The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Classification of Complaints for Criminal Intelligence Purposes
|
|
Author(s): Pauline Rousseau (CY Cergy Paris University, France), Dimitris Kotzinos (CY Cergy Paris University, France)and Daniel Camara (Pole Judiciaire Gendarmerie Nationale, France)
Copyright: 2023
Pages: 28
Source title:
Handbook of Research on Applied Artificial Intelligence and Robotics for Government Processes
Source Author(s)/Editor(s): David Valle-Cruz (Universidad Autónoma del Estado de México, Mexico), Nely Plata-Cesar (Universidad Autónoma del Estado de México, Mexico)and Jacobo Leonardo González-Ruíz (Universidad Autónoma del Estado de México, Mexico)
DOI: 10.4018/978-1-6684-5624-8.ch012
Purchase
|
Abstract
The increase in the volume of available data is changing how people perceive their own fields and how the people may interact with this surplus of information. Public security is not different; law enforcement agencies (LEAs) now have available a large quantity of information to help them fight criminality. One challenging problem is to classify/predict criminal activities. The differentiation over two different complaints may only be clear through the careful analysis of complaints' open text fields (e.g., the modus operandi), where the specificity of the perpetrated crime is described. Sometimes the intention behind a crime is not evident unless it is correlated to other crimes and patterns get extracted from them. This chapter shows that it is possible to classify criminal data using machine learning-based methods and that open text fields, such as the modus operandi, may play a fundamental role in the performance of the classification.
Related Content
|
Kamel Mouloudj, Vu Lan Oanh LE, Achouak Bouarar, Ahmed Chemseddine Bouarar, Dachel Martínez Asanza, Mayuri Srivastava.
© 2024.
20 pages.
|
|
José Eduardo Aleixo, José Luís Reis, Sandrina Francisca Teixeira, Ana Pinto de Lima.
© 2024.
52 pages.
|
|
Jorge Figueiredo, Isabel Oliveira, Sérgio Silva, Margarida Pocinho, António Cardoso, Manuel Pereira.
© 2024.
24 pages.
|
|
Fatih Pinarbasi.
© 2024.
20 pages.
|
|
Stavros Kaperonis.
© 2024.
25 pages.
|
|
Thomas Rui Mendes, Ana Cristina Antunes.
© 2024.
24 pages.
|
|
Nuno Geada.
© 2024.
12 pages.
|
|
|