{"id":"https://openalex.org/W2913690911","doi":"https://doi.org/10.1109/bigdata.2018.8622226","title":"Identification of Traffic Accident Clusters using Kulldorff\u2019s Space-Time Scan Statistics","display_name":"Identification of Traffic Accident Clusters using Kulldorff\u2019s Space-Time Scan Statistics","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2913690911","doi":"https://doi.org/10.1109/bigdata.2018.8622226","mag":"2913690911"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2018.8622226","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2018.8622226","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Big Data (Big Data)","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/A5101615703","display_name":"Junxian Song","orcid":"https://orcid.org/0000-0002-2982-5538"},"institutions":[{"id":"https://openalex.org/I4210091207","display_name":"Singapore Institute of Manufacturing Technology","ror":"https://ror.org/00f44np30","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I4210091207","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Junxian Song","raw_affiliation_strings":["Planning and Operations Management Group, Singapore Institute of Manufacturing Technology, Singapore"],"affiliations":[{"raw_affiliation_string":"Planning and Operations Management Group, Singapore Institute of Manufacturing Technology, Singapore","institution_ids":["https://openalex.org/I4210091207"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100686432","display_name":"Rong Wen","orcid":"https://orcid.org/0000-0002-8526-1626"},"institutions":[{"id":"https://openalex.org/I4210091207","display_name":"Singapore Institute of Manufacturing Technology","ror":"https://ror.org/00f44np30","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I4210091207","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Rong Wen","raw_affiliation_strings":["Planning and Operations Management Group, Singapore Institute of Manufacturing Technology, Singapore"],"affiliations":[{"raw_affiliation_string":"Planning and Operations Management Group, Singapore Institute of Manufacturing Technology, Singapore","institution_ids":["https://openalex.org/I4210091207"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101964528","display_name":"Wenjing Yan","orcid":"https://orcid.org/0000-0001-7115-4486"},"institutions":[{"id":"https://openalex.org/I4210091207","display_name":"Singapore Institute of Manufacturing Technology","ror":"https://ror.org/00f44np30","country_code":"SG","type":"facility","lineage":["https://openalex.org/I115228651","https://openalex.org/I4210091207","https://openalex.org/I91275662"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Wenjing Yan","raw_affiliation_strings":["Planning and Operations Management Group, Singapore Institute of Manufacturing Technology, Singapore"],"affiliations":[{"raw_affiliation_string":"Planning and Operations Management Group, Singapore Institute of Manufacturing Technology, Singapore","institution_ids":["https://openalex.org/I4210091207"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101615703"],"corresponding_institution_ids":["https://openalex.org/I4210091207"],"apc_list":null,"apc_paid":null,"fwci":0.6482,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.72246857,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3162","last_page":"3167"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9994000196456909,"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":0.9994000196456909,"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/T10370","display_name":"Traffic and Road Safety","score":0.9761000275611877,"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"}},{"id":"https://openalex.org/T11911","display_name":"Spatial and Panel Data Analysis","score":0.9757999777793884,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5993373990058899},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5448278784751892},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4550217092037201},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20942464470863342}],"concepts":[{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5993373990058899},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5448278784751892},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4550217092037201},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20942464470863342},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2018.8622226","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2018.8622226","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.8299999833106995,"display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W173828107","https://openalex.org/W1700547585","https://openalex.org/W1968141501","https://openalex.org/W2002151188","https://openalex.org/W2017755807","https://openalex.org/W2032608643","https://openalex.org/W2050497243","https://openalex.org/W2082851087","https://openalex.org/W2094551066","https://openalex.org/W2095753636","https://openalex.org/W2112348586","https://openalex.org/W2119721623","https://openalex.org/W2581907372","https://openalex.org/W2780031658","https://openalex.org/W2800135497","https://openalex.org/W4240868628","https://openalex.org/W6607021460","https://openalex.org/W6676606992","https://openalex.org/W6733056516"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2093578348","https://openalex.org/W2376932109","https://openalex.org/W2382290278","https://openalex.org/W2766271392","https://openalex.org/W2350741829","https://openalex.org/W2363804782"],"abstract_inverted_index":{"Identifying":[0],"traffic":[1,108,203],"accident":[2,17,109,129,204],"clusters":[3,79,115,184],"is":[4,122,143,180,213],"vital":[5],"in":[6,15,47,124,135],"helping":[7],"road":[8],"users":[9],"and":[10,24,27,138,155,157,206,222],"policymakers":[11],"make":[12],"better":[13,36,69],"decisions":[14],"managing":[16],"risks.":[18],"Traffic":[19],"accidents":[20],"contain":[21],"both":[22,136],"spatial":[23,60,73],"temporal":[25,75,78],"dimensions":[26],"their":[28],"interaction":[29],"should":[30],"be":[31,86],"analyzed":[32],"to":[33,106,126,149,215],"have":[34,150],"a":[35,71,118,173,181],"understanding":[37],"of":[38,41,64,101,175,224],"the":[39,42,65,77,82,99,145,159,176,199,207,218],"nature":[40],"clusters.":[43,111,227],"Similar":[44],"studies":[45],"conducted":[46,197],"this":[48,68,95,211],"area":[49],"rely":[50],"on":[51,62,198],"manually":[52],"sorting":[53],"data":[54],"into":[55],"time":[56,156],"buckets":[57],"before":[58],"conducting":[59],"analysis":[61],"each":[63,170],"buckets.":[66],"While":[67],"than":[70],"purely":[72],"or":[74,89],"analysis,":[76],"defined":[80],"by":[81,116],"researcher":[83],"may":[84],"not":[85],"statistically":[87,187,225],"significant":[88,226],"reveal":[90],"meaningful":[91],"space-time":[92,103],"interactions.":[93],"In":[94],"paper,":[96],"we":[97],"describe":[98],"use":[100],"Kulldorff's":[102],"scan":[104],"statistics":[105],"identify":[107],"spatiotemporal":[110],"The":[112,140,162,183],"method":[113,212],"identifies":[114],"using":[117,189],"scanning":[119],"cylinder":[120,171],"that":[121,144,178,210],"varying":[123],"size":[125,221],"search":[127],"for":[128,169],"cases":[130,146],"which":[131],"are":[132,147],"close":[133],"together":[134],"space":[137,154],"time.":[139],"null":[141],"hypothesis":[142,192],"assumed":[148],"constant":[151],"risk":[152],"over":[153],"follow":[158],"Poisson":[160,163],"distribution.":[161],"generalized":[164],"likelihood":[165],"ratio":[166],"was":[167,196],"determined":[168],"as":[172],"measure":[174],"evidence":[177],"it":[179],"hotspot.":[182],"were":[185],"then":[186],"evaluated":[188],"Monte":[190],"Carlo":[191],"testing.":[193],"This":[194],"study":[195],"2016":[200],"United":[201],"Kingdom":[202],"dataset":[205],"results":[208],"show":[209],"able":[214],"pin":[216],"point":[217],"exact":[219],"location,":[220],"period":[223]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}