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
.jpg)
- Institución
- Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
- OAI Identificador
- oai:digital.cic.gba.gob.ar:11746/12415
Ver los metadatos del registro completo
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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. |
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2024 |
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2024-06 |
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eng |
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