{"id":"https://openalex.org/W2808535700","doi":"https://doi.org/10.24963/ijcai.2018/476","title":"GeoMAN: Multi-level Attention Networks for Geo-sensory Time Series Prediction","display_name":"GeoMAN: Multi-level Attention Networks for Geo-sensory Time Series Prediction","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2808535700","doi":"https://doi.org/10.24963/ijcai.2018/476","mag":"2808535700"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2018/476","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/476","pdf_url":"https://www.ijcai.org/proceedings/2018/0476.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2018/0476.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018828723","display_name":"Yuxuan Liang","orcid":"https://orcid.org/0000-0003-2817-7337"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]},{"id":"https://openalex.org/I4210139765","display_name":"Beijing Computing Center","ror":"https://ror.org/047r47y76","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210139765"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuxuan Liang","raw_affiliation_strings":["School of Computer Science and Technology, Xidian University, Xi'an, China","Urban Computing Business Unit, JD Finance, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Urban Computing Business Unit, JD Finance, Beijing, China","institution_ids":["https://openalex.org/I4210139765"]}]},{"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/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]},{"id":"https://openalex.org/I4210139765","display_name":"Beijing Computing Center","ror":"https://ror.org/047r47y76","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210139765"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Songyu Ke","raw_affiliation_strings":["Urban Computing Business Unit, JD Finance, Beijing, China","Zhiyuan College, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Urban Computing Business Unit, JD Finance, Beijing, China","institution_ids":["https://openalex.org/I4210139765"]},{"raw_affiliation_string":"Zhiyuan College, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"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/I4210139765","display_name":"Beijing Computing Center","ror":"https://ror.org/047r47y76","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210139765"]},{"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":"Junbo Zhang","raw_affiliation_strings":["School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China","Urban Computing Business Unit, JD Finance, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]},{"raw_affiliation_string":"Urban Computing Business Unit, JD Finance, Beijing, China","institution_ids":["https://openalex.org/I4210139765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013889855","display_name":"Xiuwen Yi","orcid":"https://orcid.org/0000-0003-2703-6794"},"institutions":[{"id":"https://openalex.org/I4210139765","display_name":"Beijing Computing Center","ror":"https://ror.org/047r47y76","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210139765"]},{"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":"Xiuwen Yi","raw_affiliation_strings":["School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China","Urban Computing Business Unit, JD Finance, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]},{"raw_affiliation_string":"Urban Computing Business Unit, JD Finance, Beijing, China","institution_ids":["https://openalex.org/I4210139765"]}]},{"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/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]},{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]},{"id":"https://openalex.org/I4210139765","display_name":"Beijing Computing Center","ror":"https://ror.org/047r47y76","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210139765"]},{"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":"Yu Zheng","raw_affiliation_strings":["School of Computer Science and Technology, Xidian University, Xi'an, China","School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China","Urban Computing Business Unit, JD Finance, Beijing, China","Zhiyuan College, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]},{"raw_affiliation_string":"Urban Computing Business Unit, JD Finance, Beijing, China","institution_ids":["https://openalex.org/I4210139765"]},{"raw_affiliation_string":"Zhiyuan College, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5018828723"],"corresponding_institution_ids":["https://openalex.org/I149594827","https://openalex.org/I4210139765"],"apc_list":null,"apc_paid":null,"fwci":37.0716,"has_fulltext":false,"cited_by_count":516,"citation_normalized_percentile":{"value":0.99915249,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3428","last_page":"3434"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9965000152587891,"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":0.9965000152587891,"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/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9947999715805054,"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"}},{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.991100013256073,"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/computer-science","display_name":"Computer science","score":0.7515062093734741},{"id":"https://openalex.org/keywords/geospatial-analysis","display_name":"Geospatial analysis","score":0.6318476796150208},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5757681131362915},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5714826583862305},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5645280480384827},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.539381742477417},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5170355439186096},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.50336092710495},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4241958260536194},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.343790203332901},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.1856602132320404},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.133795827627182}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7515062093734741},{"id":"https://openalex.org/C9770341","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Geospatial analysis","level":2,"score":0.6318476796150208},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5757681131362915},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5714826583862305},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5645280480384827},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.539381742477417},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5170355439186096},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.50336092710495},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4241958260536194},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.343790203332901},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.1856602132320404},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.133795827627182},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"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:10.24963/ijcai.2018/476","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/476","pdf_url":"https://www.ijcai.org/proceedings/2018/0476.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2018/476","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/476","pdf_url":"https://www.ijcai.org/proceedings/2018/0476.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/6","display_name":"Clean water and sanitation","score":0.6399999856948853}],"awards":[{"id":"https://openalex.org/G2859735059","display_name":null,"funder_award_id":"2015CB352400","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G4814215590","display_name":null,"funder_award_id":"61672399","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5047629933","display_name":null,"funder_award_id":"U1609217","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"},{"id":"https://openalex.org/F4320322392","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2808535700.pdf","grobid_xml":"https://content.openalex.org/works/W2808535700.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W1511986666","https://openalex.org/W1522301498","https://openalex.org/W1678356000","https://openalex.org/W1969865391","https://openalex.org/W2016287239","https://openalex.org/W2036785686","https://openalex.org/W2062275317","https://openalex.org/W2103452139","https://openalex.org/W2130942839","https://openalex.org/W2133564696","https://openalex.org/W2140325612","https://openalex.org/W2157331557","https://openalex.org/W2271840356","https://openalex.org/W2466025545","https://openalex.org/W2513378248","https://openalex.org/W2528639018","https://openalex.org/W2530386080","https://openalex.org/W2546521009","https://openalex.org/W2613328025","https://openalex.org/W2732016772","https://openalex.org/W2762079755","https://openalex.org/W2788997482","https://openalex.org/W2964199361","https://openalex.org/W2964308564","https://openalex.org/W4233713109"],"related_works":["https://openalex.org/W2004086023","https://openalex.org/W4367313141","https://openalex.org/W2733999579","https://openalex.org/W2910751785","https://openalex.org/W2110217573","https://openalex.org/W2622688551","https://openalex.org/W2119012848","https://openalex.org/W1990205660","https://openalex.org/W1550175370","https://openalex.org/W4387331850"],"abstract_inverted_index":{"Numerous":[0],"sensors":[1,23],"have":[2],"been":[3],"deployed":[4],"in":[5],"different":[6,124],"geospatial":[7],"locations":[8],"to":[9,107,118],"continuously":[10],"and":[11,58,90,137],"cooperatively":[12],"monitor":[13],"the":[14,19,66,109,120],"surrounding":[15],"environment,":[16],"such":[17],"as":[18,46],"air":[20,134],"quality.":[21],"These":[22],"generate":[24],"multiple":[25,85],"geo-sensory":[26,36],"time":[27,37],"series,":[28],"with":[29],"spatial":[30,91],"correlations":[31,57],"between":[32],"their":[33],"readings.":[34],"Forecasting":[35],"series":[38],"is":[39,48],"of":[40,68,98,130],"great":[41],"importance":[42],"yet":[43],"very":[44],"challenging":[45],"it":[47],"affected":[49],"by":[50,75],"many":[51],"complex":[52],"factors,":[53],"i.e.,":[54],"dynamic":[55,110],"spatio-temporal":[56,111],"external":[59,121],"factors.":[60],"In":[61],"this":[62],"paper,":[63],"we":[64],"predict":[65],"readings":[67],"a":[69,77,103,114],"geo-sensor":[70],"over":[71],"several":[72],"future":[73],"hours":[74],"using":[76],"multi-level":[78,104],"attention-based":[79],"recurrent":[80],"neural":[81],"network":[82],"that":[83,142],"considers":[84],"sensors'":[86],"readings,":[87],"meteorological":[88],"data,":[89,140],"data.":[92],"More":[93],"specifically,":[94],"our":[95,143],"model":[96,108],"consists":[97],"two":[99,128],"major":[100],"parts:":[101],"1)":[102],"attention":[105],"mechanism":[106],"dependencies.":[112],"2)":[113],"general":[115],"fusion":[116],"module":[117],"incorporate":[119],"factors":[122],"from":[123],"domains.":[125],"Experiments":[126],"on":[127],"types":[129],"real-world":[131],"datasets,":[132],"viz.,":[133],"quality":[135,139],"data":[136],"water":[138],"demonstrate":[141],"method":[144],"outperforms":[145],"nine":[146],"baseline":[147],"methods.":[148]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":57},{"year":2024,"cited_by_count":60},{"year":2023,"cited_by_count":71},{"year":2022,"cited_by_count":98},{"year":2021,"cited_by_count":92},{"year":2020,"cited_by_count":75},{"year":2019,"cited_by_count":51},{"year":2018,"cited_by_count":5}],"updated_date":"2026-06-06T09:05:17.133730","created_date":"2025-10-10T00:00:00"}
