Updating the partial singular value decomposition in latent semantic indexing
Folding-up is faster than either recomputing the PSVD or PSVD-updating, but avoids the degradation in the PSVD that can occur when the folding-in method is used on its own.
Again, results are given showing that this method provides savings in computational time and memory resources without compromising the accuracy of the results.The PSVD-updating method is computationally more expensive than the folding-in method, but better maintains the accuracy of the PSVD.Folding-up is a new method that combines folding-in and PSVD-updating.In a rapidly expanding environment, a term-document matrix is altered often as new documents and terms are added.Recomputing the PSVD of the term-document matrix each time these slight alterations occur can be prohibitively expensive.
Search for updating the partial singular value decomposition in latent semantic indexing:
Updating the PSVD of this matrix is much more efficient than recalculating it after each change. Results are presented illustrating that updating in this Preprint submitted to Elsevier Science 15 July 2005 manner provides tremendous savings in computation time, with little or no signifi-cant reduction in accuracy.