—We address the problem of the computational difficulties occurring by the heavy processing load required by the use of the Dempster-Shafer Theory (DST) in Information Retrieval. Specifically, we focus our efforts on the measure of performance known as the Jousselme distance between two basic probability assignments (or bodies of evidences). We discuss first the extension of the Jousselme distance from the DST to the Dezert- Smarandache Theory, a generalization of the DST. It is followed by an introduction to two new metrics we have developed: a Hamming inspired metric for evidences, and a metric based on the degree of shared uncertainty. The performances of theses metrics are compared one to each other.
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