In this paper we propose a model for relevance feedback. Our model combines evidence from user's relevance assessments with algorithms describing how words are used within documents. We motivate the use of the Dempster-Shafer framework as an appropriate theory for modelling combination of evidence. This model also incorporates the uncertain nature of information retrieval and relevance feedback. We discuss the sources of uncertainty in combining evidence in information retrievel and the importance of combining evidence in relevance feedback. We also present results from a series of experiments that highlight various aspects of our approach and discuss our findings.