{"id":"https://openalex.org/W4416017166","doi":"https://doi.org/10.1145/3746252.3761403","title":"Spatio-Temporal Forecasting under Open-World Missingness with Adaptive Mixture-of-Experts","display_name":"Spatio-Temporal Forecasting under Open-World Missingness with Adaptive Mixture-of-Experts","publication_year":2025,"publication_date":"2025-11-08","ids":{"openalex":"https://openalex.org/W4416017166","doi":"https://doi.org/10.1145/3746252.3761403"},"language":null,"primary_location":{"id":"doi:10.1145/3746252.3761403","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746252.3761403","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Information and Knowledge Management","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/A5111322869","display_name":"Chenyu Wu","orcid":"https://orcid.org/0009-0008-3747-8960"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chenyu Wu","raw_affiliation_strings":["College of Information Science and Technology, Southwest Jiaotong University, Chengdu, Sichuan, China"],"raw_orcid":"https://orcid.org/0009-0008-3747-8960","affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Southwest Jiaotong University, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071182342","display_name":"Zhipeng Ma","orcid":"https://orcid.org/0009-0008-1485-0766"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhipeng Ma","raw_affiliation_strings":["Southwest Jiaotong University, Chengdu, Sichuan, China"],"raw_orcid":"https://orcid.org/0009-0008-1485-0766","affiliations":[{"raw_affiliation_string":"Southwest Jiaotong University, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100778479","display_name":"Junbo Zhang","orcid":"https://orcid.org/0000-0001-5947-1374"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junbo Zhang","raw_affiliation_strings":["JD iCity, JD Technology, Beijing, China and JD Intelligent Cities Research, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5947-1374","affiliations":[{"raw_affiliation_string":"JD iCity, JD Technology, Beijing, China and JD Intelligent Cities Research, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026716125","display_name":"Songyu Ke","orcid":"https://orcid.org/0000-0001-7184-8074"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Songyu Ke","raw_affiliation_strings":["College of Computer and Data Science, Fuzhou University, Fuzhou, Fujian, China"],"raw_orcid":"https://orcid.org/0000-0001-7184-8074","affiliations":[{"raw_affiliation_string":"College of Computer and Data Science, Fuzhou University, Fuzhou, Fujian, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100681023","display_name":"Yu Zheng","orcid":"https://orcid.org/0000-0002-5224-4344"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Zheng","raw_affiliation_strings":["JD iCity, JD Technology, Beijing, China and JD Intelligent Cities Research, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5224-4344","affiliations":[{"raw_affiliation_string":"JD iCity, JD Technology, Beijing, China and JD Intelligent Cities Research, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5111322869"],"corresponding_institution_ids":["https://openalex.org/I4800084"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.34056496,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3366","last_page":"3375"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.8831999897956848,"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":0.8831999897956848,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.02850000001490116,"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/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.019300000742077827,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.7838000059127808},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4187000095844269},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.374099999666214},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.3188000023365021},{"id":"https://openalex.org/keywords/expert-system","display_name":"Expert system","score":0.25290000438690186}],"concepts":[{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.7838000059127808},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7091000080108643},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5504999756813049},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5350000262260437},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4691999852657318},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4187000095844269},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.374099999666214},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.3188000023365021},{"id":"https://openalex.org/C58328972","wikidata":"https://www.wikidata.org/wiki/Q184609","display_name":"Expert system","level":2,"score":0.25290000438690186},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.24459999799728394}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746252.3761403","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746252.3761403","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1543664493","display_name":null,"funder_award_id":"62172034","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":17,"referenced_works":["https://openalex.org/W1975372198","https://openalex.org/W2112738128","https://openalex.org/W2528639018","https://openalex.org/W2907492528","https://openalex.org/W2980994438","https://openalex.org/W2997848713","https://openalex.org/W3081790702","https://openalex.org/W4306317966","https://openalex.org/W4381463107","https://openalex.org/W4382318973","https://openalex.org/W4385270120","https://openalex.org/W4385288150","https://openalex.org/W4387846717","https://openalex.org/W4388936714","https://openalex.org/W4401857089","https://openalex.org/W4401863578","https://openalex.org/W4402352265"],"related_works":[],"abstract_inverted_index":{"Spatio-temporal":[0],"forecasting":[1,91],"is":[2],"crucial":[3],"for":[4],"sustainable":[5],"urban":[6],"development":[7],"and":[8,21,27,32,99],"societal":[9],"decision-making.":[10],"However,":[11],"real-world":[12,106],"spatio-temporal":[13],"data":[14],"often":[15],"exhibit":[16],"open-world":[17],"missingness:":[18],"missing":[19,74,100],"rates":[20,75],"patterns":[22],"evolve":[23],"dynamically":[24,70],"across":[25],"time":[26],"space,":[28],"severely":[29],"disrupting":[30],"dependencies":[31],"challenging":[33],"accurate":[34],"forecasting.":[35],"Traditional":[36],"methods":[37],"universally":[38],"overlook":[39],"the":[40,95],"dynamic":[41],"nature":[42],"of":[43,97],"missingness,":[44],"resulting":[45],"in":[46],"degraded":[47],"predictive":[48],"accuracy.":[49],"To":[50],"address":[51],"this":[52],"gap,":[53],"we":[54],"propose":[55],"a":[56,65,77],"novel":[57],"Spatio-Temporal":[58],"Missing-aware":[59],"Mixture-of-Experts":[60],"(STMMoE)":[61],"architecture,":[62],"equipped":[63],"with":[64],"three-stage":[66,86],"training":[67,87],"strategy.":[68],"STMMoE":[69],"adapts":[71],"to":[72],"varying":[73],"through":[76],"gating":[78],"mechanism":[79],"that":[80,109],"selects":[81],"specialized":[82],"expert":[83],"branches.":[84],"The":[85],"strategy":[88],"improves":[89],"end-to-end":[90],"performance":[92],"by":[93],"aligning":[94],"representations":[96],"complete":[98],"data.":[101],"Extensive":[102],"experiments":[103],"on":[104],"two":[105],"datasets":[107],"show":[108],"our":[110],"method":[111],"achieves":[112],"state-of-the-art":[113],"performance.":[114]},"counts_by_year":[],"updated_date":"2025-11-08T23:25:12.792448","created_date":"2025-11-08T00:00:00"}