Police report linking algorithm based on Named Entity Recognition

Autores
Álvarez, Mauro Daniel; Antonelli, Leandro
Año de publicación
2024
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Police reports include a complaint made by the victim of a crime. This complaint is a story that describes the facts from the victim’s point of view. Most of the time, crimes are perpetrated by unknown authors. This causes cases to be shelved until new evidence arrives. The use of natural language processing allows us to take advantage of non-structured text in victim’s com-plaints by generating links that could lead to the reopening of an archived investigation. Through the use of NER1, it is possible to extract entities of interest from a report of a complaint that arrives and link it with other reports of existing complaints, allowing the generation of a maps of links in order to detect similarities between cases. This idea will increase the possibility that cases in archived status being opened.
Materia
Ciencias de la Computación e Información
NLP
NER
police reports
criminal justice
graphs
similarity
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
CIC Digital (CICBA)
Institución
Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
OAI Identificador
oai:digital.cic.gba.gob.ar:11746/12415

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repository_id_str 9441
network_name_str CIC Digital (CICBA)
spelling Police report linking algorithm based on Named Entity RecognitionÁlvarez, Mauro DanielAntonelli, LeandroCiencias de la Computación e InformaciónNLPNERpolice reportscriminal justicegraphssimilarityPolice reports include a complaint made by the victim of a crime. This complaint is a story that describes the facts from the victim’s point of view. Most of the time, crimes are perpetrated by unknown authors. This causes cases to be shelved until new evidence arrives. The use of natural language processing allows us to take advantage of non-structured text in victim’s com-plaints by generating links that could lead to the reopening of an archived investigation. Through the use of NER1, it is possible to extract entities of interest from a report of a complaint that arrives and link it with other reports of existing complaints, allowing the generation of a maps of links in order to detect similarities between cases. This idea will increase the possibility that cases in archived status being opened.2024-06info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttps://digital.cic.gba.gob.ar/handle/11746/12415enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/reponame:CIC Digital (CICBA)instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Airesinstacron:CICBA2025-10-23T11:14:14Zoai:digital.cic.gba.gob.ar:11746/12415Institucionalhttp://digital.cic.gba.gob.arOrganismo científico-tecnológicoNo correspondehttp://digital.cic.gba.gob.ar/oai/snrdmarisa.degiusti@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:94412025-10-23 11:14:14.753CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse
dc.title.none.fl_str_mv Police report linking algorithm based on Named Entity Recognition
title Police report linking algorithm based on Named Entity Recognition
spellingShingle Police report linking algorithm based on Named Entity Recognition
Álvarez, Mauro Daniel
Ciencias de la Computación e Información
NLP
NER
police reports
criminal justice
graphs
similarity
title_short Police report linking algorithm based on Named Entity Recognition
title_full Police report linking algorithm based on Named Entity Recognition
title_fullStr Police report linking algorithm based on Named Entity Recognition
title_full_unstemmed Police report linking algorithm based on Named Entity Recognition
title_sort Police report linking algorithm based on Named Entity Recognition
dc.creator.none.fl_str_mv Álvarez, Mauro Daniel
Antonelli, Leandro
author Álvarez, Mauro Daniel
author_facet Álvarez, Mauro Daniel
Antonelli, Leandro
author_role author
author2 Antonelli, Leandro
author2_role author
dc.subject.none.fl_str_mv Ciencias de la Computación e Información
NLP
NER
police reports
criminal justice
graphs
similarity
topic Ciencias de la Computación e Información
NLP
NER
police reports
criminal justice
graphs
similarity
dc.description.none.fl_txt_mv Police reports include a complaint made by the victim of a crime. This complaint is a story that describes the facts from the victim’s point of view. Most of the time, crimes are perpetrated by unknown authors. This causes cases to be shelved until new evidence arrives. The use of natural language processing allows us to take advantage of non-structured text in victim’s com-plaints by generating links that could lead to the reopening of an archived investigation. Through the use of NER1, it is possible to extract entities of interest from a report of a complaint that arrives and link it with other reports of existing complaints, allowing the generation of a maps of links in order to detect similarities between cases. This idea will increase the possibility that cases in archived status being opened.
description Police reports include a complaint made by the victim of a crime. This complaint is a story that describes the facts from the victim’s point of view. Most of the time, crimes are perpetrated by unknown authors. This causes cases to be shelved until new evidence arrives. The use of natural language processing allows us to take advantage of non-structured text in victim’s com-plaints by generating links that could lead to the reopening of an archived investigation. Through the use of NER1, it is possible to extract entities of interest from a report of a complaint that arrives and link it with other reports of existing complaints, allowing the generation of a maps of links in order to detect similarities between cases. This idea will increase the possibility that cases in archived status being opened.
publishDate 2024
dc.date.none.fl_str_mv 2024-06
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv https://digital.cic.gba.gob.ar/handle/11746/12415
url https://digital.cic.gba.gob.ar/handle/11746/12415
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:CIC Digital (CICBA)
instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
instacron:CICBA
reponame_str CIC Digital (CICBA)
collection CIC Digital (CICBA)
instname_str Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
instacron_str CICBA
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repository.name.fl_str_mv CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
repository.mail.fl_str_mv marisa.degiusti@sedici.unlp.edu.ar
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