Evidence recommendation in forensics based on cyclic meta-paths in heterogeneous information networks

In this article we propose a novel approach for evidence recommendation in digital forensic applications. The so-called Evidence Graph (EG) is a Heterogeneous Information Network (HIN) constructed from entities and relationships extracted from large collections of low quality video footage, collected by surveillance cameras in relation to a crime. The EG has been developed in the context of the EU-funded project LASIE. It presents multiple types of nodes and edges and a generic network schema in which all types of nodes can be connected. In this work, relevant cyclic meta-paths are identified and an iterative scheme for evidence recommendation is proposed and evaluated on real data.