1. A method of language modeling of a document comprising: computing, by a computer processor, a plurality of local probabilities of a current document; determining a vector representation of the current document in a latent semantic analysis (LSA) space at a first time based on a first number of words present in the current document from a second time to the first time, wherein the second time precedes the first time; computing, by a computer processor, a plurality of global probabilities based upon the vector representation of the current document in an LSA space; and combining the local probabilities and the global probabilities to produce a language modeling.
12. The method of claim 1 wherein the plurality of global probabilities Pr(w q |H q−1 ) for a particular word w q , for an associated history of the word, H q−1 , for the current document {tilde over (d)} q−i , as: Pr(w q |H q−1 )=Pr(w q |{tilde over (d)} q−i ), based upon the vector representation of the current document in an LSA space.