RT Journal Article
T1 Ontology-driven automated reasoning about property crimes
A1 Navarrete, Francisco
A1 Garrido, Ángel L.
A1 Bobed, Carlos
A1 Atencia-Arcas, Manuel
A1 Vallecillo-Moreno, Antonio Jesús
K1 Proceso en lenguaje natural (Informática)
K1 Aprendizaje automático (Inteligencia artificial)
K1 Ontología
K1 Minería de datos
K1 Delincuencia
K1 Derecho de propiedad
AB The classification of police reports according to the typification of the criminal act described in them is not an easy task. The reports are written in natural language and often present missing, imprecise, or even inconsistent information, or lack sufficient details to make a clear decision. Focusing on property crimes, the aim of this work is to assist judges in this classification process by automatically extracting information from police reports and producing a list of possible classifications of crimes accompanied by a degree of confidence in each of them. The work follows the design science research methodology, developing a tool as an artifact. The proposal uses information extraction techniques to obtain the data from the reports, guided by an ontology developed for the Spanish legal system on property crimes. Probabilistic inference mechanisms are used to select the set of articles of the law that could apply to a given case, even when the evidence does not allow an unambiguous identification. The proposal has been empirically validated in a real environment with judges and prosecutors. The results show that the proposal is feasible and usable, and could be effective in assisting judges to classify property crime reports.
PB Springer
YR 2024
FD 2024
LK https://hdl.handle.net/10630/32487
UL https://hdl.handle.net/10630/32487
LA eng
NO Navarrete, F., Garrido, Á.L., Bobed, C. et al. Ontology-Driven Automated Reasoning About Property Crimes. Bus Inf Syst Eng (2024). https://doi.org/10.1007/s12599-024-00886-3
NO Funding for open access charge: Universidad de Málaga / CBUA
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 19 ene 2026