{"id":"https://openalex.org/W2581220703","doi":"https://doi.org/10.1109/tkde.2017.2657624","title":"Feature Constrained Multi-Task Learning Models for Spatiotemporal Event Forecasting","display_name":"Feature Constrained Multi-Task Learning Models for Spatiotemporal Event Forecasting","publication_year":2017,"publication_date":"2017-01-24","ids":{"openalex":"https://openalex.org/W2581220703","doi":"https://doi.org/10.1109/tkde.2017.2657624","mag":"2581220703"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2017.2657624","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2017.2657624","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-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/A5048756500","display_name":"Liang Zhao","orcid":"https://orcid.org/0000-0002-2648-9989"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Liang Zhao","raw_affiliation_strings":["Department of Information Science and Technology, George Mason University, Fairfax, VA"],"affiliations":[{"raw_affiliation_string":"Department of Information Science and Technology, George Mason University, Fairfax, VA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103218833","display_name":"Qian Sun","orcid":"https://orcid.org/0000-0002-2098-9878"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qian Sun","raw_affiliation_strings":["School of Computing, Informatics, and Decision System Engineering, Arizona State University, Phoenix, AZ"],"affiliations":[{"raw_affiliation_string":"School of Computing, Informatics, and Decision System Engineering, Arizona State University, Phoenix, AZ","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010419481","display_name":"Jieping Ye","orcid":"https://orcid.org/0000-0001-8662-5818"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jieping Ye","raw_affiliation_strings":["Department of Computational Medicine and Bioinformatics and the Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI"],"affiliations":[{"raw_affiliation_string":"Department of Computational Medicine and Bioinformatics and the Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100352703","display_name":"Feng Chen","orcid":"https://orcid.org/0000-0002-4508-5963"},"institutions":[{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Feng Chen","raw_affiliation_strings":["Department of Computer Science, University at Albany, Albany, NY"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University at Albany, Albany, NY","institution_ids":["https://openalex.org/I392282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038002204","display_name":"Chang\u2010Tien Lu","orcid":"https://orcid.org/0000-0003-3675-0199"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chang-Tien Lu","raw_affiliation_strings":["Department of Computer Science, Falls Church, VA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Falls Church, VA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035052603","display_name":"Naren Ramakrishnan","orcid":"https://orcid.org/0000-0002-1821-9743"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Naren Ramakrishnan","raw_affiliation_strings":["Department of Computer Science, Falls Church, VA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Falls Church, VA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5048756500"],"corresponding_institution_ids":["https://openalex.org/I162714631"],"apc_list":null,"apc_paid":null,"fwci":2.9362,"has_fulltext":false,"cited_by_count":46,"citation_normalized_percentile":{"value":0.91106657,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"29","issue":"5","first_page":"1059","last_page":"1072"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10757","display_name":"Geographic Information Systems Studies","score":0.9787999987602234,"subfield":{"id":"https://openalex.org/subfields/3305","display_name":"Geography, Planning and Development"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8312875628471375},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5672086477279663},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5514963865280151},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4793737232685089},{"id":"https://openalex.org/keywords/multi-task-learning","display_name":"Multi-task learning","score":0.4629197418689728},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.39302709698677063}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8312875628471375},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5672086477279663},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5514963865280151},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4793737232685089},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.4629197418689728},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.39302709698677063},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2017.2657624","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2017.2657624","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306116","display_name":"U.S. Department of the Interior","ror":"https://ror.org/03v0pmy70"},{"id":"https://openalex.org/F4320333051","display_name":"Intelligence Advanced Research Projects Activity","ror":"https://ror.org/01v3fsc55"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W11244355","https://openalex.org/W144670803","https://openalex.org/W797920393","https://openalex.org/W1980454827","https://openalex.org/W1998635907","https://openalex.org/W1999529874","https://openalex.org/W2007159951","https://openalex.org/W2016081253","https://openalex.org/W2034295546","https://openalex.org/W2054667730","https://openalex.org/W2057313398","https://openalex.org/W2100556411","https://openalex.org/W2109734180","https://openalex.org/W2112946723","https://openalex.org/W2116413942","https://openalex.org/W2122369144","https://openalex.org/W2124499489","https://openalex.org/W2126204609","https://openalex.org/W2130903752","https://openalex.org/W2135046866","https://openalex.org/W2136284997","https://openalex.org/W2143104527","https://openalex.org/W2143376306","https://openalex.org/W2147194983","https://openalex.org/W2154231875","https://openalex.org/W2165644552","https://openalex.org/W2171468534","https://openalex.org/W2209233556","https://openalex.org/W2244985651","https://openalex.org/W2404243041","https://openalex.org/W2404453404","https://openalex.org/W2913340405","https://openalex.org/W2963322354","https://openalex.org/W6600459962","https://openalex.org/W6622627190","https://openalex.org/W6677144666","https://openalex.org/W6677204830","https://openalex.org/W6679734692","https://openalex.org/W6682433143","https://openalex.org/W6684671274","https://openalex.org/W6690766546"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347","https://openalex.org/W4210805261"],"abstract_inverted_index":{"Spatial":[0],"event":[1],"forecasting":[2,82,110],"from":[3,12,120,131,182],"social":[4],"media":[5],"is":[6],"potentially":[7],"extremely":[8],"useful":[9],"but":[10,51],"suffers":[11],"critical":[13],"challenges,":[14],"such":[15],"as":[16],"the":[17,71,88,101,109,190],"dynamic":[18,43,128,132,151],"patterns":[19],"of":[20,54,78,194],"features":[21,118,129],"(keywords)":[22],"and":[23,31,46,93,127,146,150,170,174,185,192],"geographic":[24],"heterogeneity":[25],"(e.g.,":[26,40,80],"spatial":[27],"correlations,":[28],"imbalanced":[29],"samples,":[30],"different":[32,35],"populations":[33],"in":[34,135],"locations).":[36],"Most":[37],"existing":[38],"approaches":[39],"LASSO":[41],"regression,":[42],"query":[44,133],"expansion,":[45],"burst":[47],"detection)":[48],"address":[49,69],"some,":[50],"not":[52],"all,":[53],"these":[55],"challenges.":[56],"Here,":[57],"we":[58],"propose":[59],"a":[60,76,121,136],"novel":[61],"multi-task":[62,137],"learning":[63,139],"framework":[64],"that":[65,98],"aims":[66],"to":[67,143,167],"concurrently":[68],"all":[70,87],"challenges":[72],"involved.":[73],"Specifically,":[74],"given":[75],"collection":[77],"locations":[79,89],"cities),":[81],"models":[83],"are":[84,153,165],"built":[85],"for":[86,104],"simultaneously":[90],"by":[91,124],"extracting":[92],"utilizing":[94],"appropriate":[95],"shared":[96],"information":[97],"effectively":[99],"increases":[100],"sample":[102],"size":[103],"each":[105],"location,":[106],"thus":[107],"improving":[108],"performance.":[111],"The":[112],"new":[113],"model":[114,172],"combines":[115],"both":[116],"static":[117,149],"derived":[119],"predefined":[122],"vocabulary":[123],"domain":[125],"experts":[126],"generated":[130],"expansion":[134],"feature":[138],"framework.":[140],"Different":[141],"strategies":[142],"balance":[144],"homogeneity":[145],"diversity":[147],"between":[148],"terms":[152],"also":[154],"investigated.":[155],"And,":[156],"efficient":[157,169],"algorithms":[158],"based":[159],"on":[160,179],"Iterative":[161],"Group":[162],"Hard":[163],"Thresholding":[164],"developed":[166],"achieve":[168],"effective":[171],"training":[173],"prediction.":[175],"Extensive":[176],"experimental":[177],"evaluations":[178],"Twitter":[180],"data":[181],"civil":[183],"unrest":[184],"influenza":[186],"outbreak":[187],"datasets":[188],"demonstrate":[189],"effectiveness":[191],"efficiency":[193],"our":[195],"proposed":[196],"approach.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":2}],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2025-10-10T00:00:00"}