3. The method of claim 2 , further comprising: splitting the first document-term matrix into N non-overlapping first document-term submatrices for the first language; splitting the second document-term matrix into N non-overlapping second document-term submatrices for the second language; for each value i of N; applying the algorithm to the ith first document-term submatrix for the first language and the ith second document-term submatrix for the second language to create an ith set of stored matrices; storing the ith set of stored matrices that in an ith instance of the algorithm; applying the ith set of stored matrices to the ith first document-term submatrix of the first language to create ith first translingual text representation (TTR) vectors in the first language; accumulating each of the ith first TTR vectors as rows in an ith first TTR submatrix for the first language; and applying the ith set of stored matrices to the ith second document-term submatrix of the second language, to produce an ith second TTR submatrix for the second language; and by appending columns together: combining the first TTR submatrices for the first language into a first TTR matrix for the first language, and combining the second TTR submatrices for the second language into a second TTR matrix for the second language.
2. The method of claim 1 , wherein the algorithm is an oriented principal component analysis algorithm.