Ontology Population Framework of MAGNETO for Instantiating Heterogeneous Forensic Data Modalities

Abstract

The growth in digital technologies has influenced three characteristics of information namely the volume, the modality and the frequency. As the amount of information generated by individuals increases, there is a critical need for the Law Enforcement Agencies to exploit all available resources to effectively carry out criminal investigation. Addressing the increasing challenges in handling the large amount of diversified media modalities generated at high-frequency, the paper outlines a systematic approach adopted for the processing and extraction of semantic concepts formalized to assist criminal investigations. The novelty of the proposed framework relies on the semantic processing of heterogeneous data sources including audio-visual footage, speech-to-text, text mining, suspect tracking and identification using distinctive region or pattern. Information extraction from textual data, machine-translated into English from various European languages, uses semantic role labeling. All extracted information is stored in one unifying system based on an ontology developed specifically for this task. The described technologies will be implemented in the Multimedia Analysis and correlation enGine for orgaNised crime prEvention and invesTiga-tiOn (MAGNETO).

Enabling Public Security Text-Based Analytics: A Survey to Outline Research Directions

“…The "Support to Law Enforcement agencies' actions" application area is related to providing complete systems architecture, methodologies, and frameworks for agencies dedicated to ensuring compliance with the laws to maintain public security and social welfare. This set is composed of the works by Badii et al [28] that proposed a system architecture to provide data analytics (including a text mining and analytics module) for supporting decision-making in law enforcement agencies; Bisio et al [29] that proposed an approach to allow law enforcement agencies to detect events, using Twitter traffic monitoring, that compromise public security; Basilio et al [30] that presented a methodology to extract knowledge from police reports for extracting information to support activities related to law enforcement; Behmer et al [31] that proposed a framework to support law enforcement agencies in the investigations and analyzes of organized crime; Basilio et al [32] that developed a method for knowledge discovery in emergency response databases based on police reports; and Hou et al [33] that proposed the Bidirectional Encoder Representation from Transformers based on the Chinese relation extraction algorithm for public security, for security information mining.…”

Arquitectura de interoperabilidad para mejorar las capacidades de análisis de información y toma de decisiones

“…Esta base de conocimiento puede incluir diferentes tipos de información, desde hechos y relaciones entre los datos hasta reglas y algoritmos de inferencia. La KB se nutre de la información procesada y estructurada previamente, permitiendo realizar consultas y generar nuevos conocimientos a través de técnicas de análisis y razonamiento [134]. Esto permite tener una visión global y completa de los datos, eliminando duplicidades y redundancias, y facilitando el acceso y la manipulación de la información consolidada.…”

“…Para lograr esto, se realiza primero un análisis lingüístico detallado de los datos textuales, seguido de la interpretación del significado de las palabras dentro del contexto en que se encuentran. Estos análisis se fundamentan en marcos teóricos de NLP, tanto en el enfoque basado en reglas como en el enfoque estadístico, este último empleando algoritmos de ML o, más recientemente, técnicas DNN [134].…”