Choosing an appropriate document representation and search strategy for document retrieval has been largely guided by achieving good average performance instead of optimizing the results for each individual query. A model of retrieval based on plausible inference gives us a different perspective and suggests that techniques should be found for combining multiple sources of evidence (or search strategies) into an overall assessment of a document's relevance, rather than attempting to pick a single strategy. In this paper, we explain our approach to plausible inference for retrieval and describe some preliminary experiments designed to test this approach. The experiments use a spreading activation search to implement the plausible inference process. The results show that significant effectiveness improvements are possible using this approach.