{"id":"https://openalex.org/W3208946914","doi":"https://doi.org/10.1145/3459637.3482482","title":"Spatio-Temporal-Categorical Graph Neural Networks for Fine-Grained Multi-Incident Co-Prediction","display_name":"Spatio-Temporal-Categorical Graph Neural Networks for Fine-Grained Multi-Incident Co-Prediction","publication_year":2021,"publication_date":"2021-10-26","ids":{"openalex":"https://openalex.org/W3208946914","doi":"https://doi.org/10.1145/3459637.3482482","mag":"3208946914"},"language":"en","primary_location":{"id":"doi:10.1145/3459637.3482482","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482482","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information & 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/A5070106281","display_name":"Zhaonan Wang","orcid":"https://orcid.org/0000-0002-2613-9727"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Zhaonan Wang","raw_affiliation_strings":["University of Tokyo, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040449880","display_name":"Renhe Jiang","orcid":"https://orcid.org/0000-0003-2593-4638"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Renhe Jiang","raw_affiliation_strings":["University of Tokyo & Southern University of Science and Technology, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tokyo & Southern University of Science and Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108659841","display_name":"Zekun Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Zekun Cai","raw_affiliation_strings":["University of Tokyo, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009062546","display_name":"Zipei Fan","orcid":"https://orcid.org/0000-0002-1442-1530"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Zipei Fan","raw_affiliation_strings":["University of Tokyo & Southern University of Science and Technology, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tokyo & Southern University of Science and Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011513741","display_name":"Xin Liu","orcid":"https://orcid.org/0000-0002-2336-7409"},"institutions":[{"id":"https://openalex.org/I73613424","display_name":"National Institute of Advanced Industrial Science and Technology","ror":"https://ror.org/01703db54","country_code":"JP","type":"government","lineage":["https://openalex.org/I73613424"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xin Liu","raw_affiliation_strings":["National Institute of Advanced Industrial Science and Technology & AIST-Tokyo Tech Real World Big-Data Computation Open Innovation Laboratory, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Advanced Industrial Science and Technology & AIST-Tokyo Tech Real World Big-Data Computation Open Innovation Laboratory, Tokyo, Japan","institution_ids":["https://openalex.org/I73613424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064163755","display_name":"Kyoung\u2010Sook Kim","orcid":"https://orcid.org/0000-0003-0670-8053"},"institutions":[{"id":"https://openalex.org/I73613424","display_name":"National Institute of Advanced Industrial Science and Technology","ror":"https://ror.org/01703db54","country_code":"JP","type":"government","lineage":["https://openalex.org/I73613424"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kyoung-Sook Kim","raw_affiliation_strings":["National Institute of Advanced Industrial Science and Technology & AIST-Tokyo Tech Real World Big-Data Computation Open Innovation Laboratory, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Advanced Industrial Science and Technology & AIST-Tokyo Tech Real World Big-Data Computation Open Innovation Laboratory, Tokyo, Japan","institution_ids":["https://openalex.org/I73613424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046856721","display_name":"Xuan Song","orcid":"https://orcid.org/0000-0003-4042-7888"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xuan Song","raw_affiliation_strings":["University of Tokyo & Southern University of Science and Technology, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tokyo & Southern University of Science and Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5105206953","display_name":"Ryosuke Shibasaki","orcid":"https://orcid.org/0000-0001-8760-244X"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ryosuke Shibasaki","raw_affiliation_strings":["University of Tokyo, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.8748,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.84070017,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2060","last_page":"2069"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":1.0,"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":1.0,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9962999820709229,"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/T10370","display_name":"Traffic and Road Safety","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/categorical-variable","display_name":"Categorical variable","score":0.8471753597259521},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7872854471206665},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5567613244056702},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47990521788597107},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4757513701915741},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4392460286617279},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41550692915916443},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.4119929075241089},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.385622501373291},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.205125093460083}],"concepts":[{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.8471753597259521},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7872854471206665},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5567613244056702},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47990521788597107},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4757513701915741},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4392460286617279},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41550692915916443},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.4119929075241089},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.385622501373291},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.205125093460083},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"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:10.1145/3459637.3482482","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482482","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information & Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6600000262260437,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G1109955749","display_name":"Neural Network based Graph Learning: Model Evolution and Real-World Application","funder_award_id":"21K12042","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G4984633598","display_name":"A Benchmark for Video-Like Urban Computing on Citywide Crowd and Traffic Prediction","funder_award_id":"20K19859","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G7531168543","display_name":"An Online Adaptive Boosting Ensemble Approach to Human Mobility Prediction at a Metropolitan Scale","funder_award_id":"20K19782","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2082633923","https://openalex.org/W2468907370","https://openalex.org/W2593390416","https://openalex.org/W2739639530","https://openalex.org/W2767949765","https://openalex.org/W2788134583","https://openalex.org/W2808862972","https://openalex.org/W2884796212","https://openalex.org/W2890096158","https://openalex.org/W2895806569","https://openalex.org/W2904449562","https://openalex.org/W2904832339","https://openalex.org/W2911535719","https://openalex.org/W2950099298","https://openalex.org/W2952734551","https://openalex.org/W2962817261","https://openalex.org/W2963043672","https://openalex.org/W2963984147","https://openalex.org/W2965341826","https://openalex.org/W2996451395","https://openalex.org/W3003651988","https://openalex.org/W3012735076","https://openalex.org/W3034826934","https://openalex.org/W3038981236","https://openalex.org/W3080253043","https://openalex.org/W3100809784","https://openalex.org/W3103720336","https://openalex.org/W3177028972","https://openalex.org/W4288278954"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W4386799044","https://openalex.org/W2773208253","https://openalex.org/W2560646951","https://openalex.org/W4297454206","https://openalex.org/W65104662","https://openalex.org/W1871748041","https://openalex.org/W2362286668","https://openalex.org/W2133382151","https://openalex.org/W2153339597"],"abstract_inverted_index":{"Forecasting":[0],"incident":[1,65,99,172],"occurrences":[2],"(e.g.":[3,72],"crime,":[4],"EMS,":[5],"traffic":[6],"accident)":[7],"is":[8],"a":[9,69,103,142],"crucial":[10],"task":[11],"for":[12,86,161],"emergency":[13],"service":[14],"providers":[15],"and":[16,24,35,43,84,132,157,180],"transportation":[17],"agencies":[18],"in":[19,68,102,119],"performing":[20,162],"response":[21],"time":[22],"optimization":[23],"dynamic":[25,158],"fleet":[26],"management.":[27],"However,":[28],"such":[29],"events":[30],"are":[31],"by":[32,62,106],"nature":[33],"rare":[34],"sparse,":[36],"which":[37,75,125],"causes":[38],"the":[39,64,77,87,96,109,129,155,175,183],"label":[40],"imbalance":[41],"problem":[42,67,101],"inferior":[44],"performance":[45],"of":[46,57,177,182],"models":[47,79],"relying":[48],"on":[49,168],"data":[50],"sufficiency.":[51],"The":[52],"existing":[53],"studies":[54],"circumvent,":[55],"instead":[56],"truly":[58],"solving,":[59],"this":[60,92,115],"issue":[61],"defining":[63],"prediction":[66,100],"coarse-grained":[70],"temporal":[71,130],"daily)":[73],"setting,":[74],"leaves":[76],"proposed":[78,184],"unrobust":[80],"to":[81,134,153],"fine-grained":[82,98,163],"dynamics":[83],"trivial":[85],"real-world":[88,170],"decision":[89],"making.":[90],"In":[91],"paper,":[93],"we":[94,140],"tackle":[95],"temporally":[97],"sparse":[104],"setting":[105],"explicitly":[107],"exploiting":[108],"behind-the-scene":[110],"chainlike":[111],"triggering":[112],"mechanism.":[113],"Moreover,":[114],"chain":[116,159],"effect":[117,160],"roots":[118],"multiple":[120],"domains":[121],"(i.e.":[122],"spatial,":[123],"categorical),":[124],"further":[126],"entangles":[127],"with":[128],"dimension":[131],"happens":[133],"be":[135,138],"time-variant.":[136],"To":[137],"specific,":[139],"propose":[141],"novel":[143],"deep":[144],"learning":[145],"framework,":[146],"namely":[147],"Spatio-Temporal-Categorical":[148],"Graph":[149],"Neural":[150],"Networks":[151],"(STC-GNN),":[152],"handle":[154],"multidimensional":[156],"multi-incident":[164],"co-prediction.":[165],"Extensive":[166],"experiments":[167],"three":[169],"city-level":[171],"datasets":[173],"verify":[174],"insightfulness":[176],"our":[178],"perspective":[179],"effectiveness":[181],"model.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":3}],"updated_date":"2026-07-09T07:52:08.696243","created_date":"2025-10-10T00:00:00"}