Routing by Discriminant Projection : TREC - 4 Kok

We present document routing as a standard problem in discriminant analysis. The standard solution involves the inversion of a large matrix whose dimension is the number of indexed terms. Typically, the solution does not exist because the number of training documents are much smaller compared to the number of terms. We show that one can project this raw document space into a lower dimensional space where solution is possible. Our projection algorithm exploits the characterisitics of the empty space, using only the training documents for eecient coding of the relevance information. Its complexity is linear with respect to the number of terms, and second order with respect to the number of training documents. We can therefore fully exploit the power of discriminant analysis without imposing severe computational and storage constraints.