{"id":"https://openalex.org/W2901339881","doi":"https://doi.org/10.1145/3274895.3274994","title":"Theft prediction with individual risk factor of visitors","display_name":"Theft prediction with individual risk factor of visitors","publication_year":2018,"publication_date":"2018-11-06","ids":{"openalex":"https://openalex.org/W2901339881","doi":"https://doi.org/10.1145/3274895.3274994","mag":"2901339881"},"language":"en","primary_location":{"id":"doi:10.1145/3274895.3274994","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3274895.3274994","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/conference_contribution/Theft_prediction_with_individual_risk_factor_of_visitors/27583875","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054869158","display_name":"Shakila Khan Rumi","orcid":"https://orcid.org/0000-0002-8927-597X"},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]},{"id":"https://openalex.org/I4210095297","display_name":"MIT University","ror":"https://ror.org/00v140q16","country_code":"MK","type":"education","lineage":["https://openalex.org/I4210095297"]}],"countries":["AU","MK"],"is_corresponding":true,"raw_author_name":"Shakila Khan Rumi","raw_affiliation_strings":["RMIT University, Melbourne, VIC"],"affiliations":[{"raw_affiliation_string":"RMIT University, Melbourne, VIC","institution_ids":["https://openalex.org/I4210095297","https://openalex.org/I82951845"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101668440","display_name":"Ke Deng","orcid":"https://orcid.org/0000-0002-1008-2498"},"institutions":[{"id":"https://openalex.org/I4210095297","display_name":"MIT University","ror":"https://ror.org/00v140q16","country_code":"MK","type":"education","lineage":["https://openalex.org/I4210095297"]},{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU","MK"],"is_corresponding":false,"raw_author_name":"Ke Deng","raw_affiliation_strings":["RMIT University, Melbourne, VIC"],"affiliations":[{"raw_affiliation_string":"RMIT University, Melbourne, VIC","institution_ids":["https://openalex.org/I4210095297","https://openalex.org/I82951845"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090893421","display_name":"Flora D. Salim","orcid":"https://orcid.org/0000-0002-1237-1664"},"institutions":[{"id":"https://openalex.org/I4210095297","display_name":"MIT University","ror":"https://ror.org/00v140q16","country_code":"MK","type":"education","lineage":["https://openalex.org/I4210095297"]},{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU","MK"],"is_corresponding":false,"raw_author_name":"Flora D. Salim","raw_affiliation_strings":["RMIT University, Melbourne, VIC"],"affiliations":[{"raw_affiliation_string":"RMIT University, Melbourne, VIC","institution_ids":["https://openalex.org/I4210095297","https://openalex.org/I82951845"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5054869158"],"corresponding_institution_ids":["https://openalex.org/I4210095297","https://openalex.org/I82951845"],"apc_list":null,"apc_paid":null,"fwci":6.5476,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.9640752,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"552","last_page":"555"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10574","display_name":"Crime Patterns and Interventions","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10574","display_name":"Crime Patterns and Interventions","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.987500011920929,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9815999865531921,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.7051203846931458},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5453691482543945},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.47025883197784424},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3995519280433655},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3441816568374634},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.33900225162506104}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7051203846931458},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5453691482543945},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.47025883197784424},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3995519280433655},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3441816568374634},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.33900225162506104},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3274895.3274994","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3274895.3274994","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:alma.61RMIT_INST:11248112900001341","is_oa":false,"landing_page_url":"http://doi.org/10.1145/3274895.3274994","pdf_url":null,"source":{"id":"https://openalex.org/S4306402074","display_name":"RMIT Research Repository (RMIT University Library)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I82951845","host_organization_name":"RMIT University","host_organization_lineage":["https://openalex.org/I82951845"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"pmh:oai:figshare.com:article/27583875","is_oa":true,"landing_page_url":"https://figshare.com/articles/conference_contribution/Theft_prediction_with_individual_risk_factor_of_visitors/27583875","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/27583875","is_oa":true,"landing_page_url":"https://figshare.com/articles/conference_contribution/Theft_prediction_with_individual_risk_factor_of_visitors/27583875","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.8299999833106995,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W144670803","https://openalex.org/W157306979","https://openalex.org/W1951757437","https://openalex.org/W1967470069","https://openalex.org/W2035055162","https://openalex.org/W2056712395","https://openalex.org/W2071702404","https://openalex.org/W2112738128","https://openalex.org/W2128338591","https://openalex.org/W2147876157","https://openalex.org/W2171118265","https://openalex.org/W2189105228","https://openalex.org/W2294765051","https://openalex.org/W2513128224","https://openalex.org/W2514525802","https://openalex.org/W2752663873","https://openalex.org/W2767949765","https://openalex.org/W2768009948","https://openalex.org/W2895833243","https://openalex.org/W2963190848","https://openalex.org/W4231124864","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4224009465","https://openalex.org/W4286629047","https://openalex.org/W4306321456","https://openalex.org/W4285260836","https://openalex.org/W3046775127","https://openalex.org/W3170094116","https://openalex.org/W4205958290","https://openalex.org/W3209574120"],"abstract_inverted_index":{"Location-Based":[0],"Social":[1],"Networks":[2],"(LBSN)":[3],"provides":[4],"unprecedented":[5],"opportunities":[6],"to":[7],"tackle":[8],"various":[9],"social":[10],"problems.":[11],"In":[12],"this":[13],"study,":[14],"we":[15],"identify":[16],"a":[17],"number":[18],"of":[19,73],"crime-prediction-specific":[20,75],"dynamic":[21,43,76],"features":[22,44],"which,":[23],"for":[24],"the":[25,35,41,62,71],"first":[26],"time,":[27],"explore":[28],"crime":[29,46,63],"risk":[30],"factors":[31],"implicitly":[32],"associated":[33],"with":[34,70],"visitors.":[36],"The":[37,52],"reliable":[38],"correlations":[39],"between":[40],"proposed":[42,74],"and":[45],"event":[47],"occurrences":[48],"have":[49],"been":[50],"observed.":[51],"evaluations":[53],"on":[54],"large":[55],"real":[56],"world":[57],"data":[58],"sets":[59],"verify":[60],"that":[61],"prediction":[64],"performance":[65],"can":[66],"be":[67],"notably":[68],"improved":[69],"inclusion":[72],"features.":[77]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}