2. The method of claim 1 wherein determining the at least one concept related to the search query comprises: accessing a concept knowledge base having a plurality of concept data objects and a plurality of term data objects associated with at least one of the plurality of concept data objects; matching at least one of the at least one search term with at least one of the plurality of term data objects to generate a first term set containing term data objects from the concept knowledge base that match the at least one search term; and generating a concept set containing at least one concept data object associated with one or more of the term data objects in the first term set.
3. The method of claim 2 further comprising: generating a concept vector for each concept data object in the concept set, the concept vector comprising a dimension for each term data object associated with the concept data object, a magnitude of the dimension based on a weight of the association of the term data object with the concept data object; and generating a document vector for the at least one returned document, the document vector comprising a dimension for each of a plurality of terms in the document, a magnitude of the dimension based on a frequency of occurrence of each of the plurality of terms; wherein evaluating the similarity between the at least one returned document and the at least one concept is based on a fuzzy membership score determined by comparing the concept vector to the document vector.