{"id":"https://openalex.org/W4414931908","doi":"https://doi.org/10.1145/3757110.3757196","title":"Efficient Time Series Forecasting with MSPA for Smart Government Big Data Platforms","display_name":"Efficient Time Series Forecasting with MSPA for Smart Government Big Data Platforms","publication_year":2025,"publication_date":"2025-05-16","ids":{"openalex":"https://openalex.org/W4414931908","doi":"https://doi.org/10.1145/3757110.3757196"},"language":"en","primary_location":{"id":"doi:10.1145/3757110.3757196","doi":"https://doi.org/10.1145/3757110.3757196","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3757110.3757196","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3757110.3757196","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 2025 2nd International Conference on Modeling, Natural Language Processing and Machine Learning","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3757110.3757196","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Wenhan Song","orcid":"https://orcid.org/0009-0003-7340-8461","observed_orcids":["https://orcid.org/0009-0003-7340-8461"]},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenhan Song","raw_affiliation_strings":["School of Computer Science and Technology, Xinjiang University, Urumqi, Xinjiang, China"],"raw_orcid":"https://orcid.org/0009-0003-7340-8461","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xinjiang University, Urumqi, Xinjiang, China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047166646","display_name":"Enguang Zuo","orcid":"https://orcid.org/0000-0003-0029-2018","observed_orcids":["https://orcid.org/0000-0003-0029-2018"]},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Enguang Zuo","raw_affiliation_strings":["Department of Electronic Information, Tsinghua University, Beijing, China","School of Intelligence Science and Technology, Xinjiang University, Urumqi, Xinjiang, China"],"raw_orcid":"https://orcid.org/0000-0003-0029-2018","affiliations":[{"raw_affiliation_string":"Department of Electronic Information, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"School of Intelligence Science and Technology, Xinjiang University, Urumqi, Xinjiang, China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034613932","display_name":"Ziwei Yan","orcid":"https://orcid.org/0000-0003-2943-2707","observed_orcids":["https://orcid.org/0000-0003-2943-2707","https://orcid.org/0000-0002-6435-7274"]},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziwei Yan","raw_affiliation_strings":["College of Software, Xinjiang University, Urumqi, Xinjiang, China"],"raw_orcid":"https://orcid.org/0000-0003-2943-2707","affiliations":[{"raw_affiliation_string":"College of Software, Xinjiang University, Urumqi, Xinjiang, China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101077674","display_name":"Junyu Zhu","orcid":"https://orcid.org/0009-0006-2865-4200","observed_orcids":["https://orcid.org/0009-0006-2865-4200"]},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junyu Zhu","raw_affiliation_strings":["School of Computer Science and Technology, Xinjiang University, Urumqi, Xinjiang, China"],"raw_orcid":"https://orcid.org/0009-0006-2865-4200","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xinjiang University, Urumqi, Xinjiang, China","institution_ids":["https://openalex.org/I96908189"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23798807,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"516","last_page":"520"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9413999915122986,"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":0.9413999915122986,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.048700001090765,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.003599999938160181,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/time-series-forecasting","display_name":"time series forecasting","score":0.9900000095367432},{"id":"https://openalex.org/keywords/mspa","display_name":"MspA","score":0.6470000147819519},{"id":"https://openalex.org/keywords/multi-scale-pooling","display_name":"multi-scale pooling","score":0.9670000076293945},{"id":"https://openalex.org/keywords/attention-mechanism","display_name":"attention mechanism","score":0.8119999766349792},{"id":"https://openalex.org/keywords/knowledge-graphs","display_name":"knowledge graphs","score":0.621999979019165},{"id":"https://openalex.org/keywords/missing-data-prediction","display_name":"missing data prediction","score":0.9620000123977661},{"id":"https://openalex.org/keywords/smart-government","display_name":"smart government","score":0.753000020980835},{"id":"https://openalex.org/keywords/big-data-platform","display_name":"big data platform","score":0.9169999957084656},{"id":"https://openalex.org/keywords/computational-cost-reduction","display_name":"computational complexity reduction","score":0.6980000138282776},{"id":"https://openalex.org/keywords/urban-governance","display_name":"urban governance","score":0.6439999938011169},{"id":"https://openalex.org/keywords/government-decision-making","display_name":"government decision-making","score":0.7570000290870667}],"concepts":[{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.8384000062942505},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7342000007629395},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.7050999999046326},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6279000043869019},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5353000164031982},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.5299000144004822},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.4415999948978424},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43650001287460327},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4325000047683716},{"id":"https://openalex.org/C2778137410","wikidata":"https://www.wikidata.org/wiki/Q2732820","display_name":"Government (linguistics)","level":2,"score":0.41519999504089355},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4049000144004822},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.397599995136261},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3824000060558319},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35749998688697815},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.3222000002861023},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.29580000042915344},{"id":"https://openalex.org/C2777103469","wikidata":"https://www.wikidata.org/wiki/Q1231558","display_name":"Smart city","level":3,"score":0.27570000290870667},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.272599995136261},{"id":"https://openalex.org/C56397880","wikidata":"https://www.wikidata.org/wiki/Q6044094","display_name":"Intelligent decision support system","level":2,"score":0.266400009393692},{"id":"https://openalex.org/C82578977","wikidata":"https://www.wikidata.org/wiki/Q16773055","display_name":"Data aggregator","level":3,"score":0.2637999951839447},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2615000009536743}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3757110.3757196","doi":"https://doi.org/10.1145/3757110.3757196","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3757110.3757196","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3757110.3757196","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 2025 2nd International Conference on Modeling, Natural Language Processing and Machine Learning","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3757110.3757196","doi":"https://doi.org/10.1145/3757110.3757196","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3757110.3757196","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3757110.3757196","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 2025 2nd International Conference on Modeling, Natural Language Processing and Machine Learning","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.5142999887466431,"id":"https://metadata.un.org/sdg/11"},{"display_name":"Industry, innovation and infrastructure","score":0.4943999946117401,"id":"https://metadata.un.org/sdg/9"}],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4414931908.pdf","grobid_xml":"https://content.openalex.org/works/W4414931908.grobid-xml"},"referenced_works_count":8,"referenced_works":["https://openalex.org/W2225156818","https://openalex.org/W2250539671","https://openalex.org/W3177318507","https://openalex.org/W3204801262","https://openalex.org/W4236965008","https://openalex.org/W4285260111","https://openalex.org/W4387826250","https://openalex.org/W4402956043"],"related_works":[],"abstract_inverted_index":{"Smart":[0],"government":[1,95],"platforms":[2],"face":[3],"challenges":[4],"in":[5,12],"handling":[6],"heterogeneous":[7],"data":[8,70],"and":[9,28,50,82,97],"missing":[10,69],"information":[11],"knowledge":[13,74],"graphs.":[14],"This":[15],"paper":[16],"presents":[17],"MSPA,":[18],"an":[19],"efficient":[20],"time":[21,35],"series":[22,36],"prediction":[23,80],"model":[24,32],"combining":[25],"multi-scale":[26,41],"pooling":[27,42],"attention":[29,53],"mechanisms.":[30],"The":[31],"converts":[33],"1D":[34],"to":[37,54,64,72],"2D":[38],"format,":[39],"applies":[40],"(2\u00d72,":[43],"3\u00d73,":[44],"4\u00d74":[45],"kernels)":[46],"for":[47,93],"feature":[48],"compression,":[49],"uses":[51],"single-head":[52],"capture":[55],"global":[56],"dependencies":[57],"while":[58],"reducing":[59],"computational":[60],"complexity":[61],"from":[62],"O(H\u00d7L\u00b2)":[63],"O(0.42L\u00b2).":[65],"MSPA":[66],"effectively":[67],"predicts":[68],"dynamics":[71],"improve":[73],"graph":[75],"integrity.":[76],"Experiments":[77],"demonstrate":[78],"superior":[79],"accuracy":[81],"sixfold":[83],"efficiency":[84],"improvement":[85],"over":[86],"existing":[87],"methods,":[88],"providing":[89],"a":[90],"novel":[91],"solution":[92],"intelligent":[94],"decision-making":[96],"urban":[98],"governance.":[99]},"counts_by_year":[],"updated_date":"2026-09-24T07:57:37.273135","created_date":"2025-10-10T00:00:00"}