17. A method comprising: receiving as a training set, a set of ranked query-document pairs; summarizing global text information from documents in the training set by computing a first matrix; summarizing rank information from the training data by computing a second matrix; applying the first matrix to the second matrix to smooth the second matrix to obtain a third matrix; computing eigenvectors of the third matrix as column vectors of a subspace; and reporting the subspace as a latent semantic space for ranking.
20. The method of claim 17 wherein the latent semantic space for ranking is defined as Ω p (W*|D) where W*=argmax WεR m×p tr{W T (βδC 1 +(1−β)C 2 )W} such that W T W=I.