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Ontology Population Framework of MAGNETO for Instantiating Heterogeneous Forensic Data Modalities

: Behmer, Ernst-Josef; Chandramouli, K.; Garrido, V.; Mühlenberg, Dirk; Müller, Dennis; Müller, Wilmuth; Pallmer, Dirk; Perez, F.; Piatrik, T.; Vargas, C.

Postprint urn:nbn:de:0011-n-5491508 (681 KByte PDF)
MD5 Fingerprint: 8b4bb9940a9841f2a1b505d5b82de911
Created on: 01.12.2019

MacIntyre, John (Ed.) ; International Federation for Information Processing -IFIP-:
Artificial Intelligence Applications and Innovations : 15th IFIP WG 12.5 International Conference, AIAI 2019, Hersonissos, Crete, Greece, May 24-26, 2019, Proceedings
Cham: Springer Nature, 2019 (IFIP advances in information and communication technology 559)
ISBN: 978-3-030-19822-0 (Print)
ISBN: 978-3-030-19823-7 (Online)
International Conference on Artificial Intelligence Applications and Innovations (AIAI) <15, 2019, Crete>
European Commission EC
H2020; 786629; MAGNETO
Multimedia Analysis and Correlation Engine for Organised Crime Prevention and Investigation
Conference Paper, Electronic Publication
Fraunhofer IOSB ()
information extraction; ontology population; law enforcement

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 invesTigatiOn (MAGNETO).