{"id":"https://openalex.org/W3089838435","doi":"https://doi.org/10.1109/access.2020.3028420","title":"Comparison of Machine Learning Algorithms for Predicting Crime Hotspots","display_name":"Comparison of Machine Learning Algorithms for Predicting Crime Hotspots","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3089838435","doi":"https://doi.org/10.1109/access.2020.3028420","mag":"3089838435"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3028420","doi":"https://doi.org/10.1109/access.2020.3028420","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3028420","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09211482.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","oarl","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09211482.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103030258","display_name":"Xu Zhang","orcid":"https://orcid.org/0000-0001-9364-0418","observed_orcids":["https://orcid.org/0000-0001-9364-0418"]},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Zhang","raw_affiliation_strings":["Center of Geoinformatics for Public Security, School of Geographic Sciences, Guangzhou University, Guangzhou, China","School of Computer Sciences and Cyber Engineering, Guangzhou University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-9364-0418","affiliations":[{"raw_affiliation_string":"Center of Geoinformatics for Public Security, School of Geographic Sciences, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]},{"raw_affiliation_string":"School of Computer Sciences and Cyber Engineering, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100383312","display_name":"Lin Liu","orcid":"https://orcid.org/0000-0002-7202-3418","observed_orcids":["https://orcid.org/0000-0002-7202-3418","https://orcid.org/0000-0002-9883-7962","https://orcid.org/0009-0003-1273-4204"]},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Liu","raw_affiliation_strings":["Center of Geoinformatics for Public Security, School of Geographic Sciences, Guangzhou University, Guangzhou, China","School of Computer Sciences and Cyber Engineering, Guangzhou University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center of Geoinformatics for Public Security, School of Geographic Sciences, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]},{"raw_affiliation_string":"School of Computer Sciences and Cyber Engineering, Guangzhou University, Guangzhou, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006645212","display_name":"Luzi Xiao","orcid":"https://orcid.org/0000-0002-6318-8958","observed_orcids":["https://orcid.org/0000-0002-6318-8958"]},"institutions":[{"id":"https://openalex.org/I63135867","display_name":"University of Cincinnati","ror":"https://ror.org/01e3m7079","country_code":"US","type":"education","lineage":["https://openalex.org/I63135867"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Luzi Xiao","raw_affiliation_strings":["University of Cincinnati, Cincinnati, OH, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Cincinnati, Cincinnati, OH, USA","institution_ids":["https://openalex.org/I63135867"]}]},{"author_position":"last","author":{"id":null,"display_name":"Jiakai Ji","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiakai Ji","raw_affiliation_strings":["School of Geography and Planning, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geography and Planning, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1750,"currency":"USD","value_usd":1750},"apc_paid":{"value":1750,"currency":"USD","value_usd":1750},"fwci":14.404,"has_fulltext":true,"cited_by_count":104,"citation_normalized_percentile":{"value":0.98856255,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"8","issue":null,"first_page":"181302","last_page":"181310"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10574","display_name":"Crime Patterns and Interventions","score":0.9824000000953674,"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":0.9824000000953674,"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/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.004000000189989805,"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"}},{"id":"https://openalex.org/T12736","display_name":"Criminal Justice and Penology","score":0.0015999999595806003,"subfield":{"id":"https://openalex.org/subfields/3308","display_name":"Law"},"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/crime-prediction","display_name":"crime prediction","score":0.8669999837875366},{"id":"https://openalex.org/keywords/crime-hotspots","display_name":"crime hotspots","score":0.9739999771118164},{"id":"https://openalex.org/keywords/lstm","display_name":"LSTM","score":0.8790000081062317},{"id":"https://openalex.org/keywords/algorithm-comparison","display_name":"algorithm comparison","score":0.6240000128746033},{"id":"https://openalex.org/keywords/points-of-interest","display_name":"points of interest","score":0.9769999980926514},{"id":"https://openalex.org/keywords/road-density","display_name":"road density","score":0.9480000138282776},{"id":"https://openalex.org/keywords/crime-prevention","display_name":"crime prevention","score":0.597000002861023}],"concepts":[{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.8004002571105957},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7283116579055786},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7204850316047668},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6349554657936096},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5425856709480286},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.5206966996192932},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.51715487241745},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.4901960492134094},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4546440541744232},{"id":"https://openalex.org/C2778136018","wikidata":"https://www.wikidata.org/wiki/Q10350689","display_name":"Predictive power","level":2,"score":0.4225309491157532},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4122962951660156},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33265095949172974},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.27539438009262085},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3028420","doi":"https://doi.org/10.1109/access.2020.3028420","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3028420","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09211482.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","oarl","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:df0403d54fcc412a9a4de0728f329c53","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/df0403d54fcc412a9a4de0728f329c53","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 181302-181310 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3028420","doi":"https://doi.org/10.1109/access.2020.3028420","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3028420","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09211482.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","oarl","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.761900007724762,"id":"https://metadata.un.org/sdg/11"},{"display_name":"Peace, justice, and strong institutions","score":0.6207000017166138,"id":"https://metadata.un.org/sdg/16"}],"study_designs":[],"awards":[{"id":"https://openalex.org/G1738824791","display_name":null,"funder_award_id":"201804020016","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4571068981","display_name":null,"funder_award_id":"2014A030312010","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G559231134","display_name":null,"funder_award_id":"201804020016","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G6509972312","display_name":"\u5927\u6570\u636e\u652f\u6301\u4e0b\u7684\u72af\u7f6a\u5730\u7406\u7814\u7a76\u2014\u72af\u7f6a\u65f6\u7a7a\u8fc7\u7a0b\u7cbe\u7ec6\u5316\u6a21\u62df\u4e0e\u9632\u63a7\u4f18\u5316","funder_award_id":"41531178","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6863389657","display_name":null,"funder_award_id":"2014A030312010","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8157661444","display_name":null,"funder_award_id":"2018YFB0505500","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8593743825","display_name":null,"funder_award_id":"2018YFB0505503","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G921776079","display_name":null,"funder_award_id":"2018YFB0505500","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program 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/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3089838435.pdf","grobid_xml":"https://content.openalex.org/works/W3089838435.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W166741661","https://openalex.org/W218921420","https://openalex.org/W1555696814","https://openalex.org/W1594007058","https://openalex.org/W1607368817","https://openalex.org/W1901616594","https://openalex.org/W1905728931","https://openalex.org/W1978208906","https://openalex.org/W2016966554","https://openalex.org/W2052633775","https://openalex.org/W2055195255","https://openalex.org/W2064239738","https://openalex.org/W2080763235","https://openalex.org/W2086260676","https://openalex.org/W2088047416","https://openalex.org/W2132424470","https://openalex.org/W2134006231","https://openalex.org/W2143635696","https://openalex.org/W2303210576","https://openalex.org/W2315731341","https://openalex.org/W2325408928","https://openalex.org/W2387591080","https://openalex.org/W2511539680","https://openalex.org/W2518898439","https://openalex.org/W2632538366","https://openalex.org/W2747062477","https://openalex.org/W2760894977","https://openalex.org/W2767949765","https://openalex.org/W2778580105","https://openalex.org/W2785204214","https://openalex.org/W2790774891","https://openalex.org/W2947168485","https://openalex.org/W2953538266","https://openalex.org/W2954151159","https://openalex.org/W3022086662","https://openalex.org/W3191929918","https://openalex.org/W4249855545","https://openalex.org/W4403853345"],"related_works":["https://openalex.org/W4308355586","https://openalex.org/W7162395313","https://openalex.org/W4400491348","https://openalex.org/W4401441898","https://openalex.org/W4388775523","https://openalex.org/W4412960667","https://openalex.org/W4361251116","https://openalex.org/W4408724013","https://openalex.org/W4390306959","https://openalex.org/W4400113989"],"abstract_inverted_index":{"Crime":[0],"prediction":[1,26,142,160],"is":[2,22,131,150],"of":[3,9,15,47,58,66,113,115,164],"great":[4],"significance":[5],"to":[6,53,71],"the":[7,13,23,44,64,73,84,91,109,134,146],"formulation":[8],"policing":[10],"strategies":[11],"and":[12,18,103,118,169],"implementation":[14],"crime":[16,39,50,86,154,159,167,184],"prevention":[17],"control.":[19],"Machine":[20],"learning":[21,36,79,178],"current":[24],"mainstream":[25],"method.":[27],"However,":[28],"few":[29],"studies":[30],"have":[31],"systematically":[32],"compared":[33,144],"different":[34],"machine":[35,78,177],"methods":[37],"for":[38],"prediction.":[40,185],"This":[41],"paper":[42],"takes":[43],"historical":[45,85,153,166],"data":[46,70,87,112,155,168],"public":[48],"property":[49],"from":[51,55],"2015":[52],"2018":[54],"a":[56,59],"section":[57],"large":[60],"coastal":[61],"city":[62],"in":[63,183],"southeast":[65],"China":[67],"as":[68,128],"research":[69],"assess":[72],"predictive":[74],"power":[75],"between":[76],"several":[77],"algorithms.":[80],"Results":[81],"based":[82,151],"on":[83,152],"alone":[88],"suggest":[89],"that":[90,133,149],"LSTM":[92,126],"model":[93,127,135,148],"outperformed":[94],"KNN,":[95],"random":[96],"forest,":[97],"support":[98],"vector":[99],"machine,":[100],"naive":[101],"Bayes,":[102],"convolutional":[104],"neural":[105],"networks.":[106],"In":[107],"addition,":[108],"built":[110,137],"environment":[111,138],"points":[114],"interests":[116],"(POIs)":[117],"urban":[119],"road":[120],"network":[121],"density":[122],"are":[123,180],"input":[124],"into":[125],"covariates.":[129],"It":[130],"found":[132],"with":[136,145,172],"covariates":[139,170],"has":[140],"better":[141],"effect":[143],"original":[147],"alone.":[156],"Therefore,":[157],"future":[158],"should":[161],"take":[162],"advantage":[163],"both":[165],"associated":[171],"criminological":[173],"theories.":[174],"Not":[175],"all":[176],"algorithms":[179],"equally":[181],"effective":[182]},"counts_by_year":[{"year":2026,"cited_by_count":16},{"year":2025,"cited_by_count":27},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":11}],"updated_date":"2026-11-01T11:40:01.658920","created_date":"2020-10-08T00:00:00"}
