A cross media analysis scheme for the semantic interpretation of compound documents is presented. The proposed scheme is essentially a late-fusion mechanism that operates on top of single-media extractors output. Evidence extracted from heterogeneous sources are used to trigger probabilistic inference on a bayesian network that encodes domain knowledge and quantifies causality. Experiments performed on a set of 54 compound documents showed that the proposed scheme is able to exploit the existing cross media relations and achieve performance improvements.