[161],"embedded":[167],"agent":[170],"constructed.":[174],"Extensive":[175],"experiments":[176],"conducted":[178],"six":[180],"widely-used":[181],"benchmark":[182],"datasets":[183],"experimental":[186],"results":[187],"demonstrate":[188],"KIE-STCformer":[190],"achieves":[191],"superior":[192],"accuracy":[193],"compared":[194],"other":[196],"transformer-based":[197],"models.":[198]},"counts_by_year":[],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}
