{"id":"https://openalex.org/W3108650604","doi":"https://doi.org/10.1109/access.2020.3036715","title":"Spatio-Temporal Prediction of Baltimore Crime Events Using CLSTM Neural Networks","display_name":"Spatio-Temporal Prediction of Baltimore Crime Events Using CLSTM Neural Networks","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3108650604","doi":"https://doi.org/10.1109/access.2020.3036715","mag":"3108650604"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3036715","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3036715","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09252093.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,"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"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09252093.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074919333","display_name":"Nicolas Esquivel","orcid":null},"institutions":[{"id":"https://openalex.org/I13897259","display_name":"Universidad Andr\u00e9s Bello","ror":"https://ror.org/01qq57711","country_code":"CL","type":"education","lineage":["https://openalex.org/I13897259"]}],"countries":["CL"],"is_corresponding":false,"raw_author_name":"Nicolas Esquivel","raw_affiliation_strings":["Facultad de Ingenieria, Universidad Andres Bello, Santiago, Chile"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Facultad de Ingenieria, Universidad Andres Bello, Santiago, Chile","institution_ids":["https://openalex.org/I13897259"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030296026","display_name":"Orietta Nicolis","orcid":"https://orcid.org/0000-0001-8046-6983"},"institutions":[{"id":"https://openalex.org/I13897259","display_name":"Universidad Andr\u00e9s Bello","ror":"https://ror.org/01qq57711","country_code":"CL","type":"education","lineage":["https://openalex.org/I13897259"]}],"countries":["CL"],"is_corresponding":false,"raw_author_name":"Orietta Nicolis","raw_affiliation_strings":["Facultad de Ingenieria, Universidad Andres Bello, Santiago, Chile"],"raw_orcid":"https://orcid.org/0000-0001-8046-6983","affiliations":[{"raw_affiliation_string":"Facultad de Ingenieria, Universidad Andres Bello, Santiago, Chile","institution_ids":["https://openalex.org/I13897259"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044038720","display_name":"Billy Peralta","orcid":"https://orcid.org/0000-0002-5457-2157"},"institutions":[{"id":"https://openalex.org/I13897259","display_name":"Universidad Andr\u00e9s Bello","ror":"https://ror.org/01qq57711","country_code":"CL","type":"education","lineage":["https://openalex.org/I13897259"]}],"countries":["CL"],"is_corresponding":false,"raw_author_name":"Billy Peralta","raw_affiliation_strings":["Facultad de Ingenieria, Universidad Andres Bello, Santiago, Chile"],"raw_orcid":"https://orcid.org/0000-0002-5457-2157","affiliations":[{"raw_affiliation_string":"Facultad de Ingenieria, Universidad Andres Bello, Santiago, Chile","institution_ids":["https://openalex.org/I13897259"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103185957","display_name":"Jorge Mateu","orcid":"https://orcid.org/0000-0002-2868-7604"},"institutions":[{"id":"https://openalex.org/I10902133","display_name":"Universitat Jaume I","ror":"https://ror.org/02ws1xc11","country_code":"ES","type":"education","lineage":["https://openalex.org/I10902133"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Jorge Mateu","raw_affiliation_strings":["Department of Mathematics, Universitat Jaume I, Castell\u00f3n, Spain"],"raw_orcid":"https://orcid.org/0000-0002-2868-7604","affiliations":[{"raw_affiliation_string":"Department of Mathematics, Universitat Jaume I, Castell\u00f3n, Spain","institution_ids":["https://openalex.org/I10902133"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":8.0642,"has_fulltext":true,"cited_by_count":42,"citation_normalized_percentile":{"value":0.97524238,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"8","issue":null,"first_page":"209101","last_page":"209112"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10574","display_name":"Crime Patterns and Interventions","score":0.998199999332428,"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":0.998199999332428,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9973999857902527,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9901000261306763,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7205121517181396},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5912351608276367},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5877804160118103},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5855191946029663},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5359654426574707},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5294727087020874},{"id":"https://openalex.org/keywords/damages","display_name":"Damages","score":0.5107340812683105},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4711388945579529},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.4506346583366394},{"id":"https://openalex.org/keywords/long-short-term-memory","display_name":"Long short term memory","score":0.43490564823150635},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42207443714141846}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7205121517181396},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5912351608276367},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5877804160118103},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5855191946029663},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5359654426574707},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5294727087020874},{"id":"https://openalex.org/C2777381055","wikidata":"https://www.wikidata.org/wiki/Q308922","display_name":"Damages","level":2,"score":0.5107340812683105},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4711388945579529},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.4506346583366394},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.43490564823150635},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42207443714141846},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2020.3036715","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3036715","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09252093.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,"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:dnet:repositoriun::cafb57b7144a58be9f5bb913c65e5591","is_oa":true,"landing_page_url":"http://hdl.handle.net/10234/192286","pdf_url":null,"source":{"id":"https://openalex.org/S4306402641","display_name":"LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Cient\u00edficas)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4383465926","host_organization_name":"LA Referencia","host_organization_lineage":["https://openalex.org/I4383465926"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:doaj.org/article:4f5a72b8683b4dd583ba5641b1b7a7ce","is_oa":true,"landing_page_url":"https://doaj.org/article/4f5a72b8683b4dd583ba5641b1b7a7ce","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,"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 209101-209112 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3036715","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3036715","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09252093.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,"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":[{"score":0.7799999713897705,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G418889453","display_name":null,"funder_award_id":"PID2019-107392RBI00","funder_id":"https://openalex.org/F4320322930","funder_display_name":"Ministerio de Ciencia e Innovaci\u00f3n"},{"id":"https://openalex.org/G6489310099","display_name":null,"funder_award_id":"ID1201478","funder_id":"https://openalex.org/F4320338073","funder_display_name":"Fondo Nacional de Desarrollo Cient\u00edfico y Tecnol\u00f3gico"}],"funders":[{"id":"https://openalex.org/F4320322930","display_name":"Ministerio de Ciencia e Innovaci\u00f3n","ror":"https://ror.org/034900433"},{"id":"https://openalex.org/F4320338073","display_name":"Fondo Nacional de Desarrollo Cient\u00edfico y Tecnol\u00f3gico","ror":"https://ror.org/02ap3w078"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3108650604.pdf","grobid_xml":"https://content.openalex.org/works/W3108650604.grobid-xml"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W1485009520","https://openalex.org/W1522301498","https://openalex.org/W1976526581","https://openalex.org/W2064675550","https://openalex.org/W2075419483","https://openalex.org/W2101156862","https://openalex.org/W2143545157","https://openalex.org/W2321540385","https://openalex.org/W2548307244","https://openalex.org/W2582575101","https://openalex.org/W2618925809","https://openalex.org/W2735466839","https://openalex.org/W2795847383","https://openalex.org/W2805373902","https://openalex.org/W2885687276","https://openalex.org/W2888096023","https://openalex.org/W2897876396","https://openalex.org/W2898970737","https://openalex.org/W2903764284","https://openalex.org/W2905290611","https://openalex.org/W2921540052","https://openalex.org/W2942623744","https://openalex.org/W2950072808","https://openalex.org/W2953514083","https://openalex.org/W2955156106","https://openalex.org/W2963440212","https://openalex.org/W2964121744","https://openalex.org/W2974460824","https://openalex.org/W2982441595","https://openalex.org/W3005975264","https://openalex.org/W3011375118","https://openalex.org/W3020673398","https://openalex.org/W3046302739","https://openalex.org/W3055194044","https://openalex.org/W3060975791","https://openalex.org/W3088611441","https://openalex.org/W3106189942","https://openalex.org/W3132123706","https://openalex.org/W4250574571","https://openalex.org/W6631190155","https://openalex.org/W6674878840","https://openalex.org/W6738448952","https://openalex.org/W6749790333","https://openalex.org/W6751762632","https://openalex.org/W6756498786","https://openalex.org/W6761974947","https://openalex.org/W6765168246","https://openalex.org/W6765317628","https://openalex.org/W6780990812","https://openalex.org/W6781639888"],"related_works":["https://openalex.org/W2912153778","https://openalex.org/W4288108708","https://openalex.org/W4387163678","https://openalex.org/W2973430807","https://openalex.org/W4385280324","https://openalex.org/W2890685186","https://openalex.org/W2984436043","https://openalex.org/W4390245176","https://openalex.org/W3173606726","https://openalex.org/W4285503423"],"abstract_inverted_index":{"Crime":[0],"activity":[1,37],"in":[2,139,169],"many":[3],"cities":[4,26,41],"worldwide":[5],"causes":[6],"significant":[7],"damages":[8],"to":[9,42,59,75,103,127,130,160,173],"the":[10,40,64,105,111,132,170,181],"lives":[11],"of":[12,30,35,47,66,107,113,119,134,149,180,190],"victims":[13],"and":[14,24,50,153,165,200],"their":[15],"surrounding":[16],"communities.":[17],"It":[18],"is":[19,144,158,185],"a":[20,44,80,86,93,128,188],"public":[21],"disorder":[22],"problem,":[23],"big":[25],"experience":[27],"large":[28],"amounts":[29],"crime":[31,76,108,121],"events.":[32],"Spatio-temporal":[33],"prediction":[34,78,178],"crimes":[36],"can":[38],"help":[39],"have":[43],"better":[45],"allocation":[46],"police":[48],"resources":[49],"surveillance.":[51],"Deep":[52],"learning":[53],"techniques":[54],"are":[55,71,101,123],"considered":[56],"efficient":[57],"tools":[58],"predict":[60,104,131],"future":[61,140,175],"events":[62,109,122],"analyzing":[63],"behavior":[65],"past":[67,120,171],"ones;":[68],"however,":[69],"they":[70],"not":[72],"usually":[73],"applied":[74],"event":[77,138],"using":[79,194],"spatio-temporal":[81],"approach.":[82],"In":[83,116],"this":[84],"paper,":[85],"Convolutional":[87],"Neural":[88],"Network":[89],"(CNN)":[90],"together":[91],"with":[92],"Long-Short":[94],"Term":[95],"Memory":[96],"(LSTM)":[97],"network":[98,184],"(thus":[99],"CLSTM-NN)":[100],"proposed":[102,156,182],"presence":[106,133],"over":[110],"city":[112],"Baltimore":[114],"(USA).":[115],"particular,":[117],"matrices":[118],"used":[124],"as":[125],"input":[126],"CLSTM-NN":[129],"at":[135],"least":[136],"one":[137],"days.":[141],"The":[142,155,177],"model":[143],"implemented":[145],"on":[146],"two":[147],"types":[148],"events:":[150],"\u201cstreet":[151],"robbery\u201d":[152],"\u201clarceny\u201d.":[154],"procedure":[157],"able":[159],"take":[161],"into":[162],"account":[163],"spatial":[164],"temporal":[166],"correlations":[167],"present":[168],"data":[172],"improve":[174],"prediction.":[176],"performance":[179],"neural":[183],"assessed":[186],"under":[187],"number":[189],"controlled":[191],"plausible":[192],"scenarios,":[193],"some":[195],"standard":[196],"metrics":[197],"(Accuracy,":[198],"AUC-ROC,":[199],"AUC-PR).":[201]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":1}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
