6. A method of performing two-pass probabilistic latent semantic analysis, the method comprising: receiving a set of data objects at an input of a computing device; clustering the set of data objects into a plurality of groups; performing a first pass of performing probabilistic latent semantic analysis on the groups; estimating a ranking of each latent class; eliminating low probability links between the set of data objects and the latent classes based on the rankings, the low probability links being determined based on a predetermined probability threshold; determining remaining links between the set of data objects and the latent classes; and performing a second pass of probabilistic latent semantic analysis, using a processor of the computing device, on a result of the first pass based on the remaining links between the set of data objects and the latent classes.
6. A method of performing two-pass probabilistic latent semantic analysis, the method comprising: receiving a set of data objects at an input of a computing device; clustering the set of data objects into a plurality of groups; performing a first pass of performing probabilistic latent semantic analysis on the groups; estimating a ranking of each latent class; eliminating low probability links between the set of data objects and the latent classes based on the rankings, the low probability links being determined based on a predetermined probability threshold; determining remaining links between the set of data objects and the latent classes; and performing a second pass of probabilistic latent semantic analysis, using a processor of the computing device, on a result of the first pass based on the remaining links between the set of data objects and the latent classes. 10. The method of claim 6 , wherein the estimating the ranking includes determining, for each of the latent classes, the ranking of that latent class given a respective one of the objects, according to the following calculation: 
 P ( z|d )= P ( d ) −1 P ( d|z ) P ( z )∝ P ( d|z ) P ( z ), wherein z is the latent class and d is the respective given object.