{"id":"https://openalex.org/W4214587150","doi":"https://doi.org/10.1155/2022/4830411","title":"Predicting and Preventing Crime: A Crime Prediction Model Using San Francisco Crime Data by Classification Techniques","display_name":"Predicting and Preventing Crime: A Crime Prediction Model Using San Francisco Crime Data by Classification Techniques","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4214587150","doi":"https://doi.org/10.1155/2022/4830411"},"language":"en","primary_location":{"id":"doi:10.1155/2022/4830411","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2022/4830411","pdf_url":"https://downloads.hindawi.com/journals/complexity/2022/4830411.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://downloads.hindawi.com/journals/complexity/2022/4830411.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038898162","display_name":"Muzammil Khan","orcid":"https://orcid.org/0000-0003-4656-1041"},"institutions":[{"id":"https://openalex.org/I335365548","display_name":"University of Swat","ror":"https://ror.org/01q9mqz67","country_code":"PK","type":"education","lineage":["https://openalex.org/I335365548"]}],"countries":["PK"],"is_corresponding":true,"raw_author_name":"Muzammil Khan","raw_affiliation_strings":["Department of Computer & Software Technology, University of Swat, Swat, Pakistan"],"affiliations":[{"raw_affiliation_string":"Department of Computer & Software Technology, University of Swat, Swat, Pakistan","institution_ids":["https://openalex.org/I335365548"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086268621","display_name":"Azmat Ali","orcid":"https://orcid.org/0000-0001-5546-5866"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Azmat Ali","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039868149","display_name":"Yasser Alharbi","orcid":"https://orcid.org/0000-0002-6523-628X"},"institutions":[{"id":"https://openalex.org/I4210088963","display_name":"University of Ha'il","ror":"https://ror.org/013w98a82","country_code":"SA","type":"education","lineage":["https://openalex.org/I4210088963"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Yasser Alharbi","raw_affiliation_strings":["College of Computer Science, University of Hail, Hail, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, University of Hail, Hail, Saudi Arabia","institution_ids":["https://openalex.org/I4210088963"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5038898162"],"corresponding_institution_ids":["https://openalex.org/I335365548"],"apc_list":{"value":2300,"currency":"USD","value_usd":2300},"apc_paid":{"value":2300,"currency":"USD","value_usd":2300},"fwci":15.426,"has_fulltext":true,"cited_by_count":40,"citation_normalized_percentile":{"value":0.98985651,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"2022","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10574","display_name":"Crime Patterns and Interventions","score":0.9930999875068665,"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":0.9930999875068665,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9817000031471252,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9398999810218811,"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/random-forest","display_name":"Random forest","score":0.8388296365737915},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.7779524326324463},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.7671312093734741},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.7631785869598389},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6715117692947388},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.6041964292526245},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5451769232749939},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4987003803253174},{"id":"https://openalex.org/keywords/crime-analysis","display_name":"Crime analysis","score":0.4861990809440613},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.442670613527298},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3525291085243225},{"id":"https://openalex.org/keywords/criminology","display_name":"Criminology","score":0.2025040090084076},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.20232635736465454},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.18483024835586548},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.09880194067955017}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.8388296365737915},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.7779524326324463},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.7671312093734741},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.7631785869598389},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6715117692947388},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.6041964292526245},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5451769232749939},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4987003803253174},{"id":"https://openalex.org/C2776876444","wikidata":"https://www.wikidata.org/wiki/Q2845200","display_name":"Crime analysis","level":2,"score":0.4861990809440613},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.442670613527298},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3525291085243225},{"id":"https://openalex.org/C73484699","wikidata":"https://www.wikidata.org/wiki/Q161733","display_name":"Criminology","level":1,"score":0.2025040090084076},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.20232635736465454},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.18483024835586548},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.09880194067955017}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1155/2022/4830411","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2022/4830411","pdf_url":"https://downloads.hindawi.com/journals/complexity/2022/4830411.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:hin:complx:4830411","is_oa":false,"landing_page_url":"http://downloads.hindawi.com/journals/complexity/2022/4830411.xml","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},{"id":"pmh:oai:doaj.org/article:fb2409b6110a4c29bfe3f1c54e2d4acc","is_oa":true,"landing_page_url":"https://doaj.org/article/fb2409b6110a4c29bfe3f1c54e2d4acc","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Complexity, Vol 2022 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/2022/4830411","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2022/4830411","pdf_url":"https://downloads.hindawi.com/journals/complexity/2022/4830411.pdf","source":{"id":"https://openalex.org/S207319443","display_name":"Complexity","issn_l":"1076-2787","issn":["1076-2787","1099-0526"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complexity","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6000000238418579,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4214587150.pdf","grobid_xml":"https://content.openalex.org/works/W4214587150.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W3822628","https://openalex.org/W73332463","https://openalex.org/W161431362","https://openalex.org/W1453396990","https://openalex.org/W1501362048","https://openalex.org/W1516899372","https://openalex.org/W2120240539","https://openalex.org/W2140190241","https://openalex.org/W2163757302","https://openalex.org/W2188164722","https://openalex.org/W2217137288","https://openalex.org/W2417999172","https://openalex.org/W2470972006","https://openalex.org/W2554833420","https://openalex.org/W2560070550","https://openalex.org/W2586068811","https://openalex.org/W2593914038","https://openalex.org/W2911964244","https://openalex.org/W2926613627","https://openalex.org/W3024826585","https://openalex.org/W3191664920"],"related_works":["https://openalex.org/W2967733078","https://openalex.org/W3204430031","https://openalex.org/W3137904399","https://openalex.org/W4310492845","https://openalex.org/W2885778889","https://openalex.org/W4310224730","https://openalex.org/W2766514146","https://openalex.org/W4289703016","https://openalex.org/W2885516856","https://openalex.org/W3094138326"],"abstract_inverted_index":{"The":[0,25,50,109,140,168],"crime":[1,29,73,107,184],"is":[2,7,18,93,132,151],"difficult":[3],"to":[4,57,95],"predict;":[5],"it":[6],"random":[8],"and":[9,34,45,78,99,116,125,128,137,170,189],"possibly":[10],"can":[11,173],"occur":[12],"anywhere":[13],"at":[14,185],"any":[15,23],"time,":[16,188],"which":[17,63],"a":[19,28,106,166,186],"challenging":[20],"issue":[21],"for":[22,65,135,158],"society.":[24],"study":[26],"proposes":[27],"prediction":[30,38,149,171],"model":[31,51,131,150,172],"by":[32,82],"analyzing":[33],"comparing":[35],"three":[36],"known":[37],"classification":[39],"algorithms:":[40],"Naive":[41,112],"Bayes,":[42,113],"Random":[43,114],"Forest,":[44,115],"Gradient":[46,117,145],"Boosting":[47,118,146],"Decision":[48,119,147],"Tree.":[49],"analyzes":[52],"the":[53,68,97,101,129,144,154,175,179,183],"top":[54],"ten":[55],"crimes":[56,104],"make":[58],"predictions":[59],"about":[60],"different":[61],"categories,":[62],"account":[64],"97%":[66],"of":[67,87,103,111],"incidents.":[69],"These":[70],"two":[71,156],"significant":[72],"classes,":[74],"that":[75,143],"is,":[76],"violent":[77],"nonviolent,":[79],"are":[80,122],"created":[81],"merging":[83],"multiple":[84],"smaller":[85],"classes":[86],"crimes.":[88],"Exploratory":[89],"data":[90,164],"analysis":[91,169],"(EDA)":[92],"performed":[94],"identify":[96],"patterns":[98],"understand":[100],"trends":[102],"using":[105],"dataset.":[108],"accuracies":[110],"Tree":[120,148],"techniques":[121,157],"65.82%,":[123],"63.43%,":[124],"98.5%,":[126],"respectively,":[127],"proposed":[130],"further":[133],"evaluated":[134],"precision":[136],"recall":[138],"matrices.":[139],"results":[141],"show":[142],"better":[152],"than":[153],"other":[155],"predicting":[159],"crime,":[160],"based":[161],"on":[162],"historical":[163],"from":[165],"city.":[167],"help":[174],"security":[176],"agencies":[177],"utilize":[178],"resources":[180],"efficiently,":[181],"anticipate":[182],"specific":[187],"serve":[190],"society":[191],"well.":[192]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
